ACADEMIC GUYS

ECON520 HOMEWORK I

1

ECON 520 HOMEWORK I (20 points)
Fall 2022

Due August 17, 2022
Chapter 2

1. Explain the differences between a change in supply and a change in quantity supplied. (2 pts)

2. Indicate whether each of the following situations would shift the supply curve to the left, to the

right, or not at all. (3 pts)
a. An increase in price of inputs
b. An increase in the number of firms in the market
c. An increase in the price of substitutes in production
d. A decrease in the current price of the product
e. A decrease in productivity
f. A decrease in the expected future price of the product

3. If there is excess demand in a perfectly competitive market, does the government need to

intervene to restore the equilibrium price and quantity? Why or why not? (2 pts)

4. Suppose the equilibrium price and quantity of bicycles is determined at $40 and 200 units,
respectively. For some reason, the market price of the bicycles initially increases to $60 and then
decreases to $20. How will these deviations from the equilibrium price be corrected in a perfectly
competitive market? Explain with the help of suitable diagrams. (3 pts)

5. In each of the following situations, graphically show and explain what will happen to the

equilibrium price and the equilibrium quantity for a particular product, which is an inferior good.
(5 pts)

a. The population decreases and productivity increases
b. Income increases and the price of inputs increase
c. The number of firms in the market decreases and income decreases
d. Consumer preference decreases and the expected future price increases
e. The price of a substitute in consumption increases and the price of a substitute in production

increases

6. Using graphs, explain how the equilibrium price and quantity of MP3 will change when: (5 pts)
a. The demand curve for MP3 players shifts to the left and the supply curve for MP3 players

shift to the right.
b. The demand curve for MP3 players shifts to the right and the supply curve for MP3 players

shift to the left, but the supply curve shifts more than the demand curve.
c. The demand curve for MP3 players shifts to the right and the supply curve for MP3 players

shift to the left, but the supply curve shifts less than the demand curve.
d. Both the demand curve and the supply curve for MP3 players shift to the left but the

demand curve shifts more than the supply curve.
e. Both the demand curve and the supply curve for MP3 players shift to the right but the

supply curve shifts more than the demand curve.

roger blair
mark rush

THE ECONOMICS OF
MANAGERIAL DECISIONS

M
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THE ECONOMICS OF
MANAGERIAL DECISIONS

A01_BLAI8235_01_SE_FM_ppi-xxxiv.indd 1 15/09/17 11:33 AM

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THE ECONOMICS OF
MANAGERIAL DECISIONS

ROGER D. BLAIR
University of Florida

MARK RUSH
University of Florida

New York, NY

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Ayan
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ISBN-10: 0133548236
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A01_BLAI8235_01_SE_FM_ppi-xxxiv.indd 4 15/09/17 11:33 AM

For Chau, our kids and our grandkids
Roger D. Blair

For Sue’s memory and our kids
Mark B. Rush

A01_BLAI8235_01_SE_FM_ppi-xxxiv.indd 5 15/09/17 11:33 AM

Roger D. Blair is the Walter J. Matherly Professor and chair of economics at the
University of Florida. He has been a visiting professor at the University of Hawaii
and the University of California–Berkeley as well as Visiting Scholar in Residence,
Center for the Study of American Business, Washington University. Professor Blair’s
research centers on antitrust economics and policy. He has published 10 books and
200 journal articles. He has also served as an antitrust consultant to numerous corpo-
rations, including Intel, Anheuser-Busch, TracFone, Blue Cross–Blue Shield, Waste
Management, Astellas Pharma, and many others.

Mark Rush is a professor of economics at the University of Florida. Prior to teach-
ing at Florida, he was an assistant professor of economics at the University of
Pittsburgh. He has spent eight months at the Kansas City Federal Reserve Bank as a
Visiting Scholar. Professor Rush has taught MBA classes for many years and has won
teaching awards for his classes. He has published in numerous professional journals,
including the Journal of Political Economy; the Journal of Monetary Economics; the
Journal of Money, Credit, and Banking; the Journal of International Money and Finance;
and the Journal of Labor Economics.

ABOUT THE AUTHORS

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PART 1 ECONOMIC FOUNDATIONS

1 Managerial Economics and Decision Making 1
2 Demand and Supply 33
3 Measuring and Using Demand 86

PART 2 MARKET STRUCTURE AND MANAGERIAL
DECISIONS

4 Production and Costs 138
5 Perfect Competition 186
6 Monopoly and Monopolistic Competition 227
7 Cartels and Oligopoly 274
8 Game Theory and Oligopoly 318
9 A Manager’s Guide to Antitrust Policy 371

PART 3 MANAGERIAL DECISIONS

10 Advanced Pricing Decisions 414
11 Decisions About Vertical Integration

and Distribution 465

12 Decisions About Production, Products,
and Location 499

13 Marketing Decisions: Advertising and Promotion 541
14 Business Decisions Under Uncertainty 587
15 Managerial Decisions About Information 635
16 Using Present Value to Make Multiperiod

Managerial Decisions 677

Content on the Web:

Appendix: The Business Plan
Chapter: Franchising Decisions

BRIEF CONTENTS

A01_BLAI8235_01_SE_FM_ppi-xxxiv.indd 7 15/09/17 11:33 AM

viii

CONTENTS

1 Managerial Economics and Decision Making 1
Managers at Sears Holdings Use Opportunity Cost to Make Tough Decisions 1

Introduction 1

1.1 Managerial Economics and Your Career 2

1.2 Firms and Their Organizational Structure 3
Definition of a Firm 3
The Legal Organization of Firms 3

1.3 Profit, Accounting Cost, and Opportunity Cost 6
Goal: Profit Maximization 6
Total Revenue 7
Accounting Cost and Opportunity Cost 8

DECISION SNAPSHOT Sunk Costs in the Stock Market 11

DECISION SNAPSHOT Opportunity Cost at Singing the Blues
Blueberry Farm 13

Comparing Accounting Cost and Opportunity Cost 15
Using Opportunity Cost to Make Decisions 17

SOLVED PROBLEM Resting Energy’s Opportunity Cost 17

1.4 Marginal Analysis 18
The Marginal Analysis Rule 18
Using Marginal Analysis 19

SOLVED PROBLEM How to Respond Profitably to Changes in
Marginal Cost 20

Revisiting How Managers at Sears Holdings Used Opportunity Cost to
Make Tough Decisions 21

Summary: The Bottom Line 22

Key Terms and Concepts 23

Questions and Problems 23

MyLab Economics Auto-Graded Excel Projects 25

APPENDIX The Calculus of Marginal Analysis 28
A. Review of Mathematical Results 28
B. Marginal Benefit and Marginal Cost 29
C. Maximizing Total Surplus 29
D. Maximizing Total Surplus: Example 30

Calculus Questions and Problems 31

PART 1
ECONOMIC FOUNDATIONS

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Contents  ix

2 Demand and Supply 33
Managers at Red Lobster Cope with Early Mortality Syndrome 33

Introduction 33
2.1 Demand 34

Law of Demand 34
Demand Curve 35
Factors That Change Demand 37

DECISION SNAPSHOT Demand for the Cadillac Escalade 41

Changes in Demand: Demand Function 41

SOLVED PROBLEM Demand for Lobster Dinners 43

2.2 Supply 44
Law of Supply 44
Supply Curve 44
Factors That Change Supply 46
Changes in Supply: Supply Function 49

SOLVED PROBLEM The Supply of Gasoline-Powered Cars and the Price
of Hybrid Cars 50

2.3 Market Equilibrium 51
Equilibrium Price and Equilibrium Quantity 51
Demand and Supply Functions: Equilibrium 53

SOLVED PROBLEM Equilibrium Price and Quantity of Plush Toys 54

2.4 Competition and Society 54
Total Surplus 54
Consumer Surplus 58
Producer Surplus 59

SOLVED PROBLEM Total Surplus, Consumer Surplus, and Producer Surplus
in the Webcam Market 60

2.5 Changes in Market Equilibrium 61
Use of the Demand and Supply Model When One Curve Shifts: Demand 61
Use of the Demand and Supply Model When One Curve Shifts: Supply 63
Use of the Demand and Supply Model When Both Curves Shift 64
Demand and Supply Functions: Changes in Market Equilibrium 68

SOLVED PROBLEM Demand and Supply for Tablets Both Change 70

2.6 Price Controls 70
Price Ceiling 70
Price Floor 72

SOLVED PROBLEM The Effectiveness of a Minimum Wage 74

2.7 Using the Demand and Supply Model 75
Predicting Your Costs 75
Predicting Your Price 76

Revisiting How Managers at Red Lobster Coped with Early Mortality Syndrome 78

Summary: The Bottom Line 78

Key Terms and Concepts 79

Questions and Problems 80

MyLab Economics Auto-Graded Excel Projects 83

MANAGERIAL
APPLICATION

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x  Contents

3 Measuring and Using Demand 86
Managers at the Gates Foundation Decide to Subsidize Antimalarial Drugs 86

Introduction 87

3.1 Regression: Estimating Demand 87
The Basics of Regression Analysis 88
Regression Analysis 89
Regression Results: Estimated Coefficients and Estimated
Demand Curve 92

SOLVED PROBLEM Regression Analysis at Your Steak Chain 94

3.2 Interpreting the Results of Regression Analysis 94
Estimated Coefficients 94
Fit of the Regression 99

SOLVED PROBLEM Confidence Intervals and Predictions for the Demand
for Doors 100

3.3 Limitations of Regression Analysis 101
Specification of the Regression Equation 101
Functional Form of the Regression Equation 102

SOLVED PROBLEM Which Regression to Use? 104

3.4 Elasticity 105
The Price Elasticity of Demand 105

DECISION SNAPSHOT Advertising and the Price Elasticity
of Demand 117

Income Elasticity and Cross-Price Elasticity of Demand 117

SOLVED PROBLEM The Price Elasticity of Demand for a Touch-Screen
Smartphone 119

3.5 Regression Analysis and Elasticity 120
Using Regression Analysis 120
Using the Price Elasticity of Demand 122
Using the Income Elasticity of Demand Through the Business Cycle 122

Revisiting How Managers at the Gates Foundation Decided to Subsidize
Antimalarial Drugs 123

Summary: The Bottom Line 123

Key Terms and Concepts 124

Questions and Problems 124

MyLab Economics Auto-Graded Excel Projects 128

CASE STUDY Decision Making Using Regression 130

APPENDIX The Calculus of Elasticity 133
A. Price Elasticity of Demand for a Linear and a Log-Linear Demand Function 133
B. Total Revenue Test 134
C. Income Elasticity of Demand and Cross-Price Elasticity of Demand 135

Calculus Questions and Problems 136

MANAGERIAL
APPLICATION

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Contents  xi

4 Production and Costs 138
Pizza Hut Managers Learn That Size Matters 138

Introduction 138
4.1 Production 139

Production Function 139
Short-Run Production Function 141
Long-Run Production Function 145

SOLVED PROBLEM Marginal Product of Labor at a Bicycle Courier Service 147

4.2 Cost Minimization 147
Cost-Minimization Rule 148
Generalizing the Cost-Minimization Rule 149

SOLVED PROBLEM Cost Minimization at a Construction Firm 150

4.3 Short-Run Cost 150
Fixed Cost, Variable Cost, and Total Cost 151
Average Fixed Cost, Average Variable Cost, and Average Total Cost 152
Marginal Cost 153

DECISION SNAPSHOT Input Price Changes and Changes in the Marginal Cost
of an Eiffel Tower Tour 154

Competitive Return 156
Shifts in Cost Curves 157

DECISION SNAPSHOT Changes in Input Prices and Cost Changes at Shagang
Group 159

SOLVED PROBLEM Calculating Different Costs at a Caribbean Restaurant 161

4.4 Long-Run Cost 162
Long-Run Average Cost 162
Economies of Scale, Constant Returns to Scale, and Diseconomies
of Scale 166

SOLVED PROBLEM Long-Run Average Cost 169

4.5 Using Production and Cost Theory 170
Effects of a Change in the Price of an Input 170
Economies and Diseconomies of Scale 171

Revisiting How Pizza Hut Managers Learned That Size Matters 173

Summary: The Bottom Line 174

Key Terms and Concepts 174

Questions and Problems 175

MyLab Economics Auto-Graded Excel Projects 178

APPENDIX The Calculus of Cost 179
A. Marginal Product 179
B. Cost Minimization 180
C. Marginal Cost and the Marginal/Average Relationship 183

Calculus Questions and Problems 184

MANAGERIAL
APPLICATION

PART 2
MARKET STRUCTURE AND MANAGERIAL DECISIONS

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xii  Contents

5 Perfect Competition 186
Burger King Managers Decide to Let Chickens Have It Their Way 186

Introduction 186

5.1 Characteristics of Competitive Markets 187
Defining Characteristics of Perfect Competition 188
Perfectly Competitive Markets 189

SOLVED PROBLEM The Markets for Fencing and Cell Phones 190

5.2 Short-Run Profit Maximization in Competitive Markets 191
Marginal Analysis 191
Using Marginal Analysis to Maximize Profit 194

DECISION SNAPSHOT Marginal Analysis at the American Cancer Society 196

Changes in Costs 196
Amount of Profit 197
Shutting Down 201

DECISION SNAPSHOT Lundberg Family Farms Responds to a Fall in
the Price of Rice 203

The Firm’s Short-Run Supply Curve 204

DECISION SNAPSHOT A Particleboard Firm Responds to a Fall
in the Price of an Input 205

The Short-Run Market Supply Curve 206

SOLVED PROBLEM Amount of Profit and Shutting Down at a Plywood
Producer 207

5.3 Long-Run Profit Maximization in Competitive Markets 208
Long-Run Effects of an Increase in Market Demand 208
Change in Technology 212

SOLVED PROBLEM The Long Run at a Plywood Producer 214

5.4 Perfect Competition 215
Applying Marginal Analysis 215
Optimal Long-Run Adjustments 215

Revisiting How Burger King Managers Decided to Let Chickens Have
It Their Way 217

Summary: The Bottom Line 218

Key Terms and Concepts 218

Questions and Problems 219

MyLab Economics Auto-Graded Excel Projects 222

APPENDIX The Calculus of Profit Maximization for Perfectly
Competitive Firms 224
A. Marginal Revenue 224
B. Maximizing Profit 224
C. Maximizing Profit: Example 224

Calculus Questions and Problems 226

MANAGERIAL
APPLICATION

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6 Monopoly and Monopolistic Competition 227
Premature Rejoicing by the Managers at KV Pharmaceutical 227

Introduction 228

6.1 A Monopoly Market 228
Defining Characteristics of a Monopoly Market 228
Demand and Marginal Revenue for a Monopoly 229

DECISION SNAPSHOT Is Delta Airlines a Monopoly? 229

SOLVED PROBLEM The Relationship Among the Price Elasticity of Demand,
Marginal Revenue, and Price 233

6.2 Monopoly Profit Maximization 234
Profit Maximization for a Monopoly 234

DECISION SNAPSHOT Profit-Maximizing Range of Prices for Tires 237

Comparing Perfect Competition and Monopoly 239
Barriers to Entry 241

SOLVED PROBLEM Merck’s Profit-Maximizing Price, Quantity, and
Economic Profit 247

6.3 Dominant Firm 247
Dominant Firm’s Profit Maximization 248

DECISION SNAPSHOT How a Technology Firm Responds to Changes
in the Competitive Fringe 251

SOLVED PROBLEM The Demand for Shoes at a Dominant Firm 252

6.4 Monopolistic Competition 252
Defining Characteristics of Monopolistic Competition 253
Short-Run Profit Maximization for a Monopolistically Competitive Firm 253
Long-Run Equilibrium for a Monopolistically Competitive Firm 255

SOLVED PROBLEM J-Phone’s Camera Phone 256

6.5 The Monopoly, Dominant Firm, and Monopolistic Competition
Models 257
Using the Models in Managerial Decision Making 257
Applying the Monopolistic Competition Model 259

Revisiting Premature Rejoicing by the Managers at KV Pharmaceutical 261

Summary: The Bottom Line 261

Key Terms and Concepts 262

Questions and Problems 262

MyLab Economics Auto-Graded Excel Projects 268

APPENDIX The Calculus of Profit Maximization for Firms with
Market Power 269
A. Marginal Revenue Curve 269
B. Elasticity, Price, and Marginal Revenue 269
C. Maximizing Profit 270
D. Maximizing Profit: Example 271

Calculus Questions and Problems 272

MANAGERIAL
APPLICATION

Contents  xiii

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xiv  Contents

7 Cartels and Oligopoly 274
Managers at Major Publishers Read the e-Writing on the e-Wall 274

Introduction 274

7.1 Cartels 275
Cartel Profit Maximization 276
Instability of a Cartel 277

SOLVED PROBLEM Potential Profit from a Cellular Telephone Cartel 280

7.2 Tacit Collusion 280
Price Visibility 281

DECISION SNAPSHOT A Contract in the Market for Propane 282

Preannouncements 283
Precommitments 283
Price Leadership 284

SOLVED PROBLEM Price Leadership in the Market for Insulin 284

7.3 Four Types of Oligopolies 285
Cournot Oligopoly 285

DECISION SNAPSHOT South Africa’s Impala Platinum as a Cournot
Oligopolist 293

Chamberlin Oligopoly 294
Stackelberg Oligopoly 296
Bertrand Oligopoly 297
Comparing Oligopoly Models 298

SOLVED PROBLEM Coca-Cola Reacts to PepsiCo 299

7.4 Cartels and Oligopoly 300
Using Cartel Theory and Tacit Collusion for Managerial
Decision Making 301
Using Types of Oligopolies for Managerial Decision Making 301

Revisiting How Managers at Major Publishers Read the e-Writing on
the e-Wall 302

Summary: The Bottom Line 303

Key Terms and Concepts 303

Questions and Problems 304

MyLab Economics Auto-Graded Excel Projects 307

APPENDIX The Calculus of Oligopoly 309
A. Cournot Oligopoly 309
B. Stackelberg Oligopoly 315

Calculus Questions and Problems 316

MANAGERIAL
APPLICATION

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8 Game Theory and Oligopoly 318
Managers at Pfizer Welcome a Competitor in the Market for Lipitor 318

Introduction 318

8.1 Basic Game Theory and Games 319
Elements of a Game 320
A Sample Game 320
Nash Equilibrium 322
A Dilemma 323

DECISION SNAPSHOT An Advertising Game 324

Repeated Games 325

DECISION SNAPSHOT TragoCo and Boca-Cola Play a
Repeated Game 327

Dominated Strategies 330

SOLVED PROBLEM Games Between Two Smartphone
Producers 332

8.2 Advanced Games 334
Multiple Nash Equilibria 334
Mixed-Strategy Nash Equilibrium 337

SOLVED PROBLEM Custom’s Flower of the Day 343

8.3 Sequential Games 344
An Entry Game 344

DECISION SNAPSHOT Game Tree Between Disney and
Warner Brothers 347

Commitment and Credibility 348

SOLVED PROBLEM A Pharmaceutical Company Uses Game Theory to Make
an Offer 352

8.4 Game Theory 354
Using Basic Games for Managerial Decision Making 354
Using Advanced Games for Managerial Decision Making 356
Using Sequential Games for Managerial Decision Making 357

SOLVED PROBLEM Is a Threat Credible? 359

Revisiting How Managers at Pfizer Welcomed a Competitor in the Market for
Lipitor 360

Summary: The Bottom Line 361

Key Terms and Concepts 362

Questions and Problems 362

MyLab Economics Auto-Graded Excel Projects 368

MANAGERIAL
APPLICATION

Contents  xv

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xvi  Contents

9 A Manager’s Guide to Antitrust Policy 371
The Managers of Sea Star Line Walk the Plank 371

Introduction 372

9.1 Overview of U.S. Antitrust Policy 372
The Monopoly Problem 372
The Sherman Act, 1890 374
The Clayton Act, 1914 374
The Federal Trade Commission Act, 1914 375
Sanctions for Antitrust Violations 375
Recent Antitrust Cases 377

SOLVED PROBLEM A Perfectly Competitive Market Versus a Monopoly
Market 378

9.2 The Sherman Act 379
Sherman Act Section 1: Restraint of Trade 379
Sherman Act Section 2: Monopolization and Attempt to Monopolize 383

SOLVED PROBLEM Going, Going, Gone: Price Fixing in the Market
for Fine Art 387

9.3 The Clayton Act 388
Clayton Act Section 2: Price Discrimination 388
Clayton Act Section 3: Conditional Sales 388
Clayton Act Section 7: Mergers 391

SOLVED PROBLEM The Business Practices Covered in the Clayton Act 392

9.4 U.S. Merger Policy 392
Economic Effects of Horizontal Mergers 393
Antitrust Merger Policy 394

DECISION SNAPSHOT The XM/Sirius Satellite Radio Merger 396

SOLVED PROBLEM Mergers in the Office-Supply Market 397

9.5 International Competition Laws 398
European Union Laws 398
Chinese Laws 400
Worldwide Competition Laws 401

SOLVED PROBLEM Gazprom Gas Prices Create Indigestion
in the European Union 402

9.6 Antitrust Policy 402
Using the Sherman Act and the Clayton Act 402
Using International Competition Laws 403
Antitrust Advice for Managers 403

Revisiting How the Managers of Sea Star Line Walked the Plank 404

Summary: The Bottom Line 405

Key Terms and Concepts 405

Questions and Problems 406

MyLab Economics Auto-Graded Excel Projects 410

CASE STUDY Student Athletes and the NCAA 412

MANAGERIAL
APPLICATION

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10 Advanced Pricing Decisions 414
Managers at the Turtle Bay Resort Think Kama’aina Pricing Is Par for
the Course 414

Introduction 414

10.1 Price Discrimination 416
First-Degree Price Discrimination 416
Second-Degree Price Discrimination 418
Third-Degree Price Discrimination 419

DECISION SNAPSHOT American Airlines Identifies a Customer Type 425

SOLVED PROBLEM Price Discrimination at Warner Brothers: That’s All,
Folks! 426

10.2 Peak-Load Pricing 427
Long-Run Capacity Decision 428
Short-Run Pricing and Quantity Decisions 429

DECISION SNAPSHOT Peak-Load Pricing by the Minneapolis–St. Paul
Metropolitan Airport 432

SOLVED PROBLEM Peak-Load Pricing 433

10.3 Nonlinear Pricing 434
Two-Part Pricing 434
All-or-Nothing Offers 440

DECISION SNAPSHOT Nonlinear Pricing at the 55 Bar 443

Commodity Bundling 443

SOLVED PROBLEM Movie Magic 446

10.4 Using Advanced Pricing Decisions 447
Managerial Use of Price Discrimination 447
Managerial Use of Peak-Load Pricing 448
Managerial Use of Nonlinear Pricing 449

Revisiting How the Managers at Turtle Bay Resort Came to Think Kama’aina Pricing Is
Par for the Course 450

Summary: The Bottom Line 451

Key Terms and Concepts 451

Questions and Problems 451

MyLab Economics Auto-Graded Excel Projects 456

APPENDIX The Calculus of Advanced Pricing Decisions 458
A. Third-Degree Price Discrimination 458
B. Two-Part Pricing 459

Calculus Questions and Problems 463

MANAGERIAL
APPLICATION

PART 3
MANAGERIAL DECISIONS

Contents  xvii

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xviii  Contents

12 Decisions About Production, Products, and Location 499
Managers at Freeport-McMoRan Dig Deep to Make a Decision 499

Introduction 500

12.1 Joint Production 500
Fixed Proportions 501
Variable Proportions 502

SOLVED PROBLEM A Refinery Responds to an Increase in the Profit
from Gasoline 506

11 Decisions About Vertical Integration and Distribution 465
Why Would Walgreens Boots Alliance Purchase Wholesaler AmerisourceBergen? 465

Introduction 465

11.1 The Basics of Vertical Integration 467
Markets Versus Vertical Integration 467
Types of Vertical Integration 468
Transfer Prices and Taxes 469

SOLVED PROBLEM Vertical Integration 470

11.2 The Economics of Vertical Integration 471
Synergies 471
Costs of Using a Market: Transaction Costs, the Holdup Problem,
and Technological Interdependencies 471

DECISION SNAPSHOT PepsiCo Reduces Transaction Costs 473

Costs of Using Vertical Integration 476

DECISION SNAPSHOT Pilgrim’s Pride and the Limits of Vertical Integration 477

SOLVED PROBLEM IBM Avoids a Holdup Problem 478

11.3 Vertical Integration and Market Structure 478
Vertical Integration with Competitive Distributors 479
Vertical Integration with a Monopoly Distributor 483

SOLVED PROBLEM Price and Quantity with Competitive Distributors
and a Monopoly Distributor 488

11.4 Vertical Integration and Distribution 489
Using the Economics of Vertical Integration for Managerial Decision Making 489
Using Vertical Integration and Market Structure for Managerial
Decision Making Within a Firm 490

Revisiting Why Walgreens Boots Alliance Would Purchase Wholesaler
AmerisourceBergen 490

Summary: The Bottom Line 491

Key Terms and Concepts 492

Questions and Problems 492

MyLab Economics Auto-Graded Excel Projects 496

MANAGERIAL
APPLICATION

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13 Marketing Decisions: Advertising and Promotion 541
Heads Up for Advertising Decisions at Riddell 541

Introduction 541

13.1 Profit-Maximizing Advertising by a Firm 542
Advertising and Profit Maximization 543
Choosing Advertising Media 547

Contents  xix

12.2 The Multi-Plant Firm 506
Marginal Cost for a Multi-Plant Firm 507
Profit Maximization for a Multi-Plant Firm 508

SOLVED PROBLEM Can Producing Too Many Cookies Hurt Your Firm’s
Profit? 510

12.3 Location Decisions 511
Changes in Costs from Adding Plants 511
The Effect of Transportation Costs on Location Decisions 513

DECISION SNAPSHOT Quaker Oats’ Location Decision 514

DECISION SNAPSHOT Walgreens and CVS Compete for Your Drug
Prescription 515

The Effect of Geographic Variation in Input Prices on Location Decisions 516

SOLVED PROBLEM A Department Store Pays for Transportation 518

12.4 Decisions About Product Quality 518
SOLVED PROBLEM Flower Quality 520

12.5 Optimal Inventories 521
Economic Order Quantity Model 521
General Optimal Inventory Decisions 523

SOLVED PROBLEM How a Decrease in Demand Affects the Economic Order
Quantity 524

12.6 Production, Products, and Location 525
Joint Production of an Input 525
Transportation Costs, Plant Size, and Location 526

Revisiting How Managers at Freeport-McMoRan Had to Dig Deep to Make
a Decision 528

Summary: The Bottom Line 528

Key Terms and Concepts 529

Questions and Problems 529

MyLab Economics Auto-Graded Excel Projects 534

APPENDIX The Calculus of Multi-Plant Profit-Maximization and Inventory
Decisions 536
A. Production Decisions at a Multi-Plant Firm 536
B. Economic Order Quantity Inventory Model 537

Calculus Questions and Problems 539

MANAGERIAL
APPLICATION

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xx  Contents

DECISION SNAPSHOT PepsiCo Allocates Its Advertising Dollars 548

SOLVED PROBLEM Marginal Benefit from Automobile
Advertising 549

13.2 Optimal Advertising by an Industry 550
Industry-Wide Advertising as a Public Good 550
Challenges of Industry-Wide Advertising 551

SOLVED PROBLEM The National Football League’s Advertising
Problem 554

13.3 False Advertising 554
When Can False Advertising Be Successful? 555
What Are the Penalties for False Advertising? 557

SOLVED PROBLEM Advertising for Skechers Shape-Ups Gets
the Boot 558

13.4 Resale Price Maintenance and Product Promotion 558
The Effect of Resale Price Maintenance 559
Profit Maximization with Resale Price Maintenance 560
Resale Price Maintenance and Antitrust Policy 561

DECISION SNAPSHOT Amazon.com Markets Its Kindle 562

SOLVED PROBLEM Profit-Maximizing Resale Price Maintenance for Designer
Shoes 563

13.5 International Marketing: Entry and Corruption Laws 564
Entering a Foreign Market 564
U.S. Anticorruption Law: The Foreign Corrupt Practices Act 566

DECISION SNAPSHOT JPMorgan “Sons and Daughters” Program 569

U.K. Bribery Act 569

SOLVED PROBLEM Legal or Illegal? 570

13.6 Marketing and Promotional Decisions 571
Industry-Wide Advertising 571
Resale Price Maintenance 571
Foreign Marketing Issues 573

Revisiting Heads Up for Advertising Decisions at Riddell 573

Summary: The Bottom Line 575

Key Terms and Concepts 576

Questions and Problems 576

MyLab Economics Auto-Graded Excel Projects 580

APPENDIX The Calculus of Advertising 582
A. Profit-Maximizing Amount of Advertising with a Single Advertising
Medium 582
B. Profit-Maximizing Amount of Advertising with Two or More Advertising
Media 584

Calculus Questions and Problems 585

MANAGERIAL
APPLICATION

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Contents  xxi

14 Business Decisions Under Uncertainty 587
Embezzlement Makes Managers at a Nonprofit See Red 587

Introduction 587

14.1 Basics of Probability 588
Relative Frequency 588

DECISION SNAPSHOT Probability of Success at a New Branch 589

Expected Value 590
Subjective Probability 591

SOLVED PROBLEM Expected Customers at a Car Dealership 592

14.2 Profit Maximization with Random Demand and Random
Cost 593
Expected Profit Maximization with Random Demand 593
Expected Profit Maximization with Random Cost 596
Expected Profit Maximization with Random Demand
and Random Cost 598

SOLVED PROBLEM Profit Maximization for a Vineyard 599

14.3 Optimal Inventories with Random Demand 600
The Inventory Problem 600
Profit-Maximizing Inventory 601

SOLVED PROBLEM Profit-Maximizing Inventory of Pastry Rings 603

14.4 Minimizing the Cost of Random Adverse Events 604
Minimizing the Cost of Undesirable Outcomes 604
Expected Marginal Benefit from Avoiding Undesirable Outcomes 604
Marginal Cost of Avoiding Undesirable Outcomes 606
Optimal Accident Avoidance 607

DECISION SNAPSHOT Patent Search at a Pharmaceutical Firm 608

The Role of Marginal Analysis in Minimizing the Cost of Accidents 611

SOLVED PROBLEM Safety at an Energy Firm 611

14.5 The Business Decision to Settle Litigation 612
Basic Economic Model of Settlements: Parties with Similar Assessments 612

DECISION SNAPSHOT Actavis Versus Solvay Pharmaceuticals 614

Parties with Different Assessments 615

SOLVED PROBLEM To Settle or Not To Settle, That Is the Question 616

14.6 Risk Aversion 616
Insurance 617
Risk Aversion and Diversification 617
Risk Aversion and Litigation 618

SOLVED PROBLEM Merck Takes Advantage of Risk Aversion 618

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xxii  Contents

15 Managerial Decisions About Information 635
Auctions Float the Navy’s Boat 635

Introduction 635

15.1 Intellectual Property 636
Patents and Trade Secrets 637
Copyrights 639
Trademarks 640

SOLVED PROBLEM Patent Infringement 641

15.2 Value of Forecasts 642
Random Demand Model 642
Factors Affecting the Value of Forecasts 644

SOLVED PROBLEM Value of a Forecast 648

15.3 Auctions 650
Types of Auctions 650
Bidding Strategy 651

DECISION SNAPSHOT Strategy in an English Auction of a U.S. Silver Dollar 655

Expected Revenue 656

SOLVED PROBLEM The San Francisco Giants Strike Out 658

15.4 Asymmetric Information 658
Adverse Selection 659
Moral Hazard 663

SOLVED PROBLEM Adverse Selection and Insurance Companies 665

15.5 Decisions about Information 666
Value of Forecasts for Different Time Periods 666
Managing the Winner’s Curse When Selling a Product 667
Incentives and the Principal–Agent Problem 667

Revisiting How Auctions Float the Navy’s Boat 669

Summary: The Bottom Line 669

Key Terms and Concepts 670

Questions and Problems 671

MyLab Economics Auto-Graded Excel Projects 674

MANAGERIAL
APPLICATION

14.7 Making Business Decisions Under Uncertainty 619
Maximizing Profit with Random Demand and Random Cost 619
Optimal Inventories with Uncertainty About Demand 620
Making Business Decisions to Settle Litigation 622

Revisiting How Embezzlement Made Managers at a Nonprofit See Red 622

Summary: The Bottom Line 623

Key Terms and Concepts 624

Questions and Problems 624

MyLab Economics Auto-Graded Excel Projects 630

CASE STUDY Decision Making with Final Offer Arbitration 632

MANAGERIAL
APPLICATION

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16 Using Present Value to Make Multiperiod Managerial Decisions 677
Why Did Ziosk’s Managers Give Their Tablets to Chili’s for Free? 677

Introduction 677

16.1 Fundamentals of Present Value 678
Calculating Future Values 679
Calculating Present Values 680
Valuing a Stream of Future Payments 683
Future and Present Value Formulas 688

SOLVED PROBLEM Choosing a Loan Repayment Schedule 688

16.2 Evaluating Investment Options 689
Net Present Value and the Net Present Value Rule 689
Extensions to the Net Present Value Rule 692

DECISION SNAPSHOT Salvage Value at a Car Rental Firm 693

DECISION SNAPSHOT Depreciation Allowance: Should a Tax Firm Take It Now
or Later? 697

Selection of the Discount Rate 698
Risk and the Net Present Value Rule 698

SOLVED PROBLEM Investment Decision for an Electric Car Maker 700

16.3 Make-or-Buy Decisions 701
Make-or-Buy Basics 701
Make-or-Buy Net Present Value Calculations 703

SOLVED PROBLEM A Make-or-Buy Decision with Learning by Doing 704

16.4 Present Value and Net Present Value 704
Valuing Financial Assets 704
Using the Net Present Value Rule in the Real World 705
The Effect of Tax Shields on Net Present Value 706

Revisiting Why Ziosk’s Managers Gave Their Tablets to Chili’s for Free 707

Summary: The Bottom Line 708

Key Terms and Concepts 709

Questions and Problems 709

MyLab Economics Auto-Graded Excel Projects 712

CASE STUDY Analyzing Predatory Pricing as an Investment 715

Answer Key to Chapters 717

Answer Key to Calculus Appendices 756

Index 765

MANAGERIAL
APPLICATION

Contents  xxiii

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xxiv  Contents

Content on the Web

The following content is available on www.pearson.com/mylab/economics

Web Appendix: The Business Plan

A. Dehydrated Business Plan

B. Funding Business Plan
Executive Summary
Market and Customer Analysis
Company Description, Product Description, and Competitor Analysis
Marketing and Pricing Strategies

DECISION SNAPSHOT Gilead Sciences Needs a Price

Operations Plan
Development Plan
Team
Critical Risks
Offering
Financial Plan

Key Terms and Concepts

Questions and Problems

Web Chapter: Franchising Decisions

Quiznos Sandwiches Finds Its Stores Under Water

Introduction

WC.1 Franchising
Franchising Issues
Monopoly Benchmark
Input Purchase Requirements
Sales Revenue Royalties
Resale Price Controls and Sales Quotas

WORKED PROBLEM Subway Uses an Input Purchase Requirement

WC.2 Managerial Application: Franchising Theory
Managerial Use of Lump-Sum Franchise Fees
Managerial Use of Sales Revenue Royalties
Managerial Use of Resale Price Controls and Sales Quotas
Summary

Revisiting How Quiznos Sandwiches Found Its Stores Under Water

Summary: The Bottom Line

Key Terms and Concepts

Questions and Problems

A01_BLAI8235_01_SE_FM_ppi-xxxiv.indd 24 15/09/17 11:33 AM

PREFACE

Solving Teaching and Learning Challenges
Students who enroll in the managerial economics course are typically not economics
majors. They take the course with the goal of building skills that will help them be-
come better managers in a variety of business settings, including small and large
firms, nonprofit organizations, and public service. In teaching our classes, we often
skipped theoretical, abstract coverage in existing books—such as indifference curves,
isoquants, the Cobb–Douglas production function, the Rothschild Index, and the
Lerner Index—because these topics are not useful to students pursuing careers in
management. Based on our teaching experiences and feedback from many reviewers
and class testers, we have omitted this sort of theoretical, abstract coverage from our
book.

Our decision to omit these topics does not mean that we shortchange economic
theory. On the contrary, our book and a wide range of media assets show students
how economic theory and concepts—including opportunity cost, marginal analysis,
and profit maximization—can provide important insights into real-world manage-
rial challenges such as how to price a product, how many workers to hire, whether
to expand production, and how much to spend on advertising. Applications and
extensions of the core theory abound. Some of the topics include bundled pricing,
vertical integration, resale price maintenance, industry-wide advertising, settle-
ment of legal disputes, present value and investment decisions, auctions and opti-
mal bidding, and optimal patent search. We focus on how to think critically and
make decisions in real-world business situations—in other words, how to apply
economic theory.

MyLab Economics
MyLab Economics is an online homework, tutorial, and assessment program that
delivers technology-enhanced learning in tandem with printed textbooks and etexts.
It improves results by helping students quickly grasp concepts and by providing
educators with a robust set of tools to easily gauge and address the performance of
individuals and classrooms.

The Study Plan provides personalized recommendations for each student, based
on his or her ability to master the learning objectives in your course. This allows stu-
dents to focus their study time by pinpointing the precise areas they need to review,
and allowing them to use customized practice and learning aids—such as videos,
eText, tutorials, and more—to keep them on track.

First-in-class content is delivered digitally to help every student master criti-
cal course concepts. MyLab Economics includes Mini Sims, Auto-Graded Excel
Projects, and Digital Interactives to not only help students understand important
economic concepts, but also help them learn how to apply these concepts in a
variety of ways so they can see how they can use economics long after the last day
of class.

MyLab Economics allows for easy and flexible assignment creation, so
instructors can assign a variety of assignments tailored to meet their specific
course needs.

Visit www.pearson.com/mylab/economics for more information on Mini Sims,
Auto-Graded Excel Projects, Digital Interactives, our LMS integration options, and
course management options for any course of any size.

xxv

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Chapter Features
The following key features and media assets demonstrate how The Economics of
Managerial Decisions keeps the spotlight on the student as a future manager.

Real-world chapter openers and closers: Each chapter begins with a real-world
example that piques student interest and poses a managerial decision-making ques-
tion. We revisit this question and apply the chapter content to provide an answer at
the end. Because students pursue careers in various fields, the chapter openers pres-
ent challenges faced by a number of different types of organizations, including large
and small profit-seeking firms, government organizations, nongovernmental organi-
zations, and nonprofits.

xxvi  Preface

C
H

A
P

T
E

R

3 Measuring and Using Demand
Learning Objectives
After studying this chapter, you will be able to

3.1 Explain the basics of regression analysis.
3.2 Interpret the results from a regression.
3.3 Describe the limitations of regression analysis and how they affect its use by managers.
3.4 Discuss different elasticity measures and their use.
3.5 Use regression analysis and the different elasticity measures to make better managerial

decisions.

Managers at the Gates Foundation Decide to Subsidize
Antimalarial Drugs

The Bill and Melinda Gates Foundation (Gates Foundation) is the world’s largest philanthropic organization, with
a trust endowment of nearly $40 billion. The foundation
provides grants for education, medical research, and vac-
cinations around the world. As of 2015, the foundation
had made total grants of $37 billion. The goal of the Gates
Foundation is not maximizing profit. Instead, its goal is to
save lives and improve health in developing countries.

In 2010, the Global Fund to Fight AIDS, Tuberculosis
and Malaria presented proposals to the Gates Foundation
to subsidize antimalarial drugs in Kenya and other nations
of sub-Saharan Africa. Although the Gates Foundation pro-
vides nearly $4 billion in grants per year, there are more
than $4 billion worth of competing uses for its resources.
Consequently, before the managers accepted these
proposals, they needed to determine their expected
impact: How many people would these projects save
compared to alternative uses of the funds? The managers

realized that lives hinged on their decision, so they wanted
to be certain that they were getting the most value for
their money.

The proposed subsidy programs would lower
the price patients pay for the drugs. As you learned in
Chapter 2, according to the law of demand, a decrease in
the price of a product increases the quantity demanded.
Antimalarial drugs are no exception; if their price falls,
more patients will buy them. To make the proper decision
about the proposals, however, the foundation’s manag-
ers needed a more quantitative estimate: Precisely how
many additional patients would buy the drugs when their
prices were lower?

This chapter explains how to answer this and other
questions that require quantitative answers. At the end
of the chapter, you will learn how the Gates Foundation’s
managers could forecast the number of patients they
would help by subsidizing the drugs.

Sources: Karl Mathiesen, “What Is the Bill and Melinda Gates Foundation?” The Guardian. March 16, 2015;
Gavin Yamey, Marco Schaferhoff, and Dominic Montagu, “Piloting the Affordable Medicines Facility-Malaria:
What Will Success Look Like?” Bulletin of the World Health Organization, February 3, 2012, http://www.who
.int/bulletin/volumes/90/6/11-091199/en; Erinstar, “Availability of Subsidized Malaria Drugs in Kenya,” Social and
Behavioral Foundations of Primary Health Care Policy Advocacy, March 11, 2012, https://sbfphc.wordpress
.com/2012/03/11/availability-of-subsidized-malaria-drugs-in-kenya-18-2.

86

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Revisiting How Managers at the Gates Foundation Decided
to Subsidize Antimalarial Drugs

As noted at the beginning of the chapter, the manag-ers at the Bill and Melinda Gates Foundation want to
use their funds in the best way possible. Because wast-
ing their resources means that people could die unneces-
sarily, managers at the foundation want to fund the most
cost-effective programs. To achieve that goal, they must
determine the quantitative impact of the proposals pre-
sented to them.

In the case of the proposals to subsidize antimalarial
drugs in Kenya and other nations, the managers were unlikely
to have an estimated demand curve for the drugs in these
countries because of data limitations. Instead, they proba-
bly relied on estimates of the price elasticity of demand to
determine the increase in the quantity of drugs demanded.

The subsidy programs lowered the price of these
drugs between 29 percent and 78 percent (the fall in
price differed from nation to nation and from drug to
drug). Overall, the average decrease in price was roughly
50 percent. Because there are few substitutes, the demand
for pharmaceutical drugs is price inelastic. The price elas-
ticity of demand for pharmaceutical drugs for low-income
Danish consumers is estimated to be 0.31. Denmark and

Kenya differ in an important respect: Low-income consum-
ers in Kenya have much lower incomes than their coun-
terparts in Denmark. Consequently, the expenditure on
drugs in Kenya is a much larger fraction of consumers’
income, which means that the price elasticity of demand
for drugs in Kenya is larger than in Denmark. If the man-
agers at the Bill and Melinda Gates Foundation estimated
that the price elasticity of demand for drugs in Kenya
was about twice that in Denmark-—say, 0.60-—they
could then predict that lowering the price of the drugs
by 50 percent would increase the quantity demanded by
50 percent * 0.60 = 30 percent.

The Gates Foundation funded the proposals to sub-
sidize antimalarial drugs. The actual outcome was that
the quantity of the drugs demanded in the different na-
tions increased by 20 to 40 percent. The quantitative
estimate was right in line with what occurred. Using
the price elasticity of demand to estimate the impact of
the drug subsidy proposals allowed the managers at the
foundation to compare them to competing proposals
and to make decisions that saved the maximum number
of lives.

Summary: The Bottom Line
3.1 Regression: Estimating Demand
• Regression analysis is a statistical tool used to estimate

the relationships between two or more variables.
• Regression analysis assumes that the function to be es-

timated has a random element. The estimated coeffi-
cients minimize the sum of the squared residuals
between the actual values of the dependent variable
and the values predicted by the regression.

3.2 Interpreting the Results of Regression
Analysis

• The coefficients estimated by a regression change
when the data change. The statistical programs used in
regression analysis calculate confidence intervals for
each estimated coefficient. For the 95 percent confi-
dence interval, the value of the true coefficient falls
within the interval 95 percent of the time.

• The P-value indicates whether an estimated coefficient is
statistically significantly different from zero. If the P-
value is 5 percent (0.05) or less, then you can be 95 percent
confident that the true coefficient is not equal to zero.

• The R2 statistic, which measures the overall fit of the
regression, varies between 100 percent (the predicted
values capture all the variation in the actual dependent
variable) and 0 (the predicted values capture none of
the variation in the actual dependent variable).

3.3 Limitations of Regression Analysis
• Managers should examine regressions reported to

them to be certain that all the relevant variables are
included.

• Managers should determine whether a regression’s
functional form (curve or straight line) is the best fit for
the data.

3.4 Elasticity
• The price elasticity of demand measures how strongly

the quantity demanded responds to a change in the
price of a product. It equals the absolute value of the
percentage change in the quantity demanded divided
by the percentage change in the price.

Summary: The Bottom Line  123

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120  CHAPTER 3 Measuring and Using Demand

3.5 Regression Analysis and Elasticity
Learning Objective 3.5 Use regression analysis and the different elasticity
measures to make better managerial decisions.

Regression analysis and the different elasticity measures are important to managers
because they help quantify decision making. As a manager, you will face situations
in which you need to know the exact amount of a change in the price of an input,
the precise change in your cost when you change your production, or the actual
decrease in quantity demanded when you raise the price of your product.
Regression analysis and the application of the different elasticity measures can help
you answer these and many other important questions.

Using Regression Analysis
Using the results from regression analysis is an essential task in many managerial
positions. Analysts can use regression analysis for much more than estimating a
demand curve. For example, you can use it to estimate how your costs change when
production changes. We explain this important concept, called marginal cost, in
Chapter 4 and use it in all future chapters. Large companies with demand that
depends significantly on a specific influence often use regression analysis to forecast
changes in such factors as personal income (important to automobile manufacturers
such as General Motors and Honda) or new home sales (important to home improve-
ment stores such as Home Depot and Lowe’s).

The ultimate goal of regression analysis is to help you make better decisions. For
example, as a manager at the high-end steak restaurant chain, you can use an esti-
mated demand function to help you make both immediate decisions about the price
to set and long-term decisions about whether to open a new location. Suppose that
an analyst for your firm has used regression to determine that the nightly demand
for your chain’s steak dinners depends on the following factors:

1. The price of the dinners, measured as dollars per dinner
2. The average income of residents living within the city, measured as dollars per

person
3. The unemployment rate within the city, measured as the percentage unemploy-

ment rate
4. The population within 30 miles of the restaurant

Suppose that Table 3.4 includes the estimated coefficients and their standard er-
rors, t-statistics, and P-values.4 The R2 of the regression is 0.72, so the regression pre-
dicts the data reasonably well. In the table, the t-statistics for all five coefficients are
greater than 1.96, and accordingly all five P-values are less than 5 percent (0.05).
Therefore, you are confident that all the variables included in the regression affect
the demand for steak dinners. The coefficient for the price variable, −12.9, shows that
a $1 increase in the price of a dinner decreases the quantity demanded by – 12.9 * $1,
or 12.9 dinners per night. Similarly, the coefficient for the average income variable,
0.0073, shows that a $1,000 increase in average income increases the demand by

MANAGERIAL
APPLICATION

4 Often regression results are written with the standard errors in parentheses below the estimated coefficients:
Qd = 139.2 – 112.9 * PRICE2 + 10.0073 * INCOME2 – 110.0 * UNEMPLOYMENT2+ 10.0005 * POPULATION2
(11.9) (1.8) (0.0012) (3.2) (0.0002)

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Preface  xxvii

NEW! Mini Sims: The Managerial Applications are
accompanied by Mini Sims that are located in
MyLab Economics. Written by David Switzer of St.
Cloud State University and Casey DiRienzo of Elon
University, these Mini Sims are designed to build
students’ critical-thinking and decision-making
skills through an engaging, active learning experi-
ence. Each Mini Sim requires students to make a
series of decisions based on a business scenario,
which helps them move from memorization to
understanding and application. These also allow
students to experience how different functional
areas of a business interact and how each employee’s
decisions affect the organization.

Managerial Applications: Fifteen of the sixteen
chapters include a major numbered section
devoted to managerial applications of the chapter
content.

3.5 Managerial Application: Regression Analysis and Elasticity  121

0.0073 * 1,000, or 7.3 dinners per night. The coefficient for the unemployment rate
variable, −10.0, shows that a one percentage point increase in the unemployment
rate decreases the demand by – 10.0 * 1, or 10 dinners per night. And the coefficient
for the population variable, 0.0005, shows that a 1,000-person increase in population
increases the demand by 0.0005 * 1,000, or 0.5 dinners per night.

Short-Run Decisions Using Regression Analysis
Although a more detailed explanation of how managers determine price must wait until
Chapter 6, intuitively it is clear that demand must play a role. The estimated demand
function can help determine what price to charge in different cities because you can use
it to estimate the nightly quantity of dinners your customers will demand in those cities.
Suppose that one of the restaurants is located in a city of 900,000 people, in which aver-
age income is $66,300 and the unemployment rate is 5.9 percent. If you set a price of $60
per dinner, you can predict that the nightly demand for steak dinners equals

Qd = 139.2 – 112.9 * $602 + 10.0073 * $66,3002 – 110.0 * 5.92 + 10.0005 * 900,0002
or 240 dinners per night. You can now calculate consumer response to a change in
the price. For example, if you raise the price by $1, then the quantity of dinners de-
manded decreases by 12.9 per night, to approximately 227 dinners.

Long-Run Decisions Using Regression Analysis
You can also use the estimated demand function to forecast the demand for your
product. Such forecasts can help you make better decisions. For example, you and the
other executives at your steak chain might be deciding whether to open a restaurant
in a city of 750,000 residents, with average income of $60,000 and an unemployment
rate of 6.0 percent. Using the estimated demand function in Table 3.4 and a price of
$60 per dinner, you predict demand of about 118 meals per night. Suppose this quan-
tity of sales is too small to be profitable, but you expect rapid growth for the city: In
three years, you forecast the city’s population will rise to 950,000, average income will
increase to $70,000, and the unemployment rate will fall to 5.8 percent. Three years
from now, if you set a price of $60 per dinner, you forecast the demand will be 293
dinners per night. This quantity of dinners provides support for a plan to open a
restaurant in three years. You might start looking for a good location!

Other companies can use an estimated demand function to forecast their future
input needs. General Motors, for example, can use an estimated demand function
for their automobiles to forecast the quantity of steel it expects to need for next
year’s production. This information can help its managers make better decisions
about the contracts they will negotiate with their suppliers.

Table 3.4 Estimated Demand Function for Steak Dinners
The table shows the results of a regression of the demand for meals at an upscale steak restaurant, with the
estimated coefficients for the price, average income in the city in which the restaurant is located, unemployment
rate in the city, and population of the city.

Coefficient Standard Error t Stat P-value Lower 95% Upper 95%

Constant 139.2 11.9 11.7 0.00 117.3 163.1

Price of dinner −12.9 1.8 7.2 0.00 −9.4 −16.4

Average income 0.0073 0.0012 6.1 0.00 4.9 9.7

Unemployment rate −10.0 3.1 3.1 0.00 −3.9 −16.5

Population 0.0005 0.0002 2.5 0.02 0.0001 0.0009

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A01_BLAI8235_01_SE_FM_ppi-xxxiv.indd 27 15/09/17 11:33 AM

Solved Problems: This section-ending
feature guides students step by step in
solving a managerial problem, set in
the context of a situation managers may
encounter.

Decision Snapshots:  This
feature places readers in the
role of managers facing a
decision in a range of indus-
tries, including large and
small for-profit firms, public
service organizations, and
nonprofits. An answer is in-
cluded so students can con-
firm the decision they have
made.

Integrated examples: We consistently present economic concepts in the context of
business scenarios from a range of industries. For example:

• Chapter 4, “Production and Costs,” uses dinners at a restaurant to present the
concepts of production and costs.

• Chapter 13, “Marketing Decisions: Advertising and Promotion,” includes exam-
ples of advertising by a private company as well as by an entire industry.

• Chapter 14, “Business Decisions Under Uncertainty,” discusses the effect of
uncertainty on business decisions using examples including Starbucks and
Samsung.

xxviii  Preface

104  CHAPTER 3 Measuring and Using Demand

SOLVED
PROBLEM Which Regression to Use?

Your research department gives you the following two estimated demand curves. The
estimated demand curve to the left is log-linear, and the estimated demand curve to
the right is linear.

Price (dollars per dinner)

Quantity (dinners per day)

$75

$45

$50

1,100

D

1,000900800700600500

$55

$60

$65

$70

0

Price (dollars per dinner)

Quantity (dinners per day)

$75

$45

$50

1,1001,000900800700600500

$55

$60

$65

$70

0

D

a. Which regression do you think has the highest R2—the one with the log-linear speci-
fication or the one with the linear specification? Explain your answer.

b. Are the predicted quantities from one demand curve always closer to the actual
quantities than the predicted quantities from the other demand curve?

c. Which estimated demand curve would you use to make your decisions? Why?

Answer

a. The log-linear specification is closer to more of the data points than the linear speci-
fication. So the R2 of the log-linear specification exceeds that of the linear
specification.

b. Even though the predicted quantities from the log-linear specification are closer to
most of the actual quantities, there are a few predicted quantities that are closer
when using the linear specification. In particular, for prices of $67 and $64, the pre-
dicted quantities from the linear specification are closer to the actual quantities than
the predictions from the log-linear specification.

c. As a manager, you want to base your decisions on the most accurate information
possible. The log-linear specification has the higher R2, which means that it does a
better job of capturing the variation in the actual quantities than does the linear
specification. Consequently, you should use the log-linear specification as the basis
for your decisions.

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3.4 Elasticity  117

maximizes Pfizer ’s total revenue because that will maximize your royalty and
profit. Knowing the price elasticity of demand for your drug is important to
you. For example, if your drug is the only one to treat an illness, Pfizer has a
monopoly. In other words, it is the only seller in the market. You will learn in
Chapter 6 that because Pfizer has a monopoly, its profit-maximizing price for
the product will fall in the elastic range of the demand. Accepting this result,
you can see that when you license your drug to Pfizer, you need to push Pfizer
to cut the price from what it wants to set because the total revenue test shows
that when demand is elastic, a decrease in the price increases total revenue. If
Pfizer ’s total revenue increases, the royalty revenue your company receives will
get a boost as well. Of course, Pfizer will resist lowering the price, but because
you know that the demand for the drug is elastic, your biotech company will
keep pressuring Pfizer.

Your marketing department estimates that at the current price and quantity, your
firm’s product has a price elasticity of demand of 1.1. You run an advertising cam-
paign that changes the demand, so that at the current price and quantity the elas-
ticity falls to 0.8. In response to this change, would you raise the price, lower it, or
keep it the same? Explain your answer.

Answer
You should raise your price. Before the advertising campaign, the demand for
your product was elastic, so according to the total revenue test, a price hike
would lower your firm’s total revenue. After the campaign, the demand became
inelastic. You now will be able to increase your firm’s profit by raising the price.
Because the demand is inelastic, a price hike raises your firm’s total revenue. A
price hike also decreases the quantity demanded, so your firm produces less,
which decreases your costs. Raising revenue and lowering cost unambiguously
boost your firm’s profit!

DECISION
SNAPSHOT

Advertising and the Price Elasticity
of Demand

Income Elasticity and Cross-Price Elasticity of Demand
So far, you have learned about only one type of elasticity, the price elasticity of
demand. Although this is the most important elasticity, there are two others to
keep in mind: the income elasticity of demand and the cross-price elasticity of
demand. You are unlikely to use either of these two measures often, but under-
standing the different types of elasticity will help you avoid confusing them. In
addition, learning about income elasticity and cross-price elasticity will help rein-
force your understanding of the price elasticity of demand because all elasticities
have four points in common: (1) changes are expressed as percentages, (2) fractions
are used, (3) the factor driving the change is in the denominator, and (4) the factor
responding to the change is in the numerator. (The Appendix at the end of this
chapter presents a calculus treatment of these elasticities.)

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124  CHAPTER 3 Measuring and Using Demand

• If the price elasticity of demand exceeds 1.0, consum-
ers respond strongly to a change in price, and demand
is elastic. If the price elasticity of demand equals 1.0,
demand is unit elastic. If the price elasticity of demand
is less than 1.0, consumers respond weakly to a change
in price, and demand is inelastic.

• The more substitutes available for the product and the
larger the fraction of the consumer’s budget spent on
the product, the larger the price elasticity of demand.

• The income elasticity of demand equals the percentage
change in the quantity demanded divided by the per-
centage change in income. It is positive for normal
goods and negative for inferior goods.

• The cross-price elasticity of demand equals the per-
centage change in the quantity demanded of one good

divided by the percentage change in the price of a re-
lated good. It is positive for products that are substi-
tutes and negative for those that are complements.

3.5 Managerial Application: Regression
Analysis and Elasticity

• Regression analysis can estimate a firm’s demand
function and other important relationships. You can
use the estimated functions to make forecasts and pre-
dictions that improve your decisions.

• When there are not enough data to estimate a demand
function, you can use the price elasticity of demand,
the income elasticity of demand, and/or the cross-
price elasticity of demand to estimate or forecast the
effect of changes in market factors.

Key Terms and Concepts
Confidence interval

Critical value

Cross-price elasticity of demand

Elastic demand

Elasticity

Income elasticity of demand

Inelastic demand

Perfectly elastic demand

Perfectly inelastic demand

Price elasticity of demand

P-value

Regression analysis

R2 statistic

Significance level

t-statistic

Unit-elastic demand

Questions and Problems
All exercises are available on MyEconLab; solutions to even-numbered Questions and Problems appear in the back of
this book.

3.1 Regression: Estimating Demand
Learning Objective 3.1 Explain the basics of
regression analysis.

1.1 In the context of regression analysis, explain the
meaning of the terms dependent variable, indepen-
dent variable, explanatory variable, univariate equa-
tion, and multivariate equation.

1.2 Why does regression analysis presume the pres-
ence of a random error term?

1.3 Explain why minimizing the sum of the squared
residuals is a reasonable objective for regression
analysis.

3.2 Interpreting the Results of Regression
Analysis
Learning Objective 3.2 Interpret the results
from a regression.

2.1 Your marketing research department provides the
following estimated demand function for your

product: Qd = 500.6 – 11.4P + 0.5INCOME,
where P is the price of your product and
INCOME is average income.
a. Is your product a normal good or an inferior

good? Explain your answer.
b. The standard error for the price coefficient

is 2.0. What is its t-statistic? What can you
conclude about the coefficient’s statistical
significance?

c. The standard error for the income coeffi-
cient is 0.3. What is its t-statistic? What can
you conclude about the coefficient’s statisti-
cal significance?

2.2 What does the R2 statistic measure? Why is it
important?

2.3 The estimated coefficient for a variable in a
regression is 3.5, with a P-value of 0.12.
Given these two values, what conclusions
can you make about the estimated coefficient?

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Decision-Making Using Regression

Introduction
Upper-level managers frequently make important long-
run strategic decisions about acquisitions, mergers, plant
or store locations, pricing, financing, and marketing.
Indeed, a major focus of this book is to explain how man-
agers can use economic principles as a guide to making
these types of decisions. But even the best guidance can
fail without adequate information and data analysis.

Company analysts often use regression analysis to
help them provide quantitative information to manage-
rial decision makers. In this chapter, you learned how re-
gression analysis can help managers estimate demand
functions. But regression can be used to help managers
answer other questions, such as these: How many more
units of a product will we sell if our store stays open an
extra hour each day? Is San Diego a good location to open
a new store? How will consumers react if we change the
packaging of our product? In this case study, we explore
how regression analysis can help provide invaluable in-
formation about another important managerial issue,
whether to remodel the company’s stores and/or change
how the company prices its products.

Regression Example
Regression can help managers make the decisions faced
by companies that are debating whether to remodel their
stores and/or their operations. Companies such as restau-
rant chains continually struggle to retain their market
share by remaining fresh and relevant for consumers.
Most restaurant chains undertake constant innovation,
moving specials on and off their menus as well as tweak-
ing and refining their more permanent offerings. Occa-
sionally, however, upper-level managers decide that some
of their restaurants need renovation. Take, for example,
Olive Garden, a division of Darden with more than 800
restaurant locations. In 2013, the new president of Olive
Garden, Dave George, announced that Olive Garden
would remodel and modernize its interiors.

Suppose that you work in the research department
for a similar restaurant chain. Your chain has a new presi-
dent, and your president also is considering a new style
of remodeling for your restaurants. Remodeling is expen-
sive, so the new president asks your research team to
determine if the expense is justified by the projected
increased in the chain’s profit.

To obtain the information needed to make this type
of decision, a firm often remodels a few stores and then

130

CASE STUDY

1 This situation is similar to what Darden’s analysts faced in
2013 because Olive Garden had started remodeling its stores’ ex-
teriors and some of the interiors to present a different view of
Italy. That approach, however, was not what the incoming presi-
dent, Mr. George, envisioned. His goal was modernization, not
changing the geographic region the stores presented.

uses regression analysis to compare the profitability of the
remodeled stores to that of stores that are not remodeled.
Suppose, however, that your chain faces a more compli-
cated situation: Under the previous president, the chain
had already remodeled some locations but in a way that
differs from your new president’s vision.1 So you have
two types of restaurants—already remodeled and not
previously remodeled. The regression analysis needs to
consider this factor.

To use regression, your chain needs to remodel sev-
eral restaurants according to the new president’s vision.
Which restaurants are remodeled is unimportant because
your regression should be able to predict the profitability
regardless of location. After the remodeling, your group
must collect data over several months to measure the
profitability of all your restaurants. Ideally, you would
collect the economic profits of the restaurants. In practice,
however, their economic profit is impossible to measure,
so you will need to use their accounting profits as a proxy
for their economic profits. Your research group will use
these data as the dependent variable in the regression.

Your team of analysts needs to determine how the
new remodeling scheme affects profitability. But other
factors also affect profitability. A restaurant’s profit equals
its total revenue minus its total cost, so you and the other
analysts need to determine what variables affect total rev-
enue and total cost:

• Total revenue. The higher the demand for meals at
your restaurants, the greater the total revenue. So the
regression should include independent variables that
affect the demand for dining at your restaurants. For
example, your group might decide to include two in-
dependent variables that affect demand and thereby
total revenue: (1) the population of the county or lo-
cality in which the restaurant is located and (2) in-
come in that county or locality. When these variables
are included in the regression, the estimated coeffi-
cients for both these variables are expected to be pos-
itive—higher population and higher income both in-
crease demand and thereby increase the restaurant’s
total revenue and raise its profit.

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Preface  xxix

Assessment: End-of-chapter Ques-
tions and Problems are grouped by
the titles of the major numbered sec-
tions and the accompanying learn-
ing objectives so that instructors can
easily assign problems based on
those objectives, and students can
efficiently review material that they
find difficult. Students can complete
these problems and questions on
MyLab Economics, where they receive tutorial
help, instant feedback, and assistance with
incorrect responses.

NEW! MyLab Economics Auto-
Graded Excel Projects: Excel is a
software application that managers in all
industries and all functional areas, such as

marketing, sales, and finance, use to analyze data and
make decisions such as what to produce, how much to
produce, and how to price products. Mandie Weinandt
of the University of South Dakota created Excel projects
for each chapter based on the content of the chapter.
Kathryn Nantz of Fairfield University accuracy checked
the projects and solutions. The projects are accessible in
MyLab Economics, where instructors can seamlessly
integrate Excel content into their courses without having

Case studies: Four chapters end with case studies
that illustrate how managers used the topics in the
chapter to approach or solve a business challenge.

The case studies conclude with open-
ended questions about a similar situation
that instructors can use for class discus-
sion or assign as homework. Here are the
four cases:

• Chapter 3 Case Study: Decision
Making Using Regression

• Chapter 9 Case Study: Student
Athletes and the NCAA

• Chapter 14 Case Study: Decision
Making with Final Offer Arbitration

• Chapter 16 Case Study: Analyzing
Predatory Pricing as an Investment

3.3 Limitations of Regression Analysis
Learning Objective 3.3 Describe the limita-
tions of regression analysis and how they
affect its use by managers.

3.1 You are a manager at a company similar to KB
Home, one of the largest home builders in the
United States. You hired a consulting firm to es-
timate the demand for your homes. The consul-
tants’ report used regression analysis to esti-
mate the demand. They assumed that the
demand for your homes depended on the
mortgage interest rate and disposable income.
The R2 of the regression they report is 0.24
(24 percent). What suggestions do you have for
the consultants?

3.2 Your research analyst informs you that “I always
estimate log-linear regressions.” Do you think
the analyst’s procedure is correct? What would
you say to the analyst?

3.3 You are an executive manager for HatsforAll, a
major producer of hats. You are studying a pre-
liminary report submitted by a research firm
you hired. The report includes a regression that
estimates the demand for your hats. The re-
search firm used 20 years of data on sales of
your hats and included two independent vari-
ables: the annual average price of your hats and
the annual average winter temperature in your
marketing areas. (The theory behind the tem-
perature variable is that consumers are more
likely to buy hats when the temperature is
colder.) The estimated coefficient for the price
variable is −5.8, with a standard error of 0.8,
and the estimated coefficient for the tempera-
ture variable is −20.8, with a standard error of
15.6. Based on the results of survey cards in-
cluded with the hats, you are confident that
higher-income people buy more hats. You are
writing a memo to the research firm regarding
the report. What additional information will
you request from the research firm, and what
changes will you recommend it make?

3.4 Elasticity
Learning Objective 3.4 Discuss different
elasticity measures and their use.

4.1 The short-run price elasticity of demand for oil
is 0.3. If new discoveries of oil increase the quan-
tity of oil by 6 percent, what will be the resulting
change in the price of oil?

4.2 Complete the following table.

Elasticity

Percentage
Change in

Price

Percentage
Change in
Quantity

Demanded

a. __ 8 percent 12 percent
b. 1.4 6 percent _____
c. 0.6 6 percent _____
d. 1.2 _____ 6 percent
e. 0.4 _____ 6 percent

4.3 The slope of a linear demand curve is −$2 per unit.
a. What is the price elasticity of demand when

the price is $300 and the quantity is 100 units?
b. What is the price elasticity of demand when

the price is $250 and the quantity is 125 units?
c. What is the price elasticity of demand when

the price is $100 and the quantity is 200 units?
d. As the price falls (causing a downward

movement along the demand curve), how
does the price elasticity of demand change?

4.4 Your marketing research department estimates
that the demand function for your product is
equal to Qd = 2,000 – 20P. What is the price
elasticity of demand when P = $60?

4.5 Your marketing research department estimates
that the demand function for your product is
equal to Qd = 2,000 – 20P. What is the price
elasticity of demand when P = $40?

4.6 Your marketing research department estimates
that the demand function for your product is
equal to ln Qd = 7.5 – 2.0ln P. What is the price
elasticity of demand when P = $60?

4.7 As a brand manager for Honey Bunches of Oats
cereal, you propose lowering the price by
4 percent. What will you tell your supervisor
about what you expect will be the impact on
sales in the short run and in the long run?
Explain your answer.

4.8 You own a small business and want to increase
the total revenue you collect from sales of your
product.
a. If the demand for your product is inelastic,

what can you do to increase total revenue?
b. If the demand for your product is elastic,

what can you do to increase total revenue?
c. If the demand for your product is unit elas-

tic, what can you do to increase total
revenue?

Questions and Problems  125

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SUMMARY  131

• Total cost. The higher the total cost, the lower the
profit. So your team should include independent
variables in the regression that affect a restaurant’s
cost. For example, your group might settle upon two
variables: (1) the rent paid for the restaurant, which
will vary among locations, and (2) the legal mini-
mum wage employees receive, which will also vary
among locations. When these variables are included
in the regression, the estimated coefficients for both
of them are expected to be negative—a higher rent
and a higher minimum wage both increase the
restaurant’s cost and thereby reduce its profit.

In addition to the factors that affect total revenue and
total cost, the regression needs to take account of whether
the restaurant was remodeled according to the past presi-
dent’s scheme, remodeled according to the new presi-
dent’s ideas, or not remodeled at all. To do so, your team
needs to include indicator variables (colloquially called
“dummy variables”) as additional independent variables.
Indicator variables equal 1 when a condition is met and
equal 0 otherwise. For example, one indicator variable
should equal 1 if the restaurant had previously been re-
modeled and 0 if it had not been remodeled. Call this
variable OLDREMODEL. For the purposes of determin-
ing the profitability of the new style of remodeling, the
crucial indicator variable measures whether the location
has been remodeled according to the new scheme. This
variable equals 1 for restaurants that are newly remod-
eled and 0 for the other restaurants. Call this variable
NEWREMODEL. The estimated coefficient of each indica-
tor variable measures the effect of whatever condition is
being met.2 That means that the coefficient for the vari-
able NEWREMODEL is key because when the variable
equals 1, the restaurant has been newly remodeled along
the lines suggested by the new president. The change in
profit for a restaurant going from no remodeling at all to
the new remodeling equals the estimated coefficient of
NEWREMODEL—call it gn—multiplied by the value of

the variable when the location is newly remodeled, which
is 1, or gn * 1 = gn.3

There are other factors you and your group could in-
clude that affect the total revenue and total cost, but let’s
limit the discussion to what we have discussed. Using
these variables, to predict the profitability of a restaurant
in your chain, your team would estimate the regression as

PROFIT = a + 1b * POPULATION2 + 1c * INCOME2
– 1d * RENT2 – 1e * MINIMUMWAGE2
+ 1 f * OLDREMODEL2+1g * NEWREMODEL2

in which a, b, c, d, e, f, and g are the coefficients the regres-
sion will estimate.

Once your team has estimated the regression, you
can use what you have learned in Chapter 3 to judge the
adequacy of the regression: Are the estimated coefficients
statistically different from zero? Is the fit of the regression
high? Or do you and your group need to either add or re-
move some variables? Once you are satisfied with the re-
gression, you can use it to determine the profitability of
the proposed new remodeling. In particular, the estimated
gn coefficient measures the change in profit from the new
remodeling. If this estimated coefficient is positive and
significantly different from zero, you can present it to
your new president as an estimate of the profit from re-
modeling a previously unremodeled store according to
the new style and allow the president to use it when de-
ciding whether to proceed with the new remodeling.

Your Decisions
Regression analysis can be used in any industry, not just
the restaurant industry. Take, for example, the retail
industry. In November 2011, Ron Johnson was hired to be
the new CEO of JCPenney. Less than two months later,
Mr. Johnson announced the following sweeping changes:

1. JCPenney’s pricing had relied on heavy discounting
and extensive use of coupons; Mr. Johnson immedi-
ately changed the pricing policy to adopt “full-but-
fair prices” with no discounts or coupons.

2. JCPenney had offered a large selection of middle-of-
the-road store brands; Mr. Johnson discontinued the
store brands in favor of selling more “trendy,”
high-fashion brands.

2 For technical reasons, when a set of conditions taken together
equals the entire set of observations, it is not possible to use an
indicator variable for each type of condition; one type must not
have an indicator variable. For example, in the analysis discussed
above, you cannot use an indicator variable that equals 1 if the
location had been previously remodeled, another indicator vari-
able that equals 1 if the location is newly remodeled, and yet a
third indicator variable that equals 1 if the location has not been
remodeled. You cannot use all three of these indicator variables
because taken together these three conditions equal the entire set
of observations. Consequently, in the regression discussed in the
example, there is no indicator variable for the stores that have not
been remodeled.

3 More specifically, the NEWREMODEL indicator variable’s coeffi-
cient, gn, measures the profit from the new remodeling relative to
whichever condition has not been given an indicator variable. In
the example at hand, gn measures the restaurant’s change in profit
from being newly remodeled compared to not being remodeled
at all.

CHAPTER 3 CASE STUDY Decision-Making Using Regression  131

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128  CHAPTER 3 Measuring and Using Demand

3.1 Bret’s Accounting & Tax Services is a small but
locally well-known accounting firm in Sioux
City, IA, that completes taxes for individuals.
Every year firms like Bret’s decide how much
they will charge to complete and file an individ-
ual tax return. This price determines how many
tax returns firms complete each year.
Suppose that you are an office manager for a
firm like Bret’s Accounting & Tax Services and
you are trying to determine what your firm
should charge next year for tax returns. Use the
data provided to complete the following:
a. Graph the data using a scatter plot. Using the

Insert Trendline function in Excel, determine
whether you should use linear or log-linear
regression. (Place the graph beneath the data;
be sure to label both axes.)

b. Using Excel’s Regression Analysis function, run
a regression, and answer the following ques-
tions about your output. (Place your regression
results beneath the graph from part a.)

c. What is your estimated demand function?
(Round the estimated coefficients to two
decimal places.)

d. What is the R2? (Report this as a percentage;
round to two decimal places.)

e. Based on the R2, do you think this regression
can be used for analysis?

f. How many returns do you expect to be com-
pleted if the firm charges $85 per return?

g. What is the elasticity at this point on the
demand curve?

h. At this price, are you on the elastic, inelastic, or
unit-elastic portion of your demand curve?

i. Do you recommend an increase, a decrease, or
no change in the price with this information?

3.2 Hawaiian Shaved Ice, in Newton Grove, NC,
sells shaved ice and snow cone equipment and
supplies for individual and commercial use.
Suppose that you purchased a commercial-grade
machine and supplies from a company similar to
Hawaiian Shaved Ice to open a shaved ice stand
on a beach busy with tourists. Because this is a
new business, you’ve tried a number of prices
and run a few specials to try to attract customers.
As such, you have 20 days’ worth of data to ana-
lyze and help you set a more permanent price.

a. Graph the data provided using a scatter plot.
Using the Insert Trendline function in Excel,
determine whether you should use linear or
log-linear regression. (Place the graph
beneath the data; be sure to label both axes.)

b. Using Excel’s Regression Analysis function, run
a regression, and answer the following ques-
tions about your output. (Place your regression
results beneath the graph from part a.)

c. What is your estimated demand function?
d. Discuss the fit and significance of the

regression.

MyLab Economics Auto-Graded Excel Projects

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A01_BLAI8235_01_SE_FM_ppi-xxxiv.indd 29 15/09/17 11:33 AM

to manually grade spreadsheets. Students simply download a spreadsheet, work
live on a problem in Excel, and then upload that file back into MyLab Economics,
where they receive personalized, detailed feedback in the form of reports that pin-
point where they went wrong on any step of the problem.

Optional calculus appendices: The mathematics we use in the chapters is algebra
and geometry because this level is appropriate for managers. For those who want to
delve more deeply into the math, appendices showing calculus derivations of the
important results accompany 9 of the 16 chapters (Chapters 1, 3, 4, 5, 6, 7, 10, 12, and
13). Each appendix includes five homework problems that use calculus.

Developing Career Skills
Students who want to succeed in a rapidly changing job
market should be aware of their career options and how to
go about developing a variety of skills. As featured on the
previous pages, the text focuses on developing these skills
in various features:

• Real-world chapter openers and closers show how manag-
ers from a variety of business organizations apply eco-
nomic concepts to make decisions.

• Solved Problems and Decision Snapshots help students
build their analytical and critical-thinking skills.

• Mini Sims related to the Managerial Application at the end
of each chapter, except Chapter 1, help build students’
critical-thinking and decision-making skills through an
engaging, active learning experience. The screen on the
left shows one decision-point step in the Mini Sim that
accompanies Chapter 2, “Demand and Supply.”

• Auto-Graded Excel Projects at the end of each chapter help students build their
skill using Excel, a software application that they will need to use as managers
regardless of the industry or functional area in which they choose to work.

Table of Contents Overview
Chapters 1 through 6 are core chapters. An instructor can cover these chapters in or-
der and then proceed either to Chapters 7 and 8 or to Chapter 10. The chapters in
Part 3 (Chapters 10–16) can be covered in any order. For those who want to delve
more deeply into the mathematics, appendices showing calculus derivations of the
important results accompany 9 of the 16 chapters (Chapters 1, 3, 4, 5, 6, 7, 10, 12, and
13). An appendix on how to write a business plan and an additional chapter on fran-
chising decisions are located at www.pearson.com/mylab/economics.

Part 1. ECONOMIC FOUNDATIONS
Chapter 1: Managerial Economics and Decision Making
Chapter 2: Demand and Supply
Chapter 3: Measuring and Using Demand

Part 2. MARKET STRUCTURES AND MANAGERIAL DECISIONS
Chapter 4: Production and Costs
Chapter 5: Perfect Competition

xxx  Preface

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Preface  xxxi

Chapter 6: Monopoly and Monopolistic Competition
Chapter 7: Cartels and Oligopoly
Chapter 8: Game Theory and Oligopoly
Chapter 9: A Manager’s Guide to Antitrust Policy

Part 3. MANAGERIAL DECISIONS
Chapter 10: Advanced Pricing Decisions
Chapter 11: Decisions About Vertical Integration and Distribution
Chapter 12: Decisions About Production, Products, and Location
Chapter 13: Marketing Decisions: Advertising and Promotion
Chapter 14: Business Decisions Under Uncertainty
Chapter 15: Managerial Decisions About Information
Chapter 16: Using Present Value to Make Multiperiod Managerial Decisions

The following content is posted on www.pearson.com/mylab/economics:
Web Appendix: The Business Plan
Web Chapter: Franchising Decisions

Instructor Teaching Resources
The following supplements are available to instructors for download at www.
pearsonhighered.com.

The Instructor’s Manual was prepared by David Switzer of St. Cloud State
University and includes the following features:

• Solutions to all end-of-chapter and appendix questions and problems, which the
authors prepared and then revised based on an accuracy review by two other
professors.

• Chapter summaries
• Lists of learning objectives
• Chapter outlines, section summaries, and key term definitions
• Extra examples
• Teaching tips

The Test Bank was prepared by Casey DiRienzo of Elon University and includes
over 2,400 questions, with approximately 125 multiple-choice questions and 25 true/
false questions per chapter. Between 5 and 10 questions per chapter include a graph
and ask students to analyze that graph. The questions are organized by learning
objective, and each question has the following annotations:

• Topic
• Skill
• AACSB learning standard (Written and Oral Communication; Ethical

Understanding and Reasoning; Analytical Thinking; Information Technology;
Interpersonal Relations and Teamwork; Diverse and Multicultural Work; Reflective
Thinking; Application of Knowledge)

The PowerPoint Presentation was prepared by Julia Frankland of Malone
University and includes the following features:

• All the graphs, tables, and equations in each chapter
• Section summaries for all chapters
• Lecture notes

A01_BLAI8235_01_SE_FM_ppi-xxxiv.indd 31 15/09/17 11:33 AM

Eric Abrams, McKendree University
Basil Al Hashimi, Mesa Community

College
Jasmin Ansar, Mills College
Elena Antiniadou, Emory University
Sisay Asefa, Western Michigan University
Joseph Bailey, University of Maryland
Lila Balla, St. Louis University
Sourav Batabyal, Loyola University

Maryland
Jason Beck, Armstrong State University
Ariel Belasan, Southern Illinois University

at Edwardsville
Jeanne Boeh, Augsburg College
David Bouras, Lincoln University
Terry Brownschidle, Rider University
Donald Bumpass, Sam Houston State

University
Louis P. Cain, Northwestern University
Hugh Cassidy, Kansas State University
Hector Chade, Arizona State University
Kalyan Chakraborty, Emporia State

University
Keith W. Chauvin, University of Kansas
Jihui Chen, Illinois State University
Abdur Chowdhury, Marquette University
Jan Christopher, Delaware State

University
Kalock Chu, Loyola University at Chicago
Christopher Colburn, Old Dominion

University
Kristen Collett-Schmitt, University of

Notre Dame
Benjamin Compton, University of

Tennessee
Cristanna Cook, Husson University and

the University of Maine
Akash Dania, Alcorn State University
Tina Das, Elon University
Dennis Debrecht, Carroll University
Lisa Dickson, University of Maryland–

Baltimore County
Cassandra DiRienzo, Elon University
Carol Doe, Jacksonville University

Juan Du, Old Dominion University
Nazif Durmaz, University of

Texas–Victoria
Maxwell Eseonu, Virginia State

University
Xin Fang, Hawaii Pacific University
Jose Fernandez, University of Louisville
Darren Filson, Claremont McKenna

College
John Fizel, Pennsylvania State University
John Flanders, Central Methodist

University
Julia Frankland, Malone University
Yoshi Fukasawa, Midwestern State

University
Chris Gingrich, Eastern Mennonite

University
Tuncer Gocmen, Shepherd University
Rajeev Goel, Illinois State University
Natallia Gray, Southeast Missouri State

University
Anthony Greco, University of Louisiana

at Lafayette
Gauri S. Guha, Arkansas State University
John Hayfron, Western Washington

University
Martin D. Heintzelman, Clarkson

University
J. Scott Holladay, University of Tennessee
Adora Holstein, Robert Morris University
John Horowitz, Ball State University
Jack Hou, California State University

at Long Beach
Syed Jafri, Tarleton State University
Andres Jauregui, Columbus State

University
Russ Kashian, University of Wisconsin

at Whitewater
Mark Keightley, George Mason University
David Kelly, University of Miami
Abdullah Khan, Claf lin University
Felix Kwan, Maryville University
Jacob LaRiviere, University of Tennessee
Marc Law, University of Vermont

Acknowledgments
We are grateful for the guidance and recommendations of our many reviews, class
testers, and accuracy checkers. Their constructive feedback and support was indis-
pensable in the development of the chapters, media assets, and supplements.

xxxii  Acknowledgments

A01_BLAI8235_01_SE_FM_ppi-xxxiv.indd 32 15/09/17 11:33 AM

Acknowledgments  xxxiiiAcknowledgments  xxxiii

Robert Lawson, Southern Methodist
University

Mahdi Majbouri, Babson College
Michael Maloney, Clemson University
Russ McCullough, Ottawa University
Eric McDermott, University of Illinois
Hannah Mead, George Mason University
Douglas Meador, University of St. Francis

at Fort Wayne
Saul Mekies, University of Iowa/Kirkwood

Community College
Evelina Mengova, Governors State

University
Matt Metzgar, University of North

Carolina at Charlotte
Phillip Mixon, Troy University
Masoud Moallem, Rockford University
Francis Mummery, California State

University at Fullerton
Kathryn Nantz, Fairfield University
Michael Newsome, Marshall University
Dmitri Nizovtsev, Washburn University
Christian Nsiah, Baldwin Wallace

University
Tunay Oguz, Lenoir Rhyne University
Charles Parker, Wayne State College
Robert Pennington, University of Central

Florida
Paul Pieper, University of Illinois at Chicago
Chung Ping, University of North Florida
Harvey Poniachek, Rutgers University
John Reardon, Hamline University
Jean Ricot, Valencia Community College
Katy Rouse, Elon University
Stefan Ruediger, Arizona State University
Charles R. Sebuharara, Binghamton

University SUNY

Stephanie Shayne, Husson University
Dongsoo Shin, Santa Clara University
Steven Shwiff, Texas A&M University

at Commerce
Kusum Singh, LeMoyne Owen College
Ken Slaysman, York College of

Pennsylvania
John Spytek, Webster University
Denise Stanley, California State University

at Fullerton
Paul Stock, University of Mary Hardin–

Baylor University
Brock Stoddard, University of South

Dakota
David Switzer, St. Cloud State University
Michael Tasto, Southern New Hampshire

University
Bill Taylor, New Mexico Highlands

University
Kasaundra Tomlin, Oakland University
Suzanne Toney, Savannah State

University
Dosse Toulaboe, Fort Hays State

University
Julianne Treme, University of North

Carolina at Wilmington
Jennifer VanGilder, Ursinus College
Elizabeth Wark, Worcester State

University
Mandie Weinandt, University of South

Dakota
Keith Willet, Oklahoma State University
Mark Wilson, West Virginia University

Tech
Shishu Zhang, University of the Incarnate

Word
Ting Zhang, University of Baltimore

A Note of Thanks…
When we first started work on this book, we never realized how many people would
be so heavily involved, helping us, assisting us, and frequently prodding us along
the way. In truth, it is impossible to convey an adequate measure of thanks for their
input. But we shall try:

• Christina Masturzo, Senior Portfolio Manager with Pearson, was our guiding
light. We owe her a huge debt for her belief in our vision and for her tireless
work helping us achieve this vision. The team she assembled was first class, as
were her comments and inputs. Simply put, without her this book would not
exist.

A01_BLAI8235_01_SE_FM_ppi-xxxiv.indd 33 15/09/17 11:33 AM

• Lena Buonanno, Content Development Specialist with Pearson, helped keep us
on track and our noses to the grindstone. Lena was with us every step of the
way, literally from the first day to the last. We believe we would still be working
on the project were it not for her incredibly cheerful emails (most of which re-
minded us about missed deadlines).

• Karen Trost, Freelance Development Editor, together with Lena, helped convert
our writing into something that has at least a passing resemblance to English.
We cannot believe the number of hours Karen put in making grammatical im-
provements that sharpened and clarified the text. Because she will not have a
chance to edit this preface, all wee kan say is thanx.

• Carolyn Philips, Content Producer with Pearson, played a crucial role in helping
our thoughts progress from a manuscript to a finished product. We shudder to
think what the book would look like without her help.

• Courtney Paganelli, Editorial Assistant with Pearson, truly kept us organized—
at least as much as possible. We cannot imagine how Courtney was able to keep
all the details about all the aspects of the project straight and especially how she
was able to do so when working with us, disorganized as we are. We would doff
our hats to her if we could find them.

• Susan McNally, Production Manager with Cenveo, had what is probably the
most thankless task of all. Susan had to work with us when we had no idea how
to edit pages for publication. Her explanations about what could be (and what
could not be) done were invaluable. Time after time she patiently answered our
neophyte questions, making us eternally grateful and forever in her debt.

xxxiv  Acknowledgments

A01_BLAI8235_01_SE_FM_ppi-xxxiv.indd 34 15/09/17 11:33 AM

 1

Managerial Economics and
Decision Making
Learning Objectives
After studying this chapter, you will be able to:

1.1 Describe managerial economics and explain how it can help advance your career.
1.2 Define what a firm is and describe the legal structures of for-profit firms.
1.3 Compare opportunity cost and accounting cost and explain why using opportunity cost

leads to better decisions.
1.4 Explain how managers can use marginal analysis to make better decisions.

Introduction
Decision making is the most important task you will face as a manager. Companies
pay most managers quite well to make decisions. In some cases, the decisions are
small: Which custodial service should your company hire? On other occasions, the
decisions are large: Should your company build another plant to expand into
China? Your decisions will help determine the success of your company—and
your career.

1 CHAPTE
R

Managers at Sears Holdings Use Opportunity Cost to Make
Tough Decisions

Ask people in your parents’ generation about Sears, and their answers will be the same: Yes, they
shopped at Sears. Who didn’t? For decades, Sears was
the dominant retailer in the United States, selling homes
(and home insurance to protect them), blouses (and wash-
ing machines to clean them), and nails (and hammers to
drive them). Today, Sears no longer sells homes or home
insurance at all, and it sells far fewer blouses, washing
machines, nails, and hammers.

In 2005, Kmart purchased the original company and
now runs it as a subsidiary of the new parent company,
Sears Holdings. When Kmart purchased the company,
Sears had over 1,600 stores. Sales and profit at Sears
had been declining slowly over three decades but accel-
erated in more recent years as customers embraced

online shopping. As sales rapidly declined, Sears Hold-
ings’ top executives knew they had to close some stores
and faced two difficult decisions: how many stores to
close and which ones. Profitability was the key: The
executives needed to close unprofitable stores and
retain profitable ones. They consulted their accountants
about each store’s profit. Should they use the numbers
the accountants provided? Or should they use another
definition of profit?

This chapter introduces some of the fundamen-
tal concepts of managerial economics that will help you
answer these questions. At the end of this chapter, you
will see how Sears Holdings’ managers used the concepts
of opportunity cost and marginal analysis to make their
decisions.

Sources: Krystina Gustafson, “Sears to Accelerate Closings, Shutter 235 Stores,” CNBC, December 4, 2014
http://www.cnbc.com/2014/12/04/sears-to-accelerate-closings-shutter-235-stores.html; Phil Wahba, “Sears CEO
Lampert Explains Why He Closed 200 Stores,” Fortune, December 15, 2014; Suzanne Kapner, “Department Stores
Need to Cull Hundreds of Sites, Study Says,” Wall Street Journal, April 24, 2016; http://money.cnn.com/2017/01/05/
investing/sears-kmart-closing-stores/; https://blog.searsholdings.com/eddie-lampert/moving-forward/.

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2  CHAPTER 1 Managerial Economics and Decision Making

The quality of your decisions as a manager can help or hurt every functional
area within the firm. Unfortunately, there is no cut-and-dried formula that will
always lead to the correct decision, but basic economic principles can help you make
better decisions. Although these principles obviously apply to economic decisions
such as pricing, they apply equally well in virtually every business division, includ-
ing marketing, finance, and human resources.

We base many examples in this text on for-profit firms, and for simplicity, we fre-
quently refer to “firms.” But keep in mind that the lessons and economic principles
you will learn apply equally well to making decisions and achieving goals in all types
of organizations, ranging from nonprofit organizations to government agencies to
nongovernment organizations (NGOs). Once you understand the basic economic prin-
ciples, you will be well prepared for success as a manager of any type of organization.

To begin your study of the economic principles involved in managerial decision
making, Chapter 1 includes four sections:

• Section 1.1 defines managerial economics, describes economic models, and explains
why using them can help your career.

• Section 1.2 explains how economists define a firm and provides an overview of the
common legal categories of for-profit firms.

• Section 1.3 focuses on opportunity cost, which should guide the decision-making process
for managers of all types of organizations, and compares it to accounting cost.

• Section 1.4 defines and then applies the key decision-making tool of marginal analysis.

1.1 Managerial Economics and Your Career
Learning Objective 1.1 Describe managerial economics and explain how it
can help advance your career.

When you realized your program of study required a course in managerial econom-
ics, you may have asked yourself a question or two:

1. “Why do I need this class? I’ve already taken an economics course.”
2. “How will a course in managerial economics help my career?”

These are excellent questions. Let’s start with the first one: Your previous eco-
nomics courses helped you understand how the economy functions. In contrast, this
course explains how microeconomic concepts can help you manage a firm more
effectively. Managerial economics is the application of microeconomic principles
and tools to business problems faced by decision makers.

Whenever you must make a business decision on behalf of your firm, microeco-
nomic principles can assist you in making the best decision possible. That brings us
to the answer to the second question: Applying the microeconomic principles we
discuss in this text can help you make better decisions and, as a result, have a suc-
cessful career as a manager. Understanding how to use economics to make better
decisions is the driving goal of this class and text.

As we guide your study of managerial economics, we present and illustrate
microeconomic principles and tools using economic models. An economic model
is an abstract, simplified representation of the real world and real-world situa-
tions. In the real world, there are an infinite number of complications. Models strip
away those complications to focus on what is important. For example, suppose

Managerial economics
The application of
microeconomic principles
and tools to business
problems faced by
decision makers.

Economic model An
abstract, simplified
representation of the real
world and real-world
situations.

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1.2 Firms and Their Organizational Structure  3

that you want to use Google Maps to plot a quick driving tour of Napa Valley’s
highlights, including its many wineries. The satellite photos in the “Earth” view
reveal an immense amount of detail—including buildings, parked cars, pedestri-
ans, and traffic signals. You don’t need this level of detail to plan your trip. It is far
easier to use the “Map” view, which focuses on the roads. Economic models are
similar: They strip away the inessential minor details that clutter the issue and
focus directly on the key factors important to your managerial decisions—
and to your career.

Because they are abstract and simplified, economic models are not recipes that
tell you exactly how to make a business decision. You will often find that getting to
an optimal outcome is a repetitive trial-and-error process. Fortunately, following
economic principles and models can help you identify both the optimal solution and
the steps you need to take to reach it.

Before we examine some of the tools of economic analysis, let’s review basic
information about firms and their organization.

1.2 Firms and Their Organizational Structure
Learning Objective 1.2 Define what a firm is and describe the legal structures
of for-profit firms.

Understanding two concepts—the exact definition of a firm and the different legal
methods of organizing for-profit firms—is an essential first step in your study of
managerial economics.

Definition of a Firm
A firm is an organization that converts inputs (such as labor) into outputs (goods
and services) that it can sell or distribute. This definition applies to all firms. It is
as true for Intel, which purchases silicon to produce computer chips, as it is for
Frito-Lay, which purchases potatoes to produce a different kind of chip. It is easy
to see that the definition applies to for-profit firms, such as Intel and Frito-Lay.
But it also applies to nonprofits, such as the American Red Cross; to government
agencies, such as the U.S. Justice Department; and to NGOs, such as Amnesty
International. These groups all use various inputs to produce an output, such as
housing people made homeless because of a tornado, enforcing the nation’s anti-
trust laws, or increasing justice worldwide. Managers in all of these different
types of firms can use the principles of managerial economics to make better deci-
sions that further the goal of their organization.

The Legal Organization of Firms
Let’s focus for the moment on privately owned, profit-seeking firms. For-profit firms
include giants, such as Microsoft in the United States, Total S.A. in the European
Union, and Industrial Bank Company, Limited, in China, as well as small, local
firms, such as the thousands of local laundries and restaurants that we find in all the
cities of the world. For-profit firms are pervasive in the economies of virtually all
nations. These firms come in a vast array of sizes and produce a nearly infinite vari-
ety of goods and services, so their owners use different methods to legally organize
them. Let’s review the four major categories of legal organization of firms used in
the United States: sole proprietorships, partnerships, limited liability companies,
and corporations.

Firm An organization that
converts inputs (such as
labor) into outputs (goods
and services) that it can
sell or distribute.

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4  CHAPTER 1 Managerial Economics and Decision Making

Sole Proprietorship
The simplest form of business organization is a sole proprietorship, a firm owned by
one person. Examples of sole proprietorships include an owner–operator of a taxi, a
farmer, a solo-practitioner lawyer, and an owner of a small laundry or restaurant. In
some of these firms, the owner has minimal supervisory duties: The owner–opera-
tors of taxis must organize their own labor services, but they have few, if any, super-
visory duties. In other firms, the owners have more responsibilities: Owners of small
retail stores have employees to supervise, which complicates their business opera-
tions and requires increased decision making.

As a form of business organization, a sole proprietorship offers several advan-
tages. First, legal formation is easy, since the owner does not need to prepare any
paperwork. Another advantage is that the government taxes a sole proprietorship’s
profits only once. The owner of a sole proprietorship adds all of the firm’s profit to
any other income and then pays personal income tax on the sum of the profit plus
other income. Of course, a sole proprietorship also has disadvantages. When the
owner dies, the sole proprietorship also dies, which makes it difficult for sole pro-
prietorships to raise large sums of money to invest in the business. Another disad-
vantage is that the owner of a sole proprietorship faces unlimited liability. If the
sole proprietorship fails, the owner can be liable for all of the company’s debts, such
as payments to creditors or back rent on office space.

Partnership
Partnerships are businesses owned by two or more people. Although the laws that govern
partnership formation vary from state to state, partners must register their partnership
with the state, and at the very least, they must carefully spell out each partner’s
responsibilities and rights in the registration papers. Types of partnerships differ
depending on the rights and responsibilities accorded to the partners,1 but most part-
nerships share a few characteristics. Let’s start with the advantages of partnerships:

1. The government taxes a partnership’s profits only once. Each of the owners
reports his or her share of the profit, along with any other income, on his or her
personal income tax form and pays the required tax. In this sense, partnerships
are like proprietorships.

2. Many partnerships, such as law firms and accounting firms, motivate their
employees by offering them the chance to become a partner, an opportunity that
can often be lucrative.

Most partnerships, however, have a significant disadvantage: Partners face unlimited
joint and individual liability for the decisions made by all of the partners and for all
the debts of the partnership. If a partnership goes bankrupt, each partner is person-
ally responsible for all of the partnership’s debts. Exceptions to the rule of unlimited
liability are limited partnerships and limited liability partnerships. The latter form of
organization is available only to a few types of professional services.

Limited Liability Company
A relatively new form of business organization, the limited liability company (LLC), is
a firm owned by one or more members who have limited liability for its debt. In
three respects, LLCs are similar to partnerships:

1 For instance, general partnerships typically divide management rights and profit shares equally among part-
ners. In contrast, limited partnerships have two types of partners: general partners, who run the company and
have unlimited liability, and limited partners, who have limited management rights and enjoy limited liability.

M01_BLAI8235_01_SE_C01_pp001-032.indd 4 23/08/17 9:48 AM

1.2 Firms and Their Organizational Structure  5

1. The LLC members may create an operating agreement that carefully describes
each member’s rights and responsibilities. If they do not, the state laws from the
state in which the LLC is formed will govern many of these issues.

2. The LLC members must file paperwork with the state in which the LLC is
formed; regulations determining what information must be filed differ from one
state to the next.

3. All of the LLC’s profit is allocated to the members, who pay personal income tax
on their share of the profit.

As suggested by their name, however, LLCs differ in one important way from part-
nerships (and sole proprietorships): The members of an LLC have limited liability
for the company’s debt. If the LLC goes bankrupt, its members are not personally
liable for the company’s debt.

Corporation
A more complicated form of business organization is the corporation, a firm owned
by one or more shareholders. Professional managers often run corporations on a
day-to-day basis. In the United States, a board of directors usually serves as the
interface between the shareholders and the management team. The shareholders,
who generally have one vote for each share owned, elect the board members. Typi-
cally, the top executives of the company are board members, but in the United States,
in aggregate approximately two-thirds of board members are independent, with no
direct connection to the management of the firm. Board members are responsible for
ensuring that the executives run the company for the benefit of the shareholders and
must approve significant actions of the firm, such as purchasing another large com-
pany or entering into a major new product line. The board also decides the amounts
of any dividends. A dividend is a dollar amount per share the company pays to the
shareholders, who are the owners of the firm. For example, the pharmaceutical firm
Pfizer Inc. might pay an annual dividend of $1.08 per share.

Compared to the other organizational forms, corporations have more legal
requirements, such as setting up a double-entry bookkeeping system to record busi-
ness transactions and filing an annual report to the state in which they are incorpo-
rated. One important disadvantage is that the government taxes a corporation’s
profits twice, once at the corporate level via a corporate income tax and again at the
personal level when the owners pay their personal income taxes on any dividends
they receive and on any gain they make when they sell shares. Corporations, how-
ever, have at least two major advantages:

1. Because a corporation has perpetual life, its managers can raise funds more eas-
ily. Lenders know that a corporation with many shareholders will survive the
death of any one shareholder, so they are more willing to lend money to corpo-
rations than to sole proprietorships or partnerships.

2. Shareholders have limited liability for the debts and actions of their company.
Consequently, if a corporation fails, owing millions or perhaps even billions of
dollars, the shareholders are not responsible for repaying any of the debt.

Table 1.1 summarizes the key characteristics of the four forms of legal
organization.

Now that you understand the definition of a firm and the different ways of orga-
nizing for-profit firms, it is time to focus on the goal of many business owners: profit.
This discussion leads naturally to an examination of your first economic tool, oppor-
tunity cost, and how it differs from accounting cost.

M01_BLAI8235_01_SE_C01_pp001-032.indd 5 23/08/17 9:48 AM

6  CHAPTER 1 Managerial Economics and Decision Making

1.3 Profit, Accounting Cost, and
Opportunity Cost

Learning Objective 1.3 Compare opportunity cost and accounting cost and
explain why using opportunity cost leads to better decisions.

A key factor motivating owners and managers of profit-seeking firms is the firm’s
profit, the difference between total revenue and total cost. In order to better under-
stand profit, you need to understand total revenue and total cost in more detail.
Defining total revenue is easy: It is the firm’s total receipts from the sale of its goods
and services. Identifying total cost is more difficult because cost means different
things to different people. Let’s begin by discussing the role played by profit and
then turn to total revenue and total cost.

Goal: Profit Maximization
Although many goals might motivate the owners of profit-seeking firms, gener-
ally the prime motivator is profit maximization. Owners who put profits first
have the most income to spend on the goods and services they want to consume.

Total revenue The firm’s
total receipts from the sale
of its goods and services.

Profit The difference
between total revenue and
total cost.

Table 1.1 Legal Organization of Firms

Type of Firm Characteristics Advantages Disadvantages Examples

Sole
proprietorship

• A firm owned by
one person

• Easy to organize
• Profits taxed only

once

• Exists only for the
life of the owner

• Unlimited liability

• Taxi owner–
operator

• Solo-practitioner
lawyer

• Restaurant owner

Partnership • A firm owned
by two or more
people

• Profits taxed only
once

• Employees
motivated to
become partner

• Registration
required

• Unlimited liability
(except for limited
partnerships and
limited liability
partnerships)

• Law firm
• Medical practice

Limited liability
company

• A firm owned
by one or more
members

• Limited liability
• Profits taxed only

once

• Registration
required

• Edgeworth
Management, LLC

• Mack Construction,
LLC

Corporation • A firm owned
by one or more
shareholders

• Typically run on a
day-to-day basis
by professional
managers and
overseen by a
board of directors

• Perpetual life
• Limited liability

• Registration
required

• Additional legal
requirements

• Profits taxed twice
(corporate income
tax on profits and
personal income
tax on shareholder
income)

• Pfizer
• Microsoft
• Ford Motor

Company

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1.3 Profit, Accounting Cost, and Opportunity Cost  7

If an owner puts other considerations, such as staff maximization, revenue maxi-
mization, or even the appearance of the employees, ahead of profits when mak-
ing business decisions, the firm’s profit will decrease, along with the owner ’s
personal consumption of goods and services. In addition, competition from profit-
maximizing firms will drive firms that do not maximize profit out of business.
Most empirical evidence suggests that profit maximization is the goal pursued
by owners, so assume that all owners of for-profit firms seek to maximize their
firms’ profits.

The owners of a profit-seeking firm may have a primary goal of profit, but the
professional managers who run that firm on a day-to-day basis may have different
goals. Managers are interested in enhancing their own well-being, an objective not
always consistent with the goals of the owners, so some conflict of interest can easily
arise when managers are not owners of the firm. Managers who believe that their
prestige depends on the number of people reporting to them may hire too many staff
members. Others may put family concerns ahead of business concerns and hire their
own children. These actions could decrease profits. Owners often respond to this
challenge by making it costly for managers not to maximize profit. For example,
owners can use executive stock options, bonuses, and raises as incentives for the
managers to put the firm first and maximize its profit. Chapter 15 examines the ways
in which owners can motivate managers to maximize profit in more detail. Because
the evidence suggests that managers as well as owners are rewarded for profit maxi-
mization, assume that successful managers also make decisions that maximize their
firms’ profits.

In general, because firms have a stream of profits and losses over time, owners
and managers strive to maximize the value of the stream of profits. Often, however,
the decisions that maximize profit in a given year are the same ones that maximize
profit over time. For this reason, and to simplify the analysis, most of the discussion
throughout the text focuses on maximizing profit for a shorter time period. You can
then apply the lessons you learn from this shorter-term analysis to the more complex
situation of maximizing profit over time after you study Chapter 16, which focuses
on multiperiod decision making.

Profit does not motivate managers of nonprofits, government agencies, or
NGOs. Instead, achievement of the organization’s goal serves as a motivator. These
managers, however, still need to use their resources as effectively as possible. Oppor-
tunity cost remains crucial for managers in these sectors because it will show them
the true cost of their resources and help them efficiently allocate these resources.
Although the examples in this section use for-profit firms, the lessons about cost are
important for managers of any type of firm.

Total Revenue
Total revenue generally means the same thing to accountants, economists, and man-
agers: the firm’s total receipts from the sale of its goods and services. At its most
basic level, a firm’s total revenue (TR) is the price of the good or service (P) multi-
plied by the quantity sold (Q):

TR = P * Q

For example, Gannett Company publishes USA Today, a newspaper that covers
nationwide news, and sells it nationally. If Rogermark, a company like Gannett, sells
1.8 million issues of its newspaper, America Today, per day to its distributors at a
wholesale price of 40¢, then the firm’s total revenue is 40¢ * 1.8 million or $720,000
per day.

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8  CHAPTER 1 Managerial Economics and Decision Making

Of course, total revenue is not always this straightforward. Some complications
can occur, but fortunately they are not overly complex. Discounts, rebates, returns,
and allowances—all called contra revenue by accountants—can affect a firm’s total
revenue:

1. Discounts and rebates. Producers offer buyers discounts for various reasons.
For example, Gannett sells USA Today to distributors such as Hudson Group,
which in turn sells the newspapers to consumers at its Hudson News stores.
Suppose that Rogermark sells its newspapers to another distributor, Realnews.
Rogermark’s contract with Realnews might set a price of 40¢ per paper but
might also offer Realnews a discount if Realnews pays its bill promptly. A “1/10
net 30” discount is common. If the distributor pays the bill within 10 days, the
distributor can take a 1 percent discount. If the distributor does not pay during
that period, the bill is due in full after 30 days. If Realnews purchases 1,000
newspapers at a price of 40¢ for its store in Boston’s Logan Airport and pays
within 10 days, it receives a discount of 0.4¢ * 1,000 = $4. In this case, Roger-
mark’s total revenue is 140¢ * 1,0002 – $4 = $396. Effectively, Rogermark
receives a price of $396>1,000 = 39.6¢ per paper.

2. Returns. Producers often allow retailers to return unsold product at the end
of the selling season. For example, Rogermark’s contract might specify that
Realnews pays 40¢ per paper but can return all unsold copies for credit. If
Rogermark sells 2,500 issues of America Today to Realnews for distribution at
LaGuardia Airport and the Realnews stores sell only 1,500 papers, Realnews
will return 1,000 papers for credit. In this case, Realnews will claim a credit
of 40¢ * 1,000 = $400. With the returns, Rogermark’s total revenue is
140¢ * 2,5002 – $400 = $600. With the return credit, Rogermark receives an
effective price of $600>2,500 = 24¢ per paper for the 2,500 papers.

3. Allowances. Producers frequently enter into agreements with retailers about
allowances for various factors, such as advertising, retail display, or spoilage.
Rogermark might offer Realnews a contract including a 5 percent retail display
allowance for placing the America Today issues at eye level. If Rogermark sells
1,200 issues of America Today to Realnews to sell in Penn Station, before the dis-
count Rogermark would receive 40¢ * 1,200 = $480. Realnews will claim an
allowance of 5 percent, or 0.05 * $480 = $24, leaving Rogermark with total
revenue of $480 – $24 = $456, for an effective price of $456>1,200 = 38¢ per
paper for the 1,200 sold to Realnews.

To calculate total revenue, it is easier to adjust the price than to take these sorts
of factors explicitly into account. The equation TR = P * Q is still used, but P is
now the adjusted price. For example, if Rogermark offers a 5 percent advertising
allowance, reduce the price by 5 percent (from 40¢ to 38¢) to capture the effect of the
discount. With this change, the total revenue from 1,200 issues of America Today
equals 38¢ * 1,200 = $456. Although the economic models you will study in this
text do not specifically discuss adjustments for discounts, rebates, returns, or allow-
ances, in your calculations as a manager you might need to make some modifications
depending on the contractual arrangement.

Accounting Cost and Opportunity Cost
Cost is more complicated than revenue. Accountants use a measure of cost called
accounting cost, while economists and successful managers use a different measure,
called opportunity cost. Why do accountants use one measure and economists use

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1.3 Profit, Accounting Cost, and Opportunity Cost  9

another, and which should you use in making decisions? Let’s compare the two and
see why opportunity cost is the preferred measure for managers to use.

Accounting Cost
When keeping a firm’s financial records, accountants generally record what are
called accounting costs. For the most part, accounting costs are explicit costs, costs
incurred by running a business that involve cash outflows. Examples of explicit costs
include wages paid to employees and rent paid on a lease. Sometimes accountants
also include implicit costs, costs incurred by running a business that do not involve
cash outflows. Depreciation creates a noncash expense, that is, an implicit cost. In
general, depreciation refers to the wear and tear on buildings or machinery that low-
ers its value. For example, newspaper publishers, such as Gannett (and Rogermark),
use huge web presses (printing presses that use paper fed from rolls) to print each
issue of their newspapers. As operators use these presses, the wear and tear lowers
their value. The fall in the presses’ value is a cost of producing the newspapers. No
cash leaves the firm to pay for the machines’ depreciation, so the fall in value is an
implicit cost for the publisher.

Opportunity Cost
When economists use the term cost, they mean opportunity cost, the return from the
best alternative use of a resource. Of all of the possible ways to use a resource, the best
alternative use is the one that, if selected, would yield the highest return. Because
opportunity cost measures what a firm gives up when a resource is used, it is the best
decision-making tool for managers. For a profit-seeking firm, the return is often the
profit that the alternative use would have provided. For example, if Rogermark uses a
web press to print its America Today newspaper, it cannot use the same press to print
its Dallas Sun newspaper. If printing the Dallas Sun is the only other option for the
press and it has a profit of $2,000, then the opportunity cost of using the press to print
America Today is the profit lost from not printing the Dallas Sun, $2,000.

Like accounting cost, opportunity cost includes both explicit and implicit costs.
There is often no difference in how accountants and economists measure explicit
costs. If Rogermark pays a press operator a salary, including all benefits and taxes, of
$44,000 per year, then both accountants and economists agree that the explicit cost to
Rogermark of employing the press operator is $44,000. Accountants and economists,
however, treat implicit costs in substantially different ways. These differences can be
particularly large when considering the cost of inventory, capital assets, competitive
return on investment, and owner’s time. We consider each of these topics in turn in
the following sections.

Cost of Inventory Manufacturing, construction, retail, and many other businesses
hold inventories of raw materials, works-in-progress, and/or finished goods. These
goods either are ready to be sold (finished goods) or, after some additional work, will
be finished and then available for sale (raw materials, works-in-progress). Managers
need to determine the cost of items held in inventory. Accountants and economists
value the cost of inventory differently. Accountants must use one of the inventory
valuation methods approved by the Internal Revenue Service (IRS), and these meth-
ods depend on the historical acquisition cost. In contrast, economists use the oppor-
tunity cost, the best alternative use for the goods, in the valuation of inventory. These
two measures are rarely equal.

To see the difference between accounting and opportunity costs, suppose that
Christina Corporation, a jewelry manufacturer and retailer like Zale Corporation,
bought 1,000 ounces of gold at a price of $1,300 per ounce and then purchased an

Accounting costs The
costs accountants use to
keep a firm’s financial
records.

Explicit cost A cost
incurred by running a
business that involves
cash outflows.

Implicit cost A cost
incurred by running a
business that does not
involve cash outflows.

Opportunity cost The
return from the best
alternative use of a
resource.

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10  CHAPTER 1 Managerial Economics and Decision Making

additional 1,000 ounces at a price of $1,400 per ounce. Christina now has 2,000
ounces of gold in its inventory. When the firm uses 500 ounces of gold to manufac-
ture necklaces to sell in its jewelry stores, what is the cost of the gold? An accountant
answers this question by using one of the following three IRS-approved inventory
valuation methods:

1. Last in, first out (LIFO) assumes that the last units added to the inventory are
used first. Using this method, the accounting cost of the gold is $1,400 per ounce.

2. First in, first out (FIFO) assumes that the first units added to the inventory are
used first. This method yields an accounting cost of the gold of $1,300 per ounce.

3. A weighted average valuation uses the weighted average of the costs, making the
accounting cost of the gold $1,350.2

The managers’ selection of an inventory valuation method is important because it
affects the taxes the firm must pay. However, none of these methods determines the
opportunity cost to the firm of using the gold. To determine the opportunity cost of
using the gold to make necklaces, you must ask the following question: “Other than
using the gold to make necklaces, what else can Christina do with it?” The answer that
gives the largest profit is the opportunity cost of using the gold. Because the company
owns the gold, often its most profitable alternative action is to sell the gold at the cur-
rent market price. For example, if the current market price of an ounce of gold has risen
to $1,600, then the opportunity cost of using the gold to make necklaces is $1,600 per
ounce. By using the gold to make necklaces, Christina loses the opportunity of selling it
at $1,600 per ounce. Regardless of what price the firm paid for the gold, its opportunity
cost of using the gold to make necklaces is the current market price of gold.

The jewelry company example generalizes easily: The opportunity cost to any
firm of any good or product in inventory is the current market price of the item. If
there is a well-established market, as is the case with gold, the market price is easy to
discover. Many items, however, have no market price. In the case of half-finished air
conditioners or six-month-old red wine being held to age for three years, a market
price is more difficult to establish, and a manager must come up with an estimated
price to determine the opportunity cost.

The Christina Corporation example made a very important point: The price ini-
tially paid for the gold has no bearing on the opportunity cost of using it to make
necklaces. The price paid for the gold is an example of a sunk cost, a cost that cannot
be recovered because it was paid or incurred in the past.

For Christina, the initial price paid for the gold is a sunk cost. For Intel, last
month’s cost of research and development is a sunk cost. Profit-maximizing manag-
ers realize that sunk costs have no bearing on current decisions. Why? Managers
make decisions to minimize costs; because they cannot change sunk costs, effective
managers ignore them when making business decisions.

Cost of Using a Capital Asset Virtually every firm owns some capital assets,
assets that managers cannot quickly sell and that the firm must have to produce
its goods or services. Capital assets include machinery (such as the web presses
owned by Gannett), buildings (such as the building occupied by the Walgreens
drugstore at 7600 Debarr Road in Anchorage), and land (such as the 6,800 acres

Sunk cost A cost that
cannot be recovered
because it was paid or
incurred in the past.

2 The weighted average is calculated according to a 1,000 ounces
2,000 ounces

b * $1,300 + a 1,000 ounces
2,000 ounces

b * $1,400,
where the weights, a 1,000 ounces

2,000 ounces
b, are the fractions of the gold purchased at the different prices.

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1.3 Profit, Accounting Cost, and Opportunity Cost  11

of fertile farmland in Michigan owned by Zwerk & Sons Farm). These capital
assets are quite different from inventory because they are not immediately used
up in the production process.

What is the cost of using a capital asset? Both accountants and economists mea-
sure this cost, but they calculate it differently. Accountants use the depreciation allow-
ance as the cost of using a capital asset, but as usual, economists use the opportunity
cost of using the capital asset.

Depreciation. Some capital assets, such as Gannett’s presses and Walgreens’ build-
ing, have finite lives: They eventually wear out. For these assets, accountants must
use one of the IRS-approved methods to calculate the depreciation allowance of us-
ing the asset. Land, on the other hand, is a capital asset that does not wear out—it
lasts forever—so there is no depreciation allowance.

One IRS-approved depreciation formula is straight-line depreciation, which dis-
tributes the depreciation allowance evenly over the expected useful life of the asset.
For example, Rogermark has purchased a $20 million web press with an expected
useful life of 10 years. After 10 years, the press is valueless. If Rogermark’s accoun-
tants use straight-line depreciation for the 10 years, then each year they record 1>10
of the initial expenditure on the press as that year’s depreciation allowance:
1>10 * $20 million = $2 million per year. These accountants then record a cost of
$2 million on Rogermark’s books.

The accounting depreciation allowance is essentially an arbitrary number cre-
ated by an arbitrary depreciation formula that the IRS has approved for tax pur-
poses, so it rarely equals the true depreciation cost of the asset. The true cost of
depreciation is the change in the market value of the asset. Economic depreciation is
the change in the market value of a capital asset such as land, equipment, or a

Suppose that you are a manager of a mutual fund specializing in biotech companies
that spent $4.5 million to purchase 100,000 shares of Dendreon Corporation for $45
per share. Dendreon made a treatment for prostate cancer, but the treatment did not
prove profitable, and the price of a share fell to $3. As a fund manager, should you
hold (not sell) the stock because you paid $4.5 million for shares of stock that are
now worth only $300,000? Explain your answer.

Answer
The $4.5 million spent for the shares is a sunk cost because you have already
incurred it and you cannot change it. Consequently, you should ignore it in mak-
ing your decision. As a manager, you should compare the profit you expect from
holding the 100,000 shares of Dendreon to the profit you expect from the most
profitable alternative use of the funds and then select whichever is the larger. You
can sell the stock and invest the $300,000, or you can hold onto the stock hoping
that the price increases. As it happens, Dendreon eventually went bankrupt, and
its stock became worthless. If you had decided you could not sell because of your
initial $4.2 million loss, you would eventually have lost the entire $4.5 million!

DECISION
SNAPSHOT Sunk Costs in the Stock Market

Economic depreciation
The change in the market
value of a capital asset
such as land, equipment,
or a building.

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12  CHAPTER 1 Managerial Economics and Decision Making

building.3 Notably, the accounting depreciation allowance for land is zero because it
does not wear out. Its economic depreciation, however, is not necessarily zero
because the market value of land can change.

Suppose that during a particular year the market value of a press Rogermark
owns falls from $20 million to $17 million. In this year, the economic depreciation of
the press equals $20 million − $17 million, or $3 million. By owning the press,
Rogermark has incurred an opportunity cost equal to its economic depreciation of
$3 million. Rogermark’s true depreciation cost of using the press is not the $2 million
depreciation allowance accountants must use but rather the loss of $3 million in
value. Managers should use economic depreciation rather than the accounting
depreciation allowance when making their decisions because economic depreciation
accurately measures the firm’s opportunity cost of the depreciation from using
the asset.

The Opportunity Cost of the Capital Asset. Because accountants must adhere to
IRS-approved depreciation schedules, they record the accounting depreciation allow-
ance as the cost of using a capital asset. Economists realize that a firm has options for
the capital asset other than using it, so the firm incurs an opportunity cost in addition
to the economic depreciation when it uses the asset. To determine this opportunity
cost, you must ask yourself the following question: “Other than using the asset itself,
what else can a firm do with it?” The best alternative use—the one that generates the
largest profit—is the opportunity cost of using the asset.

Take Rogermark’s $20 million web press, for example. Suppose that if Roger-
mark uses the press, the firm’s only option is to use it to print America Today newspa-
pers. Other than using the press to print that paper, what else can Rogermark do
with it? There are two possible answers to this question: Rogermark can either rent
the press (presuming there is a rental market for presses) or sell it. Comparing rent-
ing and selling is difficult because it involves comparing a stream of payments over
time (from renting the press) to a single payment (from selling the press). Chapter 16
explains how you can make this comparison if the company rents the asset for more
than one year. For now, to simplify the analysis, assume that Rogermark is interested
in the opportunity cost of using the press for a single year, so the relevant compari-
son becomes rental of the press for one year versus its sale.

In general, the profit from renting a capital asset is the rental payment minus any
related costs incurred by the owner. These costs can depend on the rental contract. For
example, a building owner can rent a building using a triple net lease, in which case
the owner receives the rent and the renter is responsible for the maintenance costs,
property insurance, and property taxes. For our Rogermark example, let’s suppose
that some other printer rents the press for $3.6 million per year under a triple net
lease, so the renter covers the maintenance and insurance costs. There is, however,
also the cost of the economic depreciation. At the end of the year, Rogermark still
owns the press, so the firm has incurred the opportunity cost of the economic depre-
ciation. Suppose, as above, that the economic depreciation is $3 million. Subtracting
this cost from the rental payment gives Rogermark a net profit of $0.6 million.4

Compare this amount to the return from the other alternative, selling the press.
If Rogermark sells the press, how do you determine its return for one year? Suppose

3 Sometimes a capital asset, such as land, rises in value; that is, it appreciates. Regardless of whether the
asset rises or falls in value, the change in the market value is still called economic depreciation.

4 If the capital asset (such as land) appreciates in value, you must add the gain to the rental revenue to
calculate the profit from renting the asset.

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1.3 Profit, Accounting Cost, and Opportunity Cost  13

that the firm sells the press for its market value, $20 million. This price buys owner-
ship of the press. It is not the one-year return. To determine the one-year return, you
need to analyze Rogermark’s investment opportunities. Assuming that the most
profitable investment opportunity for the year yields a profit of 12 percent, Roger-
mark can use the $20 million gained from the sale of the press to fund this opportu-
nity, for a profit at the end of the year of $20 million * 0.12 = $2.4 million. More
generally, the one-year profit from selling an asset is equal to

P * r

where P is the price of the asset and r is the highest one-year profit rate available to
the seller. Economic depreciation does not affect the firm’s return from selling the
asset because the firm no longer owns it.

Now that you have calculated the values of the alternative uses of the press, you
can determine Rogermark’s opportunity cost of using it. The opportunity cost equals
the higher of the two returns. The return for renting the press is $0.6 million, and the
return for selling the press is $2.4 million. The most profitable alternative is obvi-
ously selling the press, so the opportunity cost to Rogermark of using the press to
print America Today is $2.4 million per year.

The example demonstrates a critical difference between accounting cost and
opportunity cost: The accounting depreciation allowance ($2 million per year) is not

You belong to a group of local entrepreneurs that owns a 10-acre blueberry farm
called Singing the Blues. You could farm the land yourselves or rent it out for
$7,000 per year. Another option is to sell the land this year at its current market
price of $80,000. The price of the land next year will be $78,000. If you sell it, your
group has an investment opportunity from which you expect to make a return of
6 percent per year. What is the opportunity cost of using the land this year to grow
blueberries?

Answer
To decide how to use the land, your group needs to know its opportunity cost, its best
alternative use. The alternative uses are to rent the land or to sell it. If you rent the
land, your return is the rent ($7,000) adjusted by any economic depreciation (change
in the market value). In this case, the economic depreciation is $2,000 because the
market price of the land falls from $80,000 to $78,000. Accordingly, the total return
from renting the land is the rental payment minus the economic depreciation:

7,000 – $2,000 = $5,000

The one-year return from selling the land is

$80,000 * 0.06 = $4,800

The opportunity cost to the owners of using the land is the greater of these two
numbers, or $5,000. Consequently, when calculating the profit from using the land
to grow blueberries, your group should include $5,000 as the cost of using the land.

DECISION
SNAPSHOT

Opportunity Cost at Singing the Blues
Blueberry Farm

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14  CHAPTER 1 Managerial Economics and Decision Making

the same as the opportunity cost of using the press ($2.4 million per year). In this
particular case, if Rogermark’s managers use the accounting allowance, they will
underestimate the actual cost of using the press. This error might lead the managers
to make bad decisions. For example, underestimating the cost of using the press will
encourage the managers to use the press even if the firm’s profit would be greater if
they sell it.

Cost of Competitive Return on Invested Funds Accountants often ignore the
opportunity cost of the funds the owners have invested in the firm. In order to start
a business, the founders almost always use some of their own funds, perhaps to pur-
chase machinery, a building, or inventory. By investing their funds in the firm, the
owners lose the opportunity to use the funds elsewhere. The opportunity cost of the
funds tied up in the firm is the return the owners could have made by using the funds
in the next best endeavor. The return the owners can make is determined in compet-
itive markets, so this opportunity cost is called the competitive return. For example,
if the owners invest $600,000 in their business when they could make an alternative
rate of return of 9 percent on these funds, the owners’ competitive return is equal to
$600,000 * 0.09 = $54,000. In other words, the owners have lost the opportunity
to make $54,000 by committing their funds to the business instead of the alternative
opportunity.

Cost of Owner’s Time Owners of firms who also work in the business typically
pay themselves a salary, which constitutes an explicit opportunity cost. This salary,
however, does not necessarily reflect the true opportunity cost of the owners’ time
because owners frequently have other options that affect their opportunity costs. You
must take account of the return from these other options to calculate the owners’
opportunity cost of working for their own company.

For example, suppose that after graduation, you receive an offer from Comp-
ton Consulting, a firm similar to Deloitte Consulting, for a position that pays a
salary, including all benefits, of $105,000 per year. Instead of taking the offer, you
opt to create a marketing firm. You pay yourself a salary, again including all bene-
fits, of $65,000 per year. Your salary is definitely part of the opportunity cost of
running the firm, but it is not the total opportunity cost of your time. If you were
not running the firm, you would be working at Compton Consulting, making
$105,000 per year. Because working at that firm is your best alternative, the total
opportunity cost for your time is $105,000. Your marketing firm incurs an opportu-
nity cost of $105,000 for each year you spend in the company. Of the $105,000
opportunity cost, $65,000 is an explicit opportunity cost and $40,000 is an implicit
opportunity cost.

Suppose that you decide to pay yourself $120,000 rather than $65,000. In this
case, the opportunity cost to your firm for your time is still $105,000, your best alter-
native foregone—that is, the best alternative use of your time. Of your $120,000 sal-
ary, $105,000 is the opportunity cost of your time, and the remainder, $15,000, is a
payment to you of some of the competitive return on the funds you have invested in
your company.5

Competitive return The
opportunity cost of the
owners’ funds invested in a
company.

5 The IRS limits the amount of salary that owners of a corporation can pay themselves. If owners distrib-
ute the corporation’s profit to themselves as dividends, the IRS collects both the corporate income tax on
the profit and the personal income tax on the dividend income. The IRS’s concern is that by “overpaying”
themselves, owners transfer the corporation’s profit to themselves as salary, thereby avoiding the corpo-
rate income tax and paying only the personal income tax.

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1.3 Profit, Accounting Cost, and Opportunity Cost  15

Comparing Accounting Cost and Opportunity Cost
As you have already learned, there are definite differences between accounting cost
and opportunity cost. The following example compares the accounting cost and the
opportunity cost for a hairdressing shop. Often these salons are franchised. Regis
Corporation, for example, offers franchise opportunities for many different hair
salon concepts. Suppose that two friends form a partnership and decide to buy a
franchise from Swift Cuts Hair Salon. You will see how accounting cost can give a
misleading picture of their firm’s health.

To acquire the right to run the Swift Cuts franchise from the parent company, the
two partners must pay a franchise fee and a fee based on their sales. They already
own the building and all of the equipment they need, but they will have to hire
employees and pay various costs of operating the business. The cost and revenue
data are as follows:

• Building and equipment. Currently at the beginning of the year, the building
and equipment are worth $800,000; at the end of the year, they are worth
$780,000. The owners purchased the building and equipment five years ago for
$1,000,000. Their accountants use straight-line depreciation for the 20-year life of
the building and equipment, so one year’s depreciation allowance is $50,000.
Currently, the owners can sell the building and equipment for $800,000 or rent
them for $60,000 per year. If they rent the building and equipment, they will do
so with a triple net lease, so that the renter pays all maintenance costs, property
insurance, and property taxes.

• Salaries. The owners employ eight hair stylists, an office manager, and them-
selves. Each of the eight hair stylists is paid $40,000, the office manager is paid
$50,000, and the two owners pay themselves $60,000 each. If the owners did not
own the business, each would work for a competitor for $80,000.

• Other costs. The costs of the electricity, hair coloring, property taxes, and every-
thing else required to run the business are $200,000.

• Franchise fee. To purchase the right to operate a Swift Cuts franchise, the own-
ers paid a franchise fee of $1,250,000.

• Alternative investment. The owners can invest any funds they possess and
make a profit of 4 percent.

• Revenue. The franchise sells 27,000 hair stylings per year at a price of $31.25
each. From this revenue, the franchise must pay the parent company a fee of
4 percent.

Table 1.2 shows the total revenue, accounting cost, and opportunity cost. Com-
puting the total revenue is straightforward. Adjusting the $31.25 price per hairstyl-
ing downward by 4 percent because of the franchise fee gives an adjusted price of
$30.00, making the total revenue after the fee $30.00 per styling * 27,000 stylings =
$810,000. This total revenue is the same in the accounting cost and opportunity cost
columns of Table 1.2.

Now compare the costs of doing business:

• The costs for the salaries of the hair stylists 1$40,000 * 8 = $320,0002 and the
office manager 1$50,0002 are explicit costs and are the same in both the account-
ing cost and the opportunity cost columns of Table 1.2.

• The cost of the owners’ efforts differs. The accounting costs column records the
explicit cost of the owners’ salaries 1$60,000 + $60,000 = $120,0002. Because
each owner’s next best opportunity is to work for a competitor at a salary of

M01_BLAI8235_01_SE_C01_pp001-032.indd 15 23/08/17 9:48 AM

16  CHAPTER 1 Managerial Economics and Decision Making

$80,000, the owners’ opportunity cost of working for their business is $80,000 +
$80,000 = $160,000, the opportunity cost of the owners’ time.

• “Other costs” are the miscellaneous other (explicit) costs of operating the business,
such as the cost of the hair colorings used. These amounts are the same ($200,000)
in both the accounting cost and the opportunity cost columns in Table 1.2.

• The accounting cost column records the depreciation allowance, calculated
using straight-line depreciation, for a charge of $50,000. The opportunity cost
column includes the opportunity cost of using the building and equipment,
which depends on the return from selling the building and equipment versus
the return from renting them. If the owners sell the building and equipment,
they receive $800,000, which they can invest for a profit of 4 percent or
$800,000 * 0.04 = $32,000. Or the owners can rent them out for $60,000. Over
the year, the building and equipment fall in value from $800,000 to $780,000 for
an economic depreciation of $20,000. The net profit from renting the building
and equipment equals $60,000 minus the cost of the economic depreciation
($20,000) for a profit of $40,000. The profit from renting exceeds that from sell-
ing, so the opportunity cost of using the building and equipment is $40,000.

• The opportunity cost column includes one additional cost, the competitive
return on the invested funds. This entry represents the opportunity cost to the
owners for the franchise fee of $1,250,000. Because their alternative use for these
funds yields a 4 percent return, the competitive return on these funds is
$1,250,000 * 0.04, or $50,000.

As shown in Table 1.2, the owners have an accounting profit of $70,000 when
using accounting cost but a loss of $10,000 when considering opportunity cost. As you
will learn in Chapter 5, this loss, called an economic loss, indicates that the owners’
income from running the business is not enough to compensate them for all of their
opportunity costs. In other words, the owners’ total income from operating the busi-
ness is $10,000 less than it would be if they closed the business and used their resources
(their time, the building and equipment, and the funds they invested in the business)
in their best alternative endeavors (working for the competitor, renting the building
and equipment to someone else, and investing the funds at a competitive return).

Table 1.2 Comparing Accounting Cost and Opportunity Cost

Profit Using Accounting Cost Profit Using Opportunity Cost

Total revenue $810,000 Total revenue $810,000

Cost Costs

Hair stylists $320,000 Hair stylists $320,000

Office manager 50,000 Office manager 50,000

Owners’ salary 120,000 Owners’ time 160,000

Other costs 200,000 Other costs 200,000

Depreciation
allowance

50,000
Cost of using building and

equipment (opportunity cost)
40,000

Competitive return 50,000

Total cost $740,000 Total cost $820,000

Total profit $ 70,000 Total profit $ – 10,000

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1.3 Profit, Accounting Cost, and Opportunity Cost  17

Using Opportunity Cost to Make Decisions
Opportunity cost is a better estimate of the true costs faced by a business than
accounting cost and is therefore crucial to managerial decision making. If you accept
for a moment the reasonable idea that more accurate cost estimates lead to better
decisions, you will understand the value of using opportunity cost. In the Swift Cuts
example, the total revenue from the franchise is less than the opportunity cost of
running the business. The accounting cost gives the appearance of a highly profit-
able operation that is likely to remain in business indefinitely. Yet because the own-
ers are not covering their opportunity cost, they would be better off if they closed the
business and invested their resources in other endeavors. Similarly, the managers at
Christina Corporation who use the opportunity cost approach to value their gold
inventory will better understand whether selling the gold or using it to make jewelry
is more profitable. In both cases, opportunity cost leads to the best decision.

Managers who rely on accounting cost as the basis for their decisions will make
poorer decisions than managers who use opportunity cost. For example, the manag-
ers at state transportation departments have a goal of reducing traffic deaths.
Suppose that one state’s transportation department analysts predict that spending
$10 million on a program to increase the number of bicyclists who wear helmets will
save 5 lives. The accounting cost of this program is $10 million. The accounting cost
might make this program seem worthwhile. But suppose that the alternative use for
this funding is a program to decrease aggressive driving that the same analysts fore-
cast will save 10 lives. The opportunity cost of the program to increase helmet wear-
ing is the aggressive driving program. Once the managers consider the opportunity
cost, they are likely to reject the program to increase helmet wearing in favor of the
program to decrease aggressive driving. As this example shows, it is safe to con-
clude that managers who base their decisions on opportunity cost will have more
successful careers.

Opportunity cost is one tool economists use to make decisions. The next section
introduces marginal analysis, another decision-making tool that you will find useful
throughout both your study of managerial economics and your career.

Resting Energy’s Opportunity Cost

The managers at Resting Energy, a major producer of solar cells, buy a solar wafer
inspection system from Adjunct Materials for $5 million. Resting Energy’s managers
expect to use the inspection machine for two years, after which it will be obsolete and
worthless. They believe that the machine’s resale price is $5 million at the start of the
first year, $3 million at the start of the second year, and $0 at the start of the third year.
Resting Energy’s managers have investment opportunities that enable them to make a
one-year return of 10 percent. Alternatively, they can lease the machine with a triple net
lease for $3 million for the first year and $2 million for the second year. What is the
opportunity cost of using the machine for each of the two years?

Answer

The opportunity cost is the profit from the best alternative use of the machine. Resting
Energy’s managers have two alternative uses: They can sell the machine, or they can
lease it.

SOLVED
PROBLEM

(Continues)

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18  CHAPTER 1 Managerial Economics and Decision Making

1.4 Marginal Analysis
Learning Objective 1.4 Explain how managers can use marginal analysis to
make better decisions.

As a manager, you know that the decisions you make will have different effects on
your firm’s goal and your career, some small and some large. You always want to
make the decision that most strongly advances your firm’s goal, whether it is profit
for Intel, justice for the Justice Department, or lives saved for the Bill and Melinda
Gates Foundation.

Any action you take gains benefit and incurs cost. Perhaps the most important
decision-making device in an economist’s toolkit is marginal analysis, the comparison
of the marginal benefit from an action to its marginal cost in order to decide whether to
take the action. The word marginal means “additional.” So marginal analysis focuses
on the additional benefit from an action (not the total benefit from all of the actions
taken), as well as the additional cost of an action (not the total cost from all of the
actions taken). You can use marginal analysis in many different circumstances to help
make your decisions. We introduce marginal analysis in this chapter but revisit it in
Chapter 4 and succeeding chapters throughout the text to illustrate how managers can
use it to achieve their firm’s goals, whether they are maximizing profit or saving lives.

The Marginal Analysis Rule
As a manager, you should use marginal analysis in making decisions about a multi-
tude of issues, including the quantity of a product to produce, the amount of advertis-
ing to buy, the extent of auditing to undertake, and which life-saving projects to fund.
Although these decisions differ dramatically, in each case you must compare the mar-
ginal benefit from a unit of the activity to its marginal cost. If the marginal benefit of
the action exceeds its marginal cost, then the action should be performed. If the mar-
ginal benefit of the action is less than its marginal cost, then the action should not be
performed. These conclusions are referred to collectively as the marginal analysis rule.

Marginal analysis The
comparison of the marginal
benefit from an action to its
marginal cost in order to
decide whether to take the
action.

If they sell the machine at the start of the first year, they make

$5 million * 0.10 = $0.5 million

If they sell it at the start of the second year, they make

$3 million * 0.10 = $0.3 million
If they lease the machine, they receive the rental payment but must subtract the
economic depreciation, the fall in the market price of the machine—$2 million the
first year and $3 million the second year. So if they lease it for the first year, they make

$3 million – $2 million = $1 million

If they lease it for the second year, they make

$2 million – $3 million = – $1 million

Whichever action has the highest profit is the opportunity cost. For the first year, the
opportunity cost (from leasing the machine) is $1 million, and for the second year, the
opportunity cost (from selling the machine) is $0.3 million.

SOLVED PROBLEM (continued )

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1.4 Marginal Analysis  19

The intuition behind the marginal analysis rule is powerful. If the marginal ben-
efit of the action exceeds its marginal cost, then undertaking the action results in a
net gain. Conversely, if the marginal benefit of the action is less than its marginal
cost, then undertaking the action creates a net loss. No manager wants to incur a
loss, so in this case you definitely do not want to undertake the action.

Using Marginal Analysis
As a manager, decisions you make may include how much flour to produce, whether
to purchase boosted Facebook posts, how many auditors to hire, or which antima-
laria project to fund. In this introductory chapter, you do not yet have the foundation
to examine a specific business decision, so we look at the marginal benefit and mar-
ginal cost of an action without identifying the specific action.

Figure 1.1 includes two curves to help illustrate marginal analysis. The marginal
benefit curve (MB) is linear, and the marginal cost curve (MC) is curved, but that is
not always the case. Both might be linear or curved, or MC might be linear and MB
curved. The shape of the curves is not important. However, the vertical distance
between the two curves is crucial for marginal analysis because it measures the dif-
ference between the marginal benefit and the marginal cost. In Figure 1.1,
the 10th unit of the action has a marginal benefit of $50, labeled as point A, and a

• If the marginal benefit of an action exceeds the marginal cost of the action,
then the action should be performed.

• If the marginal benefit of an action is less than the marginal cost of the action,
then the action should not be performed.

MARGINAL ANALYSIS RULE

Marginal benefit and marginal
cost (dollars per unit)

Action (unit)

$60

$10

$20

70605040302010

$30

$40

$50

0

MC

A

C

D
B

MB

Figure 1.1 Marginal Analysis

The marginal benefit curve (MB) shows the marginal
benefit from each unit of the action. The marginal cost
curve (MC) shows the marginal cost of each unit of the
action. For the 10th unit of the action, the marginal
benefit is $50 (point A), and the marginal cost is $10
(point B), so undertaking this unit yields a surplus of
benefit over cost (or profit) of $50 – $10 = $40.
Similarly, the 30th unit, with points C and D, has a
surplus of $15. All units of the action up to the 40th
unit have a surplus and should be undertaken. All
units beyond the 40th unit have a loss and should not
be undertaken. Forty units of the action provides the
maximum gain.

M01_BLAI8235_01_SE_C01_pp001-032.indd 19 23/08/17 9:48 AM

20  CHAPTER 1 Managerial Economics and Decision Making

marginal cost of $10, labeled as point B. The vertical distance between these two
points indicates that if the managers undertake this unit of the action, they will
receive a surplus of benefit over cost of $50 − $10, or $40. This amount is equal to
the length of the arrow between points A and B. Similarly, the arrow between
points C and D shows that the 30th unit has a surplus of benefit over cost of $15.
For a profit-seeking firm, the surplus of benefit over cost equals the profit. For a
charity or other nonprofit organization, it might be the additional number of peo-
ple helped.

Figure 1.1 shows that the marginal benefit exceeds the marginal cost up to the
40th unit of action, so each of these units has a surplus of benefit over cost and
thereby increases the total surplus. Some units of the action increase the total surplus
by more than others (compare the surplus of benefit over cost of the 10th unit and
that of the 30th unit), but managers want to undertake all of the units up to the 40th
because they all increase the total surplus. The marginal benefit is less than the mar-
ginal cost for all units of the action beyond the 40th, so each of these units has a loss.
Needless to say, managers do not want to undertake any of these units.

In short, to maximize total surplus (or total profit), managers want to under-
take all of the profitable units of the action and none of the unprofitable ones. As
you can see from Figure 1.1, at 40 units the marginal benefit of the action equals
its marginal cost, or MB = MC. By performing 40 units, the managers have max-
imized their total surplus because they have undertaken all of the profitable
units and none of the unprofitable ones. This conclusion generalizes: To maxi-
mize total surplus (profit), managers want to undertake the quantity at which
MB = MC.6 You will return to this important conclusion throughout future
chapters.

In your career as a manager, it is highly unlikely that you will possess a figure,
such as Figure 1.1, that shows the marginal benefit curve and marginal cost curve.
Instead, you must apply marginal analysis to informed estimates of marginal
benefits and marginal costs. The goal remains the same, however: Undertake all the
actions until you reach the point where MB = MC.

6 The appendix to this chapter uses calculus to demonstrate that undertaking the quantity that sets
MB = MC maximizes the total surplus.

How to Respond Profitably to Changes in Marginal Cost

Suppose that the marginal cost of the action illustrated in Figure 1.1 increases by $15
for each unit of the action. For a profit-maximizing firm, what quantity of the action
maximizes the firm’s profit?

Answer

The increase in marginal cost shifts the marginal cost curve in Figure 1.1 upward, as shown
in the figure here. The new marginal cost curve is labeled MC1. For each unit of the action,
the arrows show that the new MC1 curve lies $15 above the initial MC curve. With the higher
cost, only the units up to the 30th are profitable. To maximize the profit from this activity, the
manager should undertake 30 units of the action, the quantity at which MB = MC1.

SOLVED
PROBLEM

M01_BLAI8235_01_SE_C01_pp001-032.indd 20 23/08/17 9:48 AM

Revisiting How Managers at Sears Holdings Used Opportunity
Cost to Make Tough Decisions

At the beginning of the chapter, you learned how Sears’ falling sales forced Sears Holdings’ executives to
make decisions about closing stores. These executives
used marginal analysis to make their decisions. Because
Sears is a for-profit business, you can identify the stores
with a marginal benefit (MB) that exceeds marginal cost
(MC ) as profitable and the stores with a marginal bene-
fit that falls short of marginal cost as unprofitable. Sears’
executives determined that the optimal number of stores
for Sears Holdings was 630 because, ranking their stores
by profitability, all the stores up to the 630th were profit-
able and additional stores were unprofitable. When Kmart
purchased Sears, Sears operated over 1,600 stores, so the
executives needed to close over 900 unprofitable stores.

Sears’ executives had accounting data on which stores
were profitable. This information can be helpful when mak-
ing decisions about which stores should close and which
should remain open, but the accounting data should not be
definitive. As you have learned, accountants do not consider
opportunity cost when calculating cost and profit. Effective
and successful managers always use opportunity cost in
making managerial decisions. Edward Lampert, the chief
executive officer and a major shareholder of Sears Holdings,
definitely used opportunity cost when making his decision
about which stores to close.

Sears’ accountants used the rent charged the stores
as the cost of their location, but as Mr. Lampert knew, some-
times the rental payment does not equal the opportunity

Marginal benefit and marginal
cost (dollars per unit)

Action (unit)

$60

$10

$20

70605040302010

$30

$40

$50

0

MC

MB

MC1

If the marginal cost of the activity increases, keeping the action level at 40 units means
that for some units the marginal benefit now falls short of the higher marginal cost. The
amount of the action must be reduced until the marginal benefit equals the marginal
cost, in this case from 40 to 30.

The marginal analysis rule indicates that anytime the marginal cost increases, less
of the action should be undertaken because fewer units have a marginal benefit that
exceeds its marginal cost. Of course, the converse is also true: Anytime the marginal
cost decreases, more of the action should be undertaken.

Revisiting How Managers at Sears Holdings Used Opportunity Cost to Make Tough Decisions  21

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22  CHAPTER 1 Managerial Economics and Decision Making

Summary: The Bottom Line

1.1 Managerial Economics and Your Career
• The goal of this text is to show you how to make better

decisions by using managerial economics, the applica-
tion of microeconomic principles to business problems
faced by decision makers.

• Microeconomic principles are frequently illustrated
using economic models, which are abstract, simplified
representations of the real world and real-world situ-
ations. These principles can improve the decision-
making process.

1.2 Firms and Their Organizational
Structure

• A firm is any organization that converts inputs into
outputs that it can sell or distribute. Firms can be for-
profit or nonprofit, as well as government or nongov-
ernment organizations.

• Sole proprietorships businesses owned by one person,
are easy to organize, and their profits are taxed only
once. The owners of sole proprietorships face unlim-
ited liability.

• The profits of partnerships, businesses owned by two
or more people, are taxed only once. Generally, part-
ners face unlimited liability—they are jointly and indi-
vidually liable for all debts of the partnership.

• The profits of a limited liability company, a company
owned by one or more members who have limited lia-
bility for its debt, are taxed only once.

• The profits of corporations, businesses owned by one
or more shareholders, are taxed twice. Corporate
shareholders have limited liability.

1.3 Profit, Accounting Cost, and
Opportunity Cost

• The primary objective of for-profit business owners is
maximizing their firm’s profit.

• Accounting cost is based on accounting rules and
guidelines. Opportunity cost is the value of the best
alternative use of a resource. The two cost measures
differ most frequently for implicit costs, including the
use of capital assets and the competitive return on
invested funds.

• The opportunity cost of a capital asset is its best alter-
native use, the use that generates the largest profit.
Economic depreciation, the change in the market value
of a capital asset, is part of the opportunity cost if the
firm retains ownership of the asset.

• The opportunity cost of the funds invested in the busi-
ness is the competitive return the owners could make
by using the funds in another endeavor.

• Managers of all types of organizations make better
decisions if they consider opportunity cost rather than
accounting cost.

1.4 Marginal Analysis
• Marginal analysis compares the marginal benefit from

an action to its marginal cost in order to decide
whether to take action.

• According to the marginal analysis rule, if the mar-
ginal benefit from an action exceeds its marginal cost,
the decision maker should take the action, but if the
marginal benefit is less than its marginal cost, the deci-
sion maker should not take the action.

cost. Many of the Sears stores had long-term leases, and
other companies had offered Sears Holdings substantial
payments to use these spaces. When another retailer offers
to pay to take over a space, the opportunity cost of keeping
the store open at that location includes the foregone pay-
ment. If the payment is large enough, it can increase the
store’s opportunity cost so much that its accounting profit
masks an economic loss. Marginal analysis then shows that
Sears Holdings could increase its profit if it took the action
to close the store to eliminate the economic loss.

Mr. Lampert explained his decision to close some stores
by writing the following: “In some places mall owners and

developers have approached us with the opportunity to repo-
sition our stores for other uses and are willing to compen-
sate us. When they’ve offered us more money to take over
a location than our store there could earn over many, many
years, we’ve accepted offers.” Although he did not use eco-
nomic jargon in his answer, Mr. Lampert clearly understood
how to use the concepts presented in this chapter when
making profit-maximizing decisions. He correctly decided to
close stores that Sears’ accountants might have concluded
were making a profit because he knew that the opportunity
cost of keeping some of these stores open was so high that
closing them was the profit-maximizing decision.

M01_BLAI8235_01_SE_C01_pp001-032.indd 22 12/09/17 4:37 PM

Key Terms and Concepts
Accounting costs

Competitive return

Economic depreciation

Economic model

Explicit cost

Firm

Implicit cost

Managerial economics

Marginal analysis

Opportunity cost

Profit

Sunk cost

Total revenue

Questions and Problems
All exercises are available on MyEconLab; solutions to even-numbered Questions and Problems appear in the back of
this book.

1.1 Managerial Economics and Your Career
Learning Objective 1.1 Describe managerial
economics and explain how it can help
advance your career.

1.1 How do you think your course in managerial
economics will help you advance your career?

1.2 Consider the following statement: “Economic
models are useless because they are so abstract
and so simple.” Is this statement true or false?
Explain your answer.

1.2 Firms and Their Organizational
Structure
Learning Objective 1.2 Define what a firm
is and describe the legal structures of
for-profit firms.

2.1 How do the advantages and disadvantages of
sole proprietorships and partnerships compare to
those of corporations?

2.2 Why are nearly all large firms organized as
corporations?

1.3 Profit, Accounting Cost, and
Opportunity Cost
Learning Objective 1.3 Compare opportunity
cost and accounting cost and explain why
using opportunity cost leads to better
decisions.

3.1 Rob Kalin founded Etsy, an online marketplace
where crafters sell unique products. Etsy com-
petes with eBay and Amazon.com. Six years
after its founding, Mr. Kalin said that maximiz-
ing shareholders’ value, which is effectively the

same as maximizing profit, was “ridiculous.”
The major investors financing the company
removed Mr. Kalin from his position as the head
of the company within a few months. Explain
why they favored his removal.

3.2 Pete Kendall, an offensive lineman with the
New York Jets, was extremely cooperative when
the team needed help. At the club’s request, he
switched positions, helped two promising rook-
ies, and restructured his contract to help the Jets
squeeze under the salary cap. The following
year, when the Jets had more room under the
salary cap, Mr. Kendall was disappointed that
the Jets did not reciprocate and adjust his contract
higher. He said, “You never can expect a team to
do the right thing out of the goodness of their
hearts.” Explain why the actions of the Jets’
managers should not have surprised
Mr. Kendall.

3.3 Several decades ago, the British and French gov-
ernments agreed to jointly produce the Con-
corde, a supersonic plane. After British taxpayers
had spent £300 million (over $2 billion in terms
of money today) to help develop the plane, the
British government concluded that because this
vast sum of money had been spent, any decision
to cancel the plane was nonsensical and, conse-
quently, the only reasonable decision was to fin-
ish the project. Does this reasoning make
economic sense? Why or why not? (Incidentally,
the plane was finished and flew for 27 years
before it was retired in 2003.)

3.4 Why should managers use opportunity cost
rather than accounting cost when making mana-
gerial decisions?

3.5 Ace Alexia plays professional tennis for a living,
but in spite of her big first serve, she is not

Questions and Problems  23

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24  CHAPTER 1 Managerial Economics and Decision Making

very successful. During the last year, Ace
could have earned $75,000 as a tennis instruc-
tor at the Atlanta Tennis Club. She would have
spent $7,000 on meals, paid rent on a condo in
Atlanta at $800 per month, and made car pay-
ments of $300 per month. Instead, she
remained a pro and won $100,000 in prize
money in various tournaments around the
country. In doing so, she spent $20,000 on
transportation and lodging and paid her
coach/trainer $15,000 for the year. She also
spent $7,000 on meals, paid rent on her condo
in Atlanta at $800 per month, and made the
payments on her car of $300 per month.
a. Would Ace’s total income minus her costs

(her net income) be larger if she became a
tennis instructor than if she played profes-
sional tennis? Provide calculations to sup-
port your answer.

b. What was Ace’s opportunity cost of playing
tennis last year?

3.6 In addition to its namesake cupcake, Hostess
Brands produces Twinkies. Huge mixing-
baking-cooling-wrapping machines produce
both these products in Hostess Brands’ factory
in Emporia, Kansas. These machines mix the
batter for each of the products, pour the batter
into pans, and move the pans into long, winding
ovens where they are baked and then into
equally long, winding tunnels where they are
cooled. Before wrapping them, the machines
finish the tasty treats by injecting filling into
them and applying any necessary topping. The
machines even automatically clean the baking
pans! Which of the following are explicit costs
for Hostess Brands, which are implicit costs, and
which are not costs at all? Explain each of your
answers.
a. The cost of the electricity used to run the

production machines
b. The salary paid to the night-shift manager
c. The wear on the machines as they are used
d. The price paid for the paper used to wrap

the products
e. The fixed lease payments made on the

factory

3.7 Henry Hacker, a professional golfer who was
having some trouble with his driver, decided to
skip the next two tournaments on the PGA tour
to work with his swing coach. He paid his
coach $1,000 and used $1,000 worth of golf
balls. As a result, his driving must have
improved considerably because he now hits his
tee shots longer and straighter. What explicit

and implicit opportunity costs did Henry incur
during the time spent with his swing coach?

3.8 The owners of a local retailer once remarked,
“We can always beat the price that Kohl’s
charges for identical merchandise.” When
questioned, the owners revealed that this was
possible because “Kohl’s must pay rent on its
store while we own our building and have no
rent to pay.” Do these owners have a problem
with their economic logic? Explain your
answer.

3.9 During its telecast of the Olympics, NBC ran an
ad promoting its new “Fall Shows.” Because the
advertisement aired when there was a lull in the
action, an analyst said that the promotion was
free. Is the analyst correct? Explain your answer.

3.10 Grocery stores must allocate shelf space to dif-
ferent brands. What is the opportunity cost to
Safeway, a large grocery store chain, of allocat-
ing more space to Post cereals?

3.11 Harvey owns both a hardware business and the
building that he uses to run the business. What
information would you need to calculate the
total opportunity cost of operating Harvey’s
hardware business?

3.12 You are the manager of a medium-sized farm
with 100 acres of workable land. You can farm the
land yourself, rent the land using a triple net lease
to another farmer for $2,000 per acre, or sell the
land to a developer for $40,000 per acre. You have
an investment opportunity that pays a return of 6
percent a year. What is your opportunity cost for
a year if you decide to farm the land yourself?

3.13 You are a manager of a firm like Oasis Petro-
leum, an explorer and developer of shale oil in
the Williston Basin. You own a drilling rig that
you purchased for $10 million. The life of a
drilling rig is 10 years, and your accountants
use straight-line depreciation. It’s the start
of the year, and the current market value of the
rig is $6 million, so you can sell it to another
driller for $6 million. If you sell the rig, you
can use the funds in an investment that returns
a profit of 9 percent. Alternatively, you
can rent the rig using a triple net lease to
another developer for this year for $1.1 million.
At the end of the year, the rig will be worth
$5.5 million.
a. What is the depreciation allowance?
b. What is your opportunity cost if your firm

uses the rig?
c. What is the true cost to your firm of using

the rig? Explain your answer.

M01_BLAI8235_01_SE_C01_pp001-032.indd 24 23/08/17 9:48 AM

3.14 You are employed by a firm like Adams Land and
Cattle Company, a huge cattle feedlot in Nebraska
with a capacity of 85,000 to 90,000 head of cattle.
Cattle on feedlots are fed diets that are heavy in
barley; one steer eats more than 8 pounds of barley
per day. Suppose that your firm feeds your cattle
200 tons of barley per day and has a stockpile of
4,000 tons of barley for which it paid $250 per ton.
a. If the current price of barley is $300 per ton,

what is your company’s opportunity cost
per day of feeding all its cattle?

b. If the current price of barley is $200 per ton,
what is the opportunity cost per day of feed-
ing all the cattle?

c. Are your answers to parts a and b the same,
or are they different? Explain why.

3.15 Christina Corporation, a firm like Kay Jewelers,
purchased a supply of gold at $1,400 per ounce.
Christina Corporation makes and sells pen-
dants made with one ounce of gold. When gold
is $1,400 per ounce, the firm sells a pendant for
$1,600 at its Christina Jewelry stores. If the
price of gold falls to $800 per ounce and Chris-
tina Corporation’s FIFO method of valuing
inventory leads the manager to continue pric-
ing the pendants at $1,600, what is likely to
happen to the firm’s business, and why?

1.4 Marginal Analysis
Learning Objective 1.4 Explain how managers
can use marginal analysis to make better
decisions.

4.1 Say that you are a manager with the Transportation
Security Administration (TSA). The table shows
fictional estimates of the marginal benefit and
marginal cost of additional TSA security lines at
Mahlon Sweet Field, the airport in Eugene, Oregon.

Number of
Security Lines

Marginal
Benefit

Marginal
Cost

1 $10,000 $ 2,000

2 9,000 3,000

3 7,000 4,000

4 5,000 5,000

5 4,000 8,000

6 3,000 12,000

a. What is the surplus of benefit over cost for
the second security line? For the third secu-
rity line? If your goal is to maximize the
total surplus, would you want to operate
the third security line? Explain your
answer.

b. What is the optimal number of TSA security
lines? Relate this answer to your answer to
part a.

4.2 Suppose that you are a marketing manager for
the Keebler Company, the largest cookie and
cracker manufacturer in the United States. You
determine that the marginal benefit from adver-
tising has increased. Using marginal analysis,
explain how you will change Keebler’s market-
ing budget.

4.3 As an executive for the Elizabeth Glaser Pediat-
ric AIDS Foundation, you have hired the num-
ber of auditors that sets the marginal benefit
of auditing your firm equal to its marginal
cost.
a. Explain why this number of auditors maxi-

mizes your organization’s surplus of benefit
over cost. Draw a figure similar to Figure 1.1
to support your answer.

b. Explain why it is important for you to maxi-
mize the surplus of benefit over cost.

MyLab Economics Auto-Graded Excel Projects  25

MyLab Economics Auto-Graded Excel Projects
1.1 Kristen Larson just graduated at the top of

her massage class from the Aveda Institute in
Des Moines, IA. Her plan is to move to Sioux
City, IA, for at least five years so she can
spend time with her elderly grandparents and
gain experience before branching out into a top
salon in a large city.
Upon graduation, Kristen received a job offer
from Belle Touché, an Aveda Salon and Spa in

Sioux City, for $60,000 dollars (including salary
and health insurance). Kristen would have to
work Tuesday through Saturday from 9 a.m. to
6 p.m. for 50 weeks out of the year. The salon
would pay for all of Kristen’s supplies and
equipment, but she would need to put 20 percent
of her tips each day into tipshare for the front
desk and clean-up employees. Tips are estimated
at $10,000 per year.

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26  CHAPTER 1 Managerial Economics and Decision Making

Kristen also is considering using her $7,500 sav-
ings to be her own boss so she can work fewer and
more flexible hours. For $125 per week ($6,500
per year), she can rent a room at Salon Volume,
but she would have to provide her own supplies,
equipment, and health insurance. She plans to
schedule massages for 25 hours per week at an
average rate of $60 per hour and spend 5 hours
per week on other business duties (scheduling,
bookkeeping, cleaning, purchasing, etc.) for 50
weeks of the year. Tips average 15 percent of the
cost of services, and the cancellation rate (when a
client makes an appointment but ultimately can-
cels, leaving the time slot unfilled) is 5 percent.
Kristen’s estimated costs are detailed below.

• Massage table: $1,500 (one-time expense)
• Lotions, oils, linens, candles, and other sup-

plies: $150 per month
• Remaining on her parents’ health insurance

(she is only 20): $100 per month
• Advertising: $60 per month
• Liability insurance: $50 per month

If Kristen takes the job at Belle Touché, she will
be able to earn 2 percent interest on the money in
her savings account. If she decides to work for
herself, she will have 10 more hours of leisure
each week, which she values at $20 per hour.
Calculate Kristen’s annual economic profit for
each alternative using the template provided.
(Please note that each cell may not have an entry
for both options.) Which option should she
choose based on her economic profit?

Are there aspects of this situation that might
change Kristen’s decision that haven’t been
discussed?

1.2 Cakes by Monica (a bakery under the umbrella
of the Café Brulé restaurant) in Vermillion, SD,
makes cupcakes for purchase from three differ-
ent kinds of customers:

• Type 1: Customers who purchase cupcakes
at their individual price in the store

• Type 2: Customers who order cupcakes
at least 3 days in advance in increments of
1 dozen of each flavor; discount from
the individual cupcake price: $0.25 per
cupcake

• Type 3: Customers who order cupcakes
at least 2 weeks in advance but order at
least 4 dozen of each flavor; discount from
the individual cupcake price: $0.50 per
cupcake

Cakes by Monica charges customers ordering
more cupcakes of the same kind less per cup-
cake because there is less waste and less expense
for larger orders placed further in advance, since
she can order ingredients in bulk from a less
expensive supplier.

Using the information provided, calculate the
total revenue Cakes by Monica will receive from
each type of customer and in total from the sale
of cupcakes at each price. What do you notice
about sales of cupcakes and total revenue as
cupcake prices decline?

Accompanies problem 1.1.

M01_BLAI8235_01_SE_C01_pp001-032.indd 26 23/08/17 9:48 AM

If Cakes by Monica wants to make as much
revenue as possible but keep its current discount
structure, how much should the bakery charge
for its cupcakes? How much total revenue does
the bakery make?

Is there another pricing and discount struc-
ture that would increase total revenue for Cakes
by Monica? If so, what is the total revenue Cakes
by Monica will receive?

MyLab Economics Auto-Graded Excel Projects  27

M01_BLAI8235_01_SE_C01_pp001-032.indd 27 23/08/17 9:48 AM

28

The Calculus of Marginal Analysis

CHAPTER 1 APPENDIX

Section 1.4 introduced marginal analysis, the comparison of the marginal benefit from an action
to its marginal cost, as a way to decide whether to take action. Marginal analysis will emerge
as a crucial managerial decision-making tool. In future chapters, you will learn how managers
can use it in a variety of different circumstances.

The objective of marginal analysis is to maximize the total surplus, the difference between
the total benefit and the total cost of an action. The total surplus for a profit-seeking firm
is usually its total profit. Section 1.4 used a graph (Figure 1.1) to show that the total surplus is
maximized when the quantity of the action taken is such that the marginal benefit (MB) of the
action equals the marginal cost (MC), or MB = MC. Deriving this result more formally using
calculus is straightforward. But before we start with the mathematical definitions of marginal
benefit and marginal cost and the derivation of the maximization rule, we will review a few
mathematical results that occur with some frequency in these appendices.

A. Review of Mathematical Results
In economics, the most commonly used calculus concept is the derivative. Derivatives measure
how one variable changes in response to a change in another variable.

Power Rule

Frequently, we will take the derivative of a power function, such as a cubic function.
Equation A1.1 shows a general cubic function:

y = a + bx + cx2 + dx3 A1.1

where a, b, c, and d are coefficients, y is the dependent variable, and x the independent vari-
able. In Equation A1.1, to take the derivative of y with respect x, or dy/dx, use the power rule.
The power rule for differentiation of a general power function, such as y = axn, is

dy

dx
= 1n * a2x1n – 12

Using this result, the derivative of y with respect to x in Equation A1.1 is

dy

dx
= b + 12c2x + 13d2x2

For example, if the cubic formula is y = 10 + 5x + 4×2 – 6×3, then the derivative, dy/dx, is

dy

dx
= 5 + 12 * 42x – 13 * 62×2 = 5 + 8x – 18×2

Quotient Rule

Another differentiation rule that is often used in economics is the quotient rule. For example, suppose
we need the derivative dy>dx of the equation y = h1x2>g1x2. Then the quotient rule shows that:

dy

dx
=

h1x2 * g’1×2 – g1x2 * h’1×2
3g1x242

in which h’1×2 is the derivative of h1x2 with respect to x and g’1×2 is the derivative of g with
respect to x.

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CHAPTER 1 APPENDIX The Calculus of Marginal Analysis  29

Quadratic Formula

Another mathematical tool that we use with frequency is the quadratic formula, the formula
used to solve a quadratic equation. Equation A1.2 shows a general quadratic equation:

ax2 + bx + c = 0 A1.2

Two values of x solve this quadratic equation. The quadratic formula to solve for the two
values of x is Equation A1.3:

x =
– b { 2b2 – 4 * a * c

2 * a
A1.3

Although you can use the quadratic formula in Equation A1.3 to solve any quadratic
equation, multiple Internet websites have this formula preprogrammed. On these websites,
you insert the values for the coefficients—a, b, c—and the xs that solve the specific quadratic
equation are immediately presented.

Maximization of a Function

To maximize a function with only one independent variable, take the derivative of the
function with respect to the independent variable, then set the resulting equation equal
to zero. This equation is the first-order condition. Solving the first-order condition gives
the independent variable that maximizes the function.1 Call the independent variable
that maximizes the function x*. Using x* in the function gives the maximum value of the
function.

If the function has more than one independent variable, take partial derivatives with
respect to all the independent variables, and then set the resulting equations equal to zero.
Solving these first-order conditions gives the independent variables that maximize the func-
tion. Using the maximizing x*s in the function gives the maximum value of the function.

B. Marginal Benefit and Marginal Cost
The marginal benefit of an action is the change in the total benefit (TB) that results from a
change in the amount or quantity (q) of the action. Using calculus, marginal benefit is

MB =
dTB
dq

The marginal cost of an action is defined similarly. It is the change in the total cost (TC)
that results from a change in the quantity (q):

MC =
dTC
dq

C. Maximizing Total Surplus
The total surplus from an action is equal to the total benefit minus the total cost, where both
are functions of q, or

Surplus1q2 = TB1q2 – TC1q2

1 Taking the derivative of a function and setting it equal to zero gives either an extreme point—that is,
either a maximum or a minimum point—or an inflection point. Technically, to be certain that the point is a
maximum, minimum, or an inflection point, you must determine that the second derivative of the func-
tion is negative, positive, or zero (respectively). The functions we use in this book, however, are such that
when we maximize a function, the resulting extreme point gives the maximum and when we minimize a
function, the resulting extreme point gives the minimum.

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30  CHAPTER 1 APPENDIX The Calculus of Marginal Analysis

The goal of marginal analysis is to find the quantity of the action that maximizes the total
surplus. To maximize total surplus, take the derivative of Surplus(q) with respect to q and set
it equal to zero:

dSurplus

dq
=

dTB
dq


dTC
dq

= 0 A1.4

Equation A1.4 is the first-order condition to maximize the total surplus. In it,
dTB
dq

is MB and
dTC
dq

is MC. Consequently, the surplus-maximizing condition in Equation A1.4 can be rewritten as

MB – MC = 0 1 MB = MC A1.5

which is precisely the result presented in the chapter.

D. Maximizing Total Surplus: Example
When marginal analysis is used in future chapters, the total benefit and total cost functions
will be specified. Often the surplus will be the firm’s profit. For a nongovernment organiza-
tion (NGO), however, the surplus could be the number of vaccines delivered. For a charity, the
surplus could be the net amount of money raised from a funding campaign.

Maximizing Using Total Benefit and Total Cost

For the purposes of this discussion, simply suppose that the total benefit function is
TB = – 0.5q2 + 60q and the total cost function is TC = 0.00194q3 + 0.0208q2 + 9q + 10.
These are the total benefit and total cost functions that lead to the marginal benefit and
marginal cost curves graphed in Figure 1.1.

To determine the q* that maximizes the total surplus, start by using the definition of total
surplus (TS) as TB – TC, or

TS = 1−0.5q2 + 60q2 – 10.00194q3 + 0.0208q2 + 9q + 102 A1.6
Following Equation A1.4, use the power rule to take the derivative of the total surplus with
respect to q and then set it equal to zero:

dTS
dq

= 1 – 1.0q + 602 – 10.00582q2 + 0.0416q + 92 = 0 A1.7

Simplifying the first-order condition in Equation A1.7 gives

– 0.00582q2 – 1.0416q + 51 = 0 A1.8

Use the quadratic formula to solve Equation A1.8. The result is that the surplus-maximizing quan-
tity of actions, q*, is 40, which is the same answer as in Figure 1.1.2 Next, use the profit-maximizing
quantity of actions, 40, in Equation A1.6 to determine the maximum total surplus from this action:

TS = 1- 0.5 * 402 + 60 * 402 – 10.00194 * 403 + 0.0208 * 402 + 9 * 40 + 102
or

TS = 1,072.56

The maximum total surplus from this action is 1,072.56, which is achieved by undertaking
40 units of the action.

Maximizing Using Marginal Benefit and Marginal Cost

Marginal benefit and marginal cost also can be used to find the surplus-maximizing quantity, q*.
Let’s use the same total benefit and total cost functions as before, TB = – 0.5q2 + 60q and

2 The other root of Equation A1.7 is −219, which is meaningless because the quantity of actions must be positive.

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CHAPTER 1 APPENDIX The Calculus of Marginal Analysis  31

TC = 0.00194q3 + 0.0208q2 + 9q + 10. Using the power rule to differentiate the total benefit
function with respect to q gives the marginal benefit function:

MB = −1.0q + 60 A1.9

Similarly, differentiating the total cost function with respect to q gives the marginal cost function:

MC = 0.00582q2 + 0.0416q + 9 A1.10

You can now use the marginal benefit function, Equation A1.9, and the marginal cost function,
Equation A1.10, in the surplus-maximizing equation, Equation A1.5, where MB = MC:

1- 1.0q + 602 = 10.00582q2 + 0.0416q + 9) 1 – 0.00582q2 – 1.0416q + 51 = 0 A1.11
The quadratic equation in the second part of Equation A1.11 is the same quadratic equation

as in Equation A1.8 when we directly maximized the total surplus using the total benefit and
total cost functions. Consequently, the surplus-maximizing quantity, q*, of actions in Equation
A1.11 is 40, just as before. Whether calculating the surplus-maximizing quantity using the total
benefit and total cost or using the marginal benefit and marginal cost, the answer is the same.

Calculus Questions and Problems
All exercises are available on MyEconLab; solutions to even-numbered Questions and Problems appear in the back of
this book.

A1.1 Suppose that an NGO provides medical treatments
to prevent the spread of an epidemic. It can prevent
72q1>2 infections by providing q medical treatments.
Each treatment costs $3. The NGO aims to maxi-
mize its surplus, which is defined as

Surplus1q2 = 172q1>22 – 13q2
a. Determine the surplus-maximizing number of

treatments, q*, that the NGO should provide.
b. How many infections do the NGO’s efforts pre-

vent when it provides q* treatments?

A1.2 You are a manager of Moose’s Munchies, a hamburger
restaurant. The price of hamburgers is $5 per ham-
burger, and Moose’s Munchies incurs a total cost of

TC1Q2 = 0.01Q2 – 25
when it produces Q hamburgers.

a. Moose’s Munchies’ total benefit is its total reve-
nue, which equals the price multiplied by the
quantity of hamburgers, P * Q. What is Moose’s
Munchies’ marginal benefit of producing and
selling each additional hamburger?

b. What is Moose’s Munchies’ marginal cost of pro-
ducing and selling each additional hamburger?

c. Determine the profit-maximizing number of
hamburgers, Q*, that Moose’s Munchies should
produce and sell.

A1.3 Belinda’s Berries is a berry farm located just outside
of town. All the locals know Belinda’s farm pro-
duces some of the best berries around. Belinda uses

costly fertilizer on her land to increase its yield.
Belinda’s berry production is q = 27f 1>2, where f is
the bags of fertilizer she uses and q is the pounds of
berries she produces. Each pound of berries sells for
$2, and each bag of fertilizer costs $3. Belinda aims
to maximize her farm’s surplus, which is equal to

Surplus1f2 = 154f 1>22 – 13f2
a. What is the surplus-maximizing number of

bags of fertilizer, f *, that Belinda should apply?
b. How many pounds of berries, q*, does Belin-

da’s Berries produce when Belinda uses f * bags
of fertilizer?

c. Belinda’s total revenue equals the price multi-
plied by the quantity of berries, P * q. When
Belinda’s Berries applies the quantity of bags of
fertilizer that maximizes its surplus, f *, and
sells the resulting quantity of berries, q *, how
much total revenue does Belinda receive?

A1.4 Security at sporting events is very important, but it
is also costly. Scott’s Security has the contract to
provide security at a high school football game this
Friday. Scott must determine how many security
personnel he should schedule for that night. He is
attempting to maximize his surplus, which equals
the level of security, measured on a 1-to-100 scale,
minus his cost of scheduling security personnel.
The security level, SEC, is equal to

SEC1x2 =
1100×2 – 202
1×2 + 42

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where x is the number of security personnel. Scott
pays each of his employees $8.40 per game that they
work, so Scott’s total cost is 8.40x. Scott’s total surplus
equals the level of security minus his total cost, or

Surplus1x2 =
1100×2 – 202
1×2 + 42

– 8.40x

a. What is the surplus-maximizing number of
security personnel, x*, that Scott should hire for
this Friday’s game?

b. When Scott hires the surplus-maximizing
number of security personnel, x*, what level of
security does Scott provide, measured on the
1-to-100 scale?

A1.5 You are a manager of Kelly’s Koffie, a local coffee
shop that produces the best iced lattes around. The

price of an iced latte is $4, so Kelly’s Koffie’s total
revenue is

TR1Q2 = 4Q
when it produces Q iced lattes. Kelly’s Koffie incurs

a total cost of

TC1Q2 = 0.01Q2 + 2Q
Kelly’s Koffie’s total profit equals total revenue

minus total cost.
a. What is Kelly’s Koffie’s marginal benefit of pro-

ducing and selling each additional iced latte?
b. What is Kelly’s Koffie’s marginal cost of pro-

ducing and selling each additional iced latte?
c. What is the profit-maximizing number of iced

lattes, Q*, that Kelly’s Koffie should produce
and sell?

32  CHAPTER 1 APPENDIX The Calculus of Marginal Analysis

M01_BLAI8235_01_SE_C01_pp001-032.indd 32 23/08/17 9:48 AM

 33

Introduction
Like all other consumers, you use markets to purchase goods such as coffee, smart-
phones, and jeans and services such as those provided by attorneys, accountants,
and hairdressers. Economists define a market as any arrangement that allows buy-
ers and sellers to transact their business. Markets can range from competitive to
concentrated. Competitive markets, such as the market for cotton, have so many
buyers and sellers that no one buyer or seller can affect the price charged for a

Market Any arrangement
that allows buyers and
sellers to transact their
business.

2Demand and Supply
Learning Objectives
After studying this chapter, you will be able to:

2.1 Describe the factors that affect the demand for goods and services.
2.2 Describe the factors that affect the supply of goods and services.
2.3 Determine the market equilibrium price and quantity using the demand and supply

model.
2.4 Explain why perfectly competitive markets are socially optimal.
2.5 Use the demand and supply model to predict how changes in the market affect the price

and quantity of a good or service.
2.6 Explain the effects of price ceilings and price floors.
2.7 Apply the demand and supply model to make better managerial decisions.

C
H

A
P

T
E

R

Managers at Red Lobster Cope with Early Mortality Syndrome

Red Lobster is one of the world’s largest casual dining companies, operating over 700 restaurant locations
worldwide that specialize in seafood. From 2009 to 2013,
Red Lobster’s managers faced a significant problem: Shrimp
in Asia suffered from a bacterial infection called early mortal-
ity syndrome (EMS). EMS poses no health risk to humans,
but it is deadly to shrimp, killing them before they mature
and reproduce. Shrimp is one of Red Lobster’s major ingre-
dients, and the company sources the majority of its shrimp
from Asia. How could the company’s managers predict what
would happen to the price they paid their suppliers for the
shrimp and the quantity they would be able to buy?

Successful managers are aware of how markets
respond to changes, and they react in ways that help their
organization reach its goal. Red Lobster’s issue with EMS
is one dramatic example. This chapter will demonstrate
how you can use the demand and supply model to predict
changes in the price and quantity of goods and services
that affect your firm. At the end of this chapter, we’ll apply
this model to evaluate how Red Lobster’s managers dealt
with the EMS challenge and how their actions boosted
Red Lobster’s profit.

Sources: John McDuling, “Shrimp Inflation Is Killing Red Lobster,” Quartz, February 10, 2014; Kristen Reed and
Sharon Royales, “Shrimp Disease in Asia Resulting in High U.S Import Prices,” Bureau of Labor Statistics, June
2014 https://qz.com/175438/shrimp-inflation-is-killing-red-lobster/; Nopparat Chaichalearmmongkol and Julie Jargon,
“Disease Kills Shrimp Output, Pushes U.S. Prices Higher,” Wall Street Journal, July 12, 2013 https://www.bls
.gov/opub/btn/volume-3/shrimp-disease-in-asia-resulting-in-high-us-import-prices.htm.

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34  CHAPTER 2 Demand and Supply

product. Concentrated markets, such as the market for soda dominated by The
Coca-Cola Company and PepsiCo, have so few sellers that these sellers have sig-
nificant influence on price. This chapter covers the factors that determine the
price and quantity in competitive markets. Later chapters deal with firm-level
managerial decisions in competitive markets (Chapter 5) and in concentrated
markets (Chapters 6, 7, 8, and 10).

In a competitive market, the interactions between the buyers (the demanders) and
the sellers (the suppliers) determine the price and quantity of the good or service. The
demand and supply model is the most powerful tool economists have developed for
understanding how changes within a competitive market affect price and quantity.
The model provides insight into market responses to changes in factors such as
income, technology, and costs. Understanding the demand and supply model will
help you make better, more profitable decisions.

To appreciate how demand and supply determine the price and quantity of a
good or service, you must understand the factors that motivate buyers and sellers.
Countless idiosyncratic reasons motivate individuals to buy or sell. For instance,
you might decide to buy a pizza tonight because you worked late and would rather
spend your time studying managerial economics than cooking dinner. Managers,
however, are not interested in factors that influence only a few people because they
have no discernible effect on price and quantity. Managers need to understand the
factors that affect the vast majority of demanders or suppliers because they cause
changes in price and quantity. To help you understand and use the demand and sup-
ply model, Chapter 2 includes seven sections:

• Section 2.1 explores the key factors that affect the demand for a good or service.
• Section 2.2 explains the key factors that affect the supply of a good or service.
• Section 2.3 combines the separate analyses of demand and supply to explain how they

jointly determine the equilibrium price and equilibrium quantity of a good or service.
• Section 2.4 describes how perfectly competitive markets can be optimal for society.
• Section 2.5 shows how to determine the effect of changes in demand and supply on the

price and quantity of goods and services.
• Section 2.6 explains the consequences of government price controls that limit the

maximum or minimum price within a market.
• Section 2.7 applies the demand and supply model to show you how to make better

managerial decisions.

2.1 Demand
Learning Objective 2.1 Describe the factors that affect the demand for goods
and services.

Millions of different goods and services, including food, clothing, physical therapy,
legal services, and haircuts, are bought and sold in markets. Individual consumers
are the demanders in these markets, so you need to consider the factors that affect
their demands for a good or service.

Law of Demand
Price is an important factor that influences the quantity of a good or service demand-
ers are willing and able to buy during a given time period. The law of demand sum-
marizes how the price of the good or service affects the quantity that buyers will

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2.1 Demand  35

purchase: All other things remaining the same, the higher the price of the good or
service, the smaller the quantity demanded; the lower the price of the good or ser-
vice, the larger the quantity demanded.

• All other things remaining the same, the higher the price of the good or ser-
vice, the smaller the quantity demanded; the lower the price of the good or
service, the larger the quantity demanded.

LAW OF DEMAND

1 For a few products, a fall in income from the rise in the price increases the amount purchased. Intercity
bus travel is an example. For these goods, in theory the income effect might be large enough that a rise in
price increases the quantity demanded. In the real world, however, the income effect is never this large, so
invariably a higher price decreases the quantity demanded.

A change in the price of a good or service changes the quantity demanded through
two distinct channels: the substitution effect and the income effect. The substitution
effect refers to the fact that when the price of a good or service changes, its price com-
pared to the prices of other substitute goods or services changes. So, when the price
of jeans rises, some consumers will decide to switch to cargo pants or denim skirts
instead of buying the now-more-expensive jeans. As consumers make these substitu-
tions, the quantity of jeans demanded decreases. Alternatively, when the price of
jeans falls, some consumers will switch from denim skirts or cargo pants to the
now-less-expensive jeans, increasing the quantity of jeans demanded.

The income effect refers to the fact that when the price of a good or service changes,
consumers’ purchasing power changes. Continuing the jeans example, a rise in the price
of jeans means that consumers have less income left over after they buy them. With less
income, consumers must decrease their purchases. Some of that decrease is likely to be
decreased purchases of additional jeans.1 If the price of jeans falls, on the other hand,
consumers’ purchasing power increases. With more income left over after buying jeans,
consumers purchase more products, probably including more jeans.

The income effect and the substitution effect combine to create the law of
demand, which, as noted above, states that, other things remaining the same, a
higher price decreases the quantity demanded and a lower price increases the quan-
tity demanded.

Demand Curve
A demand curve shows how consumers respond to a change in the price of the prod-
uct. More formally, a demand curve is a curve that shows the relationship between
the price of a good or service and the quantity demanded.

Figure 2.1 illustrates a hypothetical demand curve, D, for jeans. This demand
curve shows the quantity of jeans consumers will buy at different prices.

The demand curve shown in Figure 2.1 is linear, but demand curves do not have
to be straight lines. The important feature of a demand curve is its negative slope,
which shows how consumers respond to a change in the price of the product. If the
price of a pair of jeans rises from $60 to $80, there is a movement along the demand
curve from point A to point B. The quantity of jeans demanded decreases from
300 million to 200 million pairs per year. When the price changes so there is a move-
ment along the demand curve, there is a change in the quantity demanded. If the price

Substitution effect When
the price of a good or
service changes, its price
compared to the prices of
other substitute goods or
services changes.

Income effect When the
price of a good or service
changes, buyers’
purchasing power
changes.

Demand curve A curve
that shows the relationship
between the price of a
good or service and the
quantity demanded.

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36  CHAPTER 2 Demand and Supply

rises, so the movement is upward along the demand curve, the quantity demanded
decreases. If the price falls, so the movement is downward along the demand curve,
the quantity demanded increases. These changes are consistent with the law of
demand: When the price rises, the quantity demanded decreases, and when the
price falls, the quantity demanded increases.

Demand curves have two interpretations. For example, point A shows the
following:

1. If a pair of jeans sells for a price of $60, consumers will buy 300 million pairs.
This interpretation is useful in this chapter because it enables you to determine
how the quantity consumers buy changes as different factors influencing the
demand change.

2. The highest price consumers are willing to pay for the 300 millionth pair of jeans is
$60. This interpretation can prove powerful for managers who are trying to set the
highest prices their customers are willing to pay, a topic covered in Chapter 10.

The Demand Function
It is also possible to represent demand algebraically using a demand function. A
demand function is an algebraic expression showing how the quantity demanded
depends on relevant variables.

Assuming that the only factor affecting the quantity demanded is the price of the
product, the general demand function is

Qd = f1P2 2.1
where Qd is the quantity demanded of the product, f is the demand function, and P
is the price of the product. Equation 2.1 shows a general function. If the demand
curve is linear, the demand function is

Qd = a – 1b * P2

Figure 2.1 A Demand Curve

The demand curve for
jeans, D, shows the
quantity of jeans
demanded at all different
prices. The slope of the
demand curve reflects the
law of demand: As the
price rises, the quantity of
jeans demanded decreases.
When the price rises from
$60 to $80, there is a
movement up along the
demand curve from point A
to point B. The quantity
demanded decreases from
300 million to 200 million
pairs of jeans.

Price (dollars per pair of jeans)

Quantity (millions of pairs of jeans per year)

$140

$20

$40

700600500400300200100

$60

$80

$100

$120

0

D

B

A

Demand function An
algebraic expression
showing how the quantity
demanded depends on
relevant variables.

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2.1 Demand  37

As before, Qd is the quantity demanded, and P is the price. Both a and b are coeffi-
cients. The value of a is the quantity of the product demanded when the price is $0,
and the value of b is the change in the quantity of the product demanded when the
price changes by $1. The negative sign in the equation reflects the law of demand,
showing that an increase in the price decreases the quantity demanded.

Analysts frequently use regression analysis, a statistical tool explained in
Chapter 3, to estimate the values of a and b. You can determine the coefficients of the
linear demand curve illustrated in Figure 2.1 more simply. The value of a is the quan-
tity of jeans demanded if the price is $0, so a equals 600 million pairs of jeans per
year. The value of b is the change in the quantity of jeans demanded when the price
changes by $1, so b equals 5 million pairs of jeans per dollar.2 This value for b means
that if the price of a pair of jeans rises by $1, the quantity of jeans demanded
decreases by 5 million pairs. Accordingly, the demand function for the demand
curve in Figure 2.1 is

Qd = 600 million – 15 million * P2
In any mathematical function, the variable on the left of the equation is the

dependent variable, and the one or more variables on the right are the independent vari-
ables. The dependent variable responds to changes in the independent variables. In a
demand equation, the quantity demanded responds to changes in price, making
quantity the dependent variable and price the independent variable. Typically, math-
ematicians plot equations with the dependent variable on the vertical axis and the
independent variable on the horizontal axis. For historical reasons, economists flout
that convention by plotting the dependent variable, Qd, on the horizontal axis and
the independent variable, P, on the vertical axis.

Price is not the only factor that affects consumers’ demand for a good or service.
For example, consumers’ income plays a role in determining the quantity of jeans
they will buy. The next section presents the effect of income and other factors that
influence demand.

Factors That Change Demand
You have seen how consumers’ responses to a change in the price of a product affect
the quantity they buy and lead to a movement along the product’s demand curve.
Of course, other factors also affect consumers’ demand for the good or service. These
include consumers’ income, the price of related goods and services, consumers’ pref-
erences and advertising, financial market conditions, the expected future price of the
product, and the number of demanders. A change in any of these factors changes the
demand for the product and, as you will see, causes the demand curve to shift.

Consumers’ Income
Changes in Income One very important factor that affects consumers’ demand
for almost all goods and services is income.3 If consumers’ incomes increase, they

2 Because the demand curve is linear, the value of b is the same at all points along it, so you can calculate
the value of b between any two points on the demand curve. Consequently, between points A and B on
the demand curve, the price rises by $20 per pair of jeans (from $60 to $80), and the quantity demanded
decreases by 100 million pairs (from 300 million to 200 million pairs). Between these points, b equals (100
million pairs of jeans)/($20 per pair of jeans,) or 5 million pairs of jeans per dollar.
3 This factor is different from the income effect, covered earlier, because the income effect results from a
change in the product’s price, not a change in consumers’ income.

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38  CHAPTER 2 Demand and Supply

can and will want to buy more of many products, including jeans. In this case, the
quantity of jeans demanded at every price increases. Figure 2.2 illustrates how a
change in income affects the demand curve. Demand curve D0 is the initial demand
curve when people’s incomes are lower, and demand curve D1 is the demand curve
when people’s incomes are higher, perhaps as a result of strong economic growth.
Before the change in income, point B shows that consumers demanded 200 mil-
lion pairs of jeans at the price of $80 per pair. After the increase in income, at the
price of $80, point C shows that consumers have increased the quantity of jeans they
demand from 200 million to 400 million pairs per year. Figure 2.2 illustrates that
the quantity demanded increases at all prices, not just at the price of $80 per pair of
jeans. This fact causes the entire demand curve to shift to the right. The shift is called
a change in demand. In the case of jeans and income, the increase in income leads to
an increase in demand.

Similarly, a decrease in the quantity demanded at all prices causes a leftward
shift of the demand curve. In our example, a decrease in income leads to a decrease
in demand for jeans.

Shift of the Demand Curve Versus a Movement Along the Demand Curve As
you have just learned, a change in income affects the demand curve differently than
does a change in price. Figure 2.1 shows that a change in price results in a movement
along the demand curve, and Figure 2.2 shows that a change in income results in a
shift of the demand curve. The change in price illustrated in Figure 2.1 leads to a
change in the quantity demanded, and the change in income illustrated in Figure 2.2
leads to a change in demand. This distinction is important. The only factor that cre-
ates a movement along the demand curve and changes the quantity demanded is
the price of the product itself. All of the other factors that affect demand, including
income, shift the demand curve and change the demand.

Although income is not the only factor that can change the demand and shift the
demand curve for a good or service, it is an important one. Before examining the
other factors, let’s take a closer look at the effects of a change in income.

Price (dollars per pair of jeans)

Quantity (millions of pairs of jeans per year)

$140

$20

$40

700600500400300200100

$60

$80

$100

$120

0

D1

B C

D0

The increase in
income shifts the
demand curve to
the right.

Figure 2.2 A Shift of the Demand Curve

The figure shows a change in the demand for
jeans. The entire demand curve has shifted to
the right, from D0 to D1. A rightward shift of the
demand curve represents an increase in
demand. At all prices, the quantity of jeans
demanded has increased.

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2.1 Demand  39

Normal and Inferior Goods and Services Returning to the jeans example, you have
seen that an increase in income increases the demand for jeans and shifts the demand
curve to the right. For some other goods and services, an increase in income decreases
the demand and shifts the demand curve to the left. For example, an increase in income
decreases the demand for intercity bus travel because people with more income can
afford to rent or buy a car or even fly to their destinations.

These two different relationships between income and demand mean that goods
and services fall into two categories: normal and inferior. When an increase in
income increases the demand for a good or service and a decrease in income
decreases that demand, the good or service is a normal good or service. As described
earlier, a pair of jeans is an example of a normal good. So, too, is dining at Red Lobster.
The majority of goods and services are normal. In contrast, when an increase in
income decreases the demand for a good or service and a decrease in income
increases that demand, the good or service is an inferior good or service. Used
clothing and boxed mac and cheese are examples of inferior goods. It is important to
note that the term inferior does not imply low quality. It refers only to the relation-
ship between income and demand. In fact, depending on the income range, some
goods can be both normal and inferior. For example, in lower income ranges, ground
beef is a normal good—when the incomes of lower-income consumers rise, they
demand more ground beef and fewer hot dogs or noodles. In higher income ranges,
however, ground beef is an inferior good—when the incomes of middle-income con-
sumers rise, they demand less ground beef and more roasts and steaks.

Price of Related Goods and Services: Substitutes and Complements
Another factor that changes the demand and shifts the demand curve is the rela-
tionship some goods and services have with other products. These relationships
are of two types: substitutes and complements. Substitutes are alternative goods
and services—a consumer buys one or the other. For example, if you are looking
to buy a smartphone, you might choose an Apple iPhone or a Samsung Galaxy.
Complements are separate goods and services that a consumer buys to use
together—a consumer buys one and the other. For example, when purchased in a
grocery store, hot dogs and hot dog buns are complements.

If the price of a substitute rises, the demand for the good in question increases,
shifting its demand curve to the right. The reverse is also true: If the price of a substi-
tute falls, the demand for the good in question decreases, and its demand curve shifts
to the left. For example, chicken and beef are substitutes. You might have one or the
other for dinner. Consider the demand for chicken. If the price of beef rises, consumers
substitute chicken, increasing the demand for chicken and shifting the demand curve
for chicken to the right. If the price of beef falls, consumers will buy more beef and less
chicken, so the demand for chicken decreases, shifting its demand curve to the left.
Keep in mind that in both cases the change in the price of beef creates a movement along
the demand curve for beef but shifts the demand curve for the substitute, chicken.

If the price of a complement rises, the demand for the good in question decreases,
and its demand curve shifts to the left. Of course, the reverse also is true: If the price of a
complement falls, the demand for the good in question increases, and its demand curve
shifts to the right. Think of the demand for bicycle helmets. Bicycles and bicycle helmets
are complements. If the price of a bicycle rises, fewer people buy bicycles, decreasing
the demand for bicycle helmets and shifting the demand curve for bicycle helmets to
the left. Alternatively, if the price of a bicycle falls, then the demand for bicycle helmets
increases, and the demand curve for bicycle helmets shifts to the right. Once again,
remember that the change in the price of a bicycle creates a movement along the demand
curve for bicycles but shifts the demand curve for the complement, bicycle helmets.

Normal good or service A
good or service for which
an increase in income
increases demand and a
decrease in income
decreases demand.

Inferior good or service A
good or service for which
an increase in income
decreases demand and a
decrease in income
increases demand.

Substitutes Alternative
goods and services; a
consumer buys one or the
other.

Complements Separate
goods and services
purchased for use
together; a consumer buys
one and the other.

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40  CHAPTER 2 Demand and Supply

Consumers’ Preferences and Advertising
Economists refer to people’s likes or dislikes for products as their preferences.
Changes in preferences change demand. If preferences change and consumers like a
good more than before, then demand increases, and the demand curve shifts to the
right. Conversely, if preferences change and consumers like a good less, then demand
decreases, and the demand curve shifts to the left.

What factors can lead to changes in preferences? The most relevant for managers
is advertising. The goal of most advertising campaigns is to increase people’s prefer-
ences for a product, thereby increasing demand. Watch an evening of network televi-
sion or spend a few hours on the Internet and you will see almost too many
advertisements to count. Not only individual firms but also some industries advertise.
The National Milk Processor Education Program’s slogan “Got milk?” tried to change
consumers’ preferences in favor of drinking milk to increase the demand for milk.
(Chapter 13 examines such industry-wide promotions in more detail.) Of course, not
all advertising tries to increase demand. For example, many states use funds from the
1998 Tobacco Master Settlement Agreement to run advertisements designed to dis-
courage smoking and decrease the demand for cigarettes.4 Nonprofits also advertise,
though often to promote donations rather than increase demand for a product.

New information can lead to changes in preferences. Sometimes this informa-
tion might come from advertisements, as when Apple advertised its then-innovative
new product, the iPad. Other times the information might come from news reports,
as when they spread the information over the past couple of decades that salmon
contains oils that are heart healthy. Regardless of the source, as the information
becomes more widespread, consumers’ preferences may change, thereby changing
the demand for the product and shifting its demand curve.

Financial Market Conditions
The ability of individuals and firms to obtain loans in financial markets, such as the mar-
ket for bank loans or the bond market, affects the demand for some goods. Most people
need to obtain a loan to purchase big ticket items such as cars and homes. Similarly,
most firms need to borrow to help finance their purchase of capital goods, as when
Brinker International Restaurants purchased new kitchens for all of its Chili’s restau-
rants. Financial market conditions affect the demand for these types of products. With
good financial market conditions—when the interest rates on loans are low and finan-
cial institutions’ lending standards are easy to meet—the demand for the goods pur-
chased with the help of these loans is high. With bad financial market conditions—when
it is difficult to obtain even a high-interest-rate loan—the demand for these goods is low.

Of course, financial market conditions have little to no effect on the demand for
many goods. No one thinks about taking out a loan to buy a slice of pizza. But for the
expensive goods that typically require a loan, financial market conditions can play a
crucial role in demand. In the recession of 2007–2009, home mortgage loans became
significantly more difficult to obtain. The demand for homes decreased so much that
the number of homes purchased was about 25 percent lower in 2008 than in 2005.

Expected Future Price
Changes in the expected future price of a good or service can change its current demand.
For example, managers of refineries demand oil to refine into gasoline, fuel oil, and
other products. If they think that turmoil in the Middle East will lead to higher crude oil

4 The Tobacco Master Settlement Agreement is a legal settlement agreement between the four major
tobacco companies and 46 states that sued the companies to recover tobacco-related health-care costs.

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2.1 Demand  41

prices in the future, the current demand for crude oil increases as these demanders try
to buy before the price rises. Conversely, if the refinery managers expect the future price
of crude oil to fall, the current demand for crude oil decreases as these demanders delay
buying crude oil until they can take advantage of the lower price. Of course, this factor
does not affect the demand for all goods and services equally. It is stronger for durable
goods, such as oil, than for nondurable goods, such as fresh fish, because demanders
can more easily accelerate or delay their purchases of durable goods.

Number of Demanders
A change in the number of demanders—the number of consumers or companies
purchasing a good or service—changes demand and shifts the demand curve. An
increase in the number of demanders increases demand and shifts the demand curve
to the right. A decrease in the number of demanders decreases demand and shifts
the demand curve to the left.

Demographic changes can lead to changes in the number of demanders. For
example, older people use more pharmaceutical drugs than do younger people. As
the average age in the population increases, the demand for pharmaceutical drugs
increases, and the demand curve for pharmaceutical drugs shifts to the right.

Seasonal changes can also trigger changes in the number of demanders. The
approach of fall and winter decreases the number of people who want to barbecue
outdoors. So at the end of summer, the demand for barbecue grills decreases, and
the demand curve for barbecue grills shifts to the left.

Changes in Demand: Demand Function
The basic demand function you saw earlier in the chapter assumed that demand
depends only on the price. Including the other factors just presented makes the
demand function more complex and more realistic. For now, let’s focus on including
just two additional factors, but know that you can incorporate other factors using a

Suppose that you are a manager at General Motors. The Cadillac Escalade is a
full-size, luxury SUV produced by your firm that gets fewer miles per gallon of
gasoline than other cars. During the recession of 2007–2009, people’s incomes
plunged, it became very difficult to obtain loans, and the price of gasoline soared.
What was the effect of these changes on the demand for the Escalade?

Answer
Three factors changed: (1) Income fell, (2) loans became difficult to obtain, and
(3) the price of gasoline soared. Start by looking at each effect separately. The
Escalade is a normal good, so the fall in income decreased the demand for
Escalades. The Escalade is also an expensive car, so the difficulty in obtaining
loans decreased the demand. Finally, gasoline and automobiles are complements,
so the higher price of gasoline decreased the demand for the Escalade. Individu-
ally, each factor decreased the demand for Escalades, so combining them means
that the demand for Escalades definitely decreased.

DECISION
SNAPSHOT Demand for the Cadillac Escalade

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42  CHAPTER 2 Demand and Supply

similar process. Assume that the demand for jeans depends on their price, on the
price of denim skirts (a substitute good), and on consumers’ average income. The
equation for this more elaborate demand function is

Qd = f1P, PSKIRTS, INCOME2 2.2
where Qd is the quantity demanded, f is the demand function, P is the price of jeans,
PSKIRTS is the price of the substitute good, and INCOME is consumers’ average
income. The function in Equation 2.2 could literally be almost anything. However, if
it is linear, it can be written as

Qd = a – 1b * P2 + 1c * PSKIRTS2 + 1d * INCOME2 2.3
In Equation 2.3, a, b, c, and d are coefficients. The meanings of the coefficients a and b are
similar to before. For example, b is the change in the quantity of jeans demanded when
the price changes by $1. The value of c is the change in the quantity of jeans demanded
when the price of the substitute (denim skirts) changes by $1. Because skirts are a sub-
stitute for jeans, there is a positive sign preceding the 1c * PSKIRTS2 term, showing that
a $1 rise in the price of a denim skirt increases the demand for jeans. The value of d is
the change in the quantity of jeans demanded when average income changes by $1.
Because jeans are a normal good, an increase in average income increases the demand
for jeans, so the sign preceding the 1d * INCOME2 term is positive.

Price (dollars per pair of jeans)

Quantity (millions of
pairs of jeans per year)

$120

$140

$20

500 600 700300 400100 200

$40

$60

$80

$100

0

D1
D0

Price (dollars per pair of jeans)

Quantity (millions of
pairs of jeans per year)

$120

$140

$20

500 600 700300 400100 200

$40

$60

$80

$100

0

D0
D1

Figure 2.3 Changes in Demand

(a) An Increase in Demand (b) A Decrease in Demand

Demand increases and the demand curve shifts to the
right when

• Income increases (for a normal good).
• Income decreases (for an inferior good).
• The price of a substitute rises.
• The price of a complement falls.
• Preferences change toward the good.
• Financial market conditions are good.
• The expected future price rises.
• The number of demanders increases.

Demand decreases and the demand curve shifts to the
left when

• Income decreases (for a normal good).
• Income increases (for an inferior good).
• The price of a substitute falls.
• The price of a complement rises.
• Preferences change away from the good.
• Financial market conditions are bad.
• The expected future price falls.
• The number of demanders decreases.

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2.1 Demand  43

Demand for Lobster Dinners

You are a manager at Lobster Brisk, a seafood restaurant chain similar to Red Lobster.
Your supervisor asks you to determine the quantity of lobster to buy for the chain’s
Brisk Feast, an annual month-long promotion when Lobster Brisk features a variety of
lobster dinners, including its signature lobster bisque soup. Your research department
reports that the demand for lobster dinners is

Qd = 1,300,000 dinners – 1100,000 dinners * P2 + 132 dinners * INCOME2
where Qd is the quantity of lobster dinners demanded per week, P is the price of a lob-
ster dinner, and INCOME is the average family income of Lobster Brisk customers.

a. If the average family income of Lobster Brisk customers is $40,000 and you set the
price of a lobster dinner at $18 per dinner, what is the quantity of dinners demanded?

b. If you raise the price of a lobster dinner from $18 to $20 and the average family
income remains equal to $40,000, what is the change in the quantity of dinners
demanded? Is there a movement along the demand curve or a shift of the curve?

c. With the price of a lobster dinner set at $20, what is the change in the quantity of
dinners demanded if your advertising brings in families with an average income of
$42,000 rather than $40,000? Is there a movement along the demand curve, or does
the curve shift?

Answer

a. The demand function shows that the quantity of lobster dinners demanded
equals 1,300,000 dinners – 1100,000 dinners * $182 + 132 dinners * $40,0002 =
780,000 dinners.

b. The coefficient for the price variable, 100,000 dinners per dollar, shows that a $2
increase in the price of a lobster dinner decreases the quantity demanded by
100,000 dinners * 2, or 200,000 dinners per week. The increase in price leads to an
upward movement along the demand curve.

c. The coefficient for the income variable, 32 dinners per dollar, shows that a $2,000
increase in the customers’ average income increases the quantity demanded by
32 dinners * $2,000, or 64,000 dinners per week. The increase in income leads to a
rightward shift of the demand curve equal to 64,000 dinners.

SOLVED
PROBLEM

The coefficients c and d affect the amount by which the demand curve shifts when
the price of denim skirts and average income change, respectively. For example, if the
coefficient d is equal to 200,000 pairs of jeans per dollar of income, then a $1,000
increase in average income shifts the demand curve to the right by 200,000 pairs * 1,000,
or 200 million pairs, precisely the shift illustrated in Figure 2.2. Of course, in reality,
no one simply hands you the values for the coefficients; analysts must estimate the
values, often using regression analysis, which is explained in Chapter 3.

Figure 2.3 summarizes how the six factors discussed in this section—consumers’
income, the price of related goods and services, consumers’ preferences and adver-
tising, financial market conditions, the expected future price of the product, and the
number of demanders—change the demand and shift the demand curve. The fol-
lowing section explores the other side of the market—supply.

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44  CHAPTER 2 Demand and Supply

2.2 Supply
Learning Objective 2.2 Describe the factors that affect the supply of goods
and services.

In markets for goods and services, firms are the suppliers. The primary factor influ-
encing supply decisions is profit. Chapter 5 provides more detail about the effect of
the pursuit of profit on firms’ behavior. In this chapter, assume that the larger the
profit from producing a good or service, the more of the good or service the firms
will produce. Conversely, the smaller the profit from producing a good or service,
the less of the good or service the firms will produce.

Law of Supply
The price of a good or service is a very important factor affecting firms’ profits. If the
price rises and nothing else changes, the profit from producing the good or service
will be larger, so firms will produce more in a given time period. Alternatively, the
lower the price, the smaller the profit and the less firms will produce. The law of
supply summarizes these insights: All other things remaining the same, the higher
the price of the good or service, the larger the quantity supplied; the lower the price
of the good or service, the smaller the quantity supplied.

5 These results are analogous to what you saw for the demand curve: A change in the price of the prod-
uct creates a movement along the demand curve, called a change in the quantity demanded.

• All other things remaining the same, the higher the price of the good or service,
the larger the quantity supplied; the lower the price of the good or service, the
smaller the quantity supplied.

LAW OF SUPPLY

Supply Curve
A supply curve illustrates the relationship between the price of a good or service
and the quantity supplied.

Figure 2.4 illustrates a supply curve for jeans that shows the quantity of jeans
suppliers will produce at different prices. At a price of $60 per pair, point A on the
supply curve shows that the quantity of jeans produced is 300 million pairs per year.
If the price rises to $80 per pair, point B on the supply curve shows that the quantity
of jeans supplied increases to 400 million pairs per year. The supply curve in
Figure 2.4 is linear, but like demand curves, supply curves are not necessarily
straight lines. What is crucial is the positive slope of the supply curve, which reflects
the law of supply: When the price rises, the quantity supplied increases, and when
the price falls, the quantity supplied decreases.

A change in the price of the product causes a movement along the supply curve,
which is called a change in the quantity supplied.5 If the price rises, the quantity supplied
increases, leading to the movement upward along the supply curve illustrated by the
arrow in Figure 2.4 between points A and B. If the price falls, the quantity supplied
decreases, resulting in a movement downward along the supply curve.

Supply curve A curve
illustrating the relationship
between the price of a
good or service and the
quantity supplied.

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2.2 Supply  45

The Supply Function
Supply can be represented using an algebraic function called the supply function just
as demand was represented using the demand function. Suppose that the only factor
affecting supply is the price of the product. In this case, the general supply function is

Qs = g1P2 2.4
where Qs is the quantity supplied, g is the supply function, and P is the price of the
product. Equation 2.4 shows a general function. If the supply curve is linear, the sup-
ply function is

Qs = r + 1s * P2 2.5
where Qs is the quantity supplied, P is the price of the product, and r and s are coef-
ficients. The value of r is the quantity supplied if the price is $0, and the value of s is
the change in the quantity supplied when the price changes by $1. The positive sign
in the equation before the 1s * P2 term reflects the law of supply: An increase in the
price increases the quantity supplied.

You can use Equation 2.5 to determine the coefficients of the supply function for
the linear supply curve illustrated in Figure 2.4. As Figure 2.4 shows, when the price is
$0, the quantity of jeans supplied is 0, so r equals 0. The value of s is the change in the
quantity of jeans supplied when the price changes by $1, so s equals 5 million pairs of
jeans per dollar.6 This value for s means that if the price of jeans rises by $1, the quan-
tity supplied increases by 5 million pairs. Therefore, the supply function for the supply
curve shown in Figure 2.4 is

Qs = 0 + 15 million * P2

Price (dollars per pair of jeans)

Quantity (millions of pairs of jeans per year)

$140

$20

$40

700600500400300200100

$60

$80

$100

$120

0

S

B

A

Figure 2.4 A Supply Curve

The supply curve for jeans, S, shows the quantity
supplied at all different prices. The slope of the
supply curve reflects the law of supply: As the
price of jeans rises, the quantity supplied
increases. When the price rises from $60 to $80
per pair, the arrow shows there is a movement
upward along the supply curve from point A to
point B, and the quantity of jeans supplied
increases from 300 million to 400 million pairs
per year.

6 As with the value of the coefficient b on a linear demand curve, the value of s is the same at every point
on a linear supply curve. Between points A and B on the supply curve in Figure 2.4, as the price of jeans
rises by $20 (from $60 to $80), the quantity of jeans supplied increases by 100 million pairs (from 300 mil-
lion to 400 million pairs). So between these two points, s equals (100 million pairs)/($20 per pair), or
5 million pairs per dollar.

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46  CHAPTER 2 Demand and Supply

As you may already have guessed, price is not the only thing that affects the
supply of a product. The next section examines the other factors that affect supply
and the supply curve.

Factors That Change Supply
A change in price creates a movement along the supply curve, but other factors that
affect supply shift the supply curve. These factors include cost, the price of related
goods and services, technology, the state of nature, the expected future price of the
product, and the number of suppliers. Of these six factors, the first five reflect firms’
profit-seeking behavior, while the last directly affects the amount of the product
available at each price.

Cost
One factor that affects the supply of all goods and services is the cost of producing
them. Cost and price differ: Cost is what the producers pay to produce the product,
and price is the amount the producers receive when they sell the product. When the
cost of producing a good or service rises and nothing else changes, the profit from
producing that good or service decreases. Firms respond to the fall in profit by
decreasing their production. For example, suppose that the cost of producing jeans
rises because of an increase in the price of the denim used in their manufacture. For
any given price, this increase in cost decreases the profit from jeans, so firms respond
by decreasing their production. In Figure 2.5, supply curve S0 is the initial supply
curve before the change in cost, and supply curve S1 is the supply curve after the cost
has increased. At the price of $80 per pair of jeans, before the rise in cost, firms supply
400 million pairs of jeans per year, point B on the initial supply curve, S0. After the
rise in cost, the quantity supplied at the price of $80 decreases to 200 million pairs of
jeans per year, point C on the new supply curve, S1. As Figure 2.5 shows, the quantity
supplied decreases at not only the price of $80 per pair of jeans but also at all prices,
so that the entire supply curve shifts to the left. The increase in cost leads to a
decrease in supply.

Similarly, if the cost of production falls, the profit from producing the good or
service rises. Firms respond to the higher profit by increasing their production of the
good or service, so the supply increases and the supply curve shifts to the right.

Shift of the Supply Curve Versus a Movement Along the Supply Curve As
was the case with the demand curve, the effect on the supply curve of a change
in the price of the product is significantly different from the effect of a change in
any other relevant factor, such as cost. Figure 2.4 illustrates that a change in price
results in a movement along the supply curve, while Figure 2.5 shows that a change
in cost results in a shift of the supply curve. The change in price illustrated in
Figure 2.4 leads to a change in the quantity supplied, and the change in cost illustrated
in Figure 2.5 leads to a change in supply. The only factor that creates a movement
along the supply curve (and a change in the quantity supplied) is the product’s
price. Changes in any of the other relevant factors shift the supply curve (and
change the supply).

Price of Related Goods: Substitutes in Production
and Complements in Production
Changes in the prices of related goods in production change the supply of a product
and shift its supply curve. There are two possible relationships between goods. Some

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2.2 Supply  47

products, called substitutes in production, are alternatives in production—a firm
can produce one or the other. For example, bakeries such as the Great Harvest Bread
Company can use their ovens to produce either white bread or wheat bread. For
Great Harvest Bread, these two goods are substitutes in production. Other products,
called complements in production, are produced simultaneously—a firm produces
one and the other. For example, when refineries such as those operated by Shell Oil
Company refine a barrel of oil, the refining process simultaneously produces gaso-
line, kerosene, and diesel fuel. For Shell Oil, gasoline, kerosene, and diesel fuel are
complements in production.7

For both substitutes in production and complements in production, the price of
the second product affects the supply of the first.

• Substitutes in production. If the price of a substitute in production rises, firms
switch production toward the substitute and away from the first product because
the substitute has become more profitable. The supply of the first product
decreases, and its supply curve shifts to the left. For example, if the price of
wheat bread rises, how does this change affect the supply of white bread? Great
Harvest Bread’s managers and managers of all bakeries use their ovens to pro-
duce more wheat bread and less white bread, decreasing the supply of white
bread and shifting the supply curve of white bread to the left. The reverse is also
true: If the price of a substitute in production falls, the supply of the first good
increases, and its supply curve shifts to the right.

• Complements in production. If the price of a complement in production rises,
firms produce more of the complement because it has become more profitable.

Substitutes in
production Products that
are alternatives in
production; a firm can
produce one or the other.

Complements in
production Products that
are produced
simultaneously; a firm
produces one and the
other.

Price (dollars per pair of jeans)

Quantity (millions of pairs of jeans per year)

$140

$20

$40

700600500400300200100

$60

$80

$100

$120

0

S0

S1

BC

The increase in
cost shifts the
supply curve
to the left.

Figure 2.5 A Shift in the
Supply Curve

The figure shows a
decrease in the supply of
jeans. The supply curve
shifts to the left, from S0
to S1. A leftward shift of
the supply curve represents
a decrease in supply
because the quantity of
jeans supplied decreases
at all prices.

7 Traditionally, economists call products that are substitutes or complements for consumers simply substi-
tutes or complements but refer to goods that are substitutes or complements for firms as substitutes in produc-
tion or complements in production.

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48  CHAPTER 2 Demand and Supply

When firms produce more of the complement, they also automatically produce
more of the first product. The supply of the first product increases, and its sup-
ply curve shifts to the right. For example, if the price of gasoline rises, how does
this change affect the supply of diesel fuel? The managers of Shell Oil’s refiner-
ies and the managers of all refineries produce more gasoline by refining more
oil. Because more oil is refined, the production of diesel fuel automatically
increases. The supply of diesel fuel increases, and the supply curve of diesel
fuel shifts to the right. Of course, if the price of a complement in production
falls, the supply of the first product also decreases, and its supply curve shifts
to the left.

Technology
Changes in technology affect the supply in many markets. Economists take a broad
view of technology by thinking of it as information that provides a recipe (or instruc-
tions) describing how to combine various inputs in order to produce the output. It is
common to view technology in terms of technological advances, the discovery of
improved methods of production of existing goods or services or even methods of
production of entirely new products or services. The automobile industry provides
examples of both types of technological advances:

• The installation of industrial robots to produce cars illustrates a new and
improved method of production.

• The introduction of hybrids or driverless automobiles illustrates the production
of new products.

In both cases, a technological advance increases the supply of a good or service and
shifts the supply curve to the right.

State of Nature
Although you might first think that the state of nature affects only the supply of
agricultural products, the concept is actually much broader. As a factor affecting
supply, the state of nature includes both the wide-scale flooding in China’s Yang-
tze River basin in the summer of 2016 that destroyed nearly 4 million acres of
crops and caused a total of $28 billion in damages, and the earthquake and result-
ing tsunami that devastated northern Japan in March 2011, severely damaging
many of Japan’s automobile factories. Floods, tsunamis, earthquakes, hurricanes,
and bad growing seasons are all examples of bad states of nature. Because these
events either increase the cost of producing the affected goods and services or
directly reduce the amount firms can produce, they decrease the supply of affected
goods and services and shift their supply curves to the left. Conversely, a good
state of nature—no flooding, an absence of tsunamis, fewer hurricanes than nor-
mal, a good growing season—increases the supply of the affected products and
shifts their supply curves to the right.

Expected Future Price
Changes in a good’s expected future price can change its current supply. For exam-
ple, Marathon Pipe Line owns six massive underground storage caverns for pro-
pane. If the future price of propane is expected to rise, Marathon and other propane
suppliers will delay selling propane today in order to take advantage of the higher
price (and larger profit) expected in the future. Consequently, the current supply of

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2.2 Supply  49

propane decreases, and the supply curve shifts to the left. Conversely, if the future
price of propane is expected to fall, the current supply of propane increases as
Marathon and the other suppliers rush to sell now before the price and profit fall
in the future. Of course, this factor does not affect the supply for all goods and ser-
vices equally. Goods that can be stored or that have production processes that can
easily be accelerated or delayed will have the strongest reaction to changes in the
expected future price.

Number of Suppliers
Of the factors that shift the supply curve, only a change in the number of suppli-
ers is not motivated by profit. A change in the number of suppliers directly
changes the amount of the product available at each price. When more firms enter
a market, the number of suppliers increases, which increases the supply and shifts
the supply curve to the right. When firms close or otherwise exit a market, the
number of suppliers decreases, which decreases the supply and shifts the supply
curve to the left.

Changes in Supply: Supply Function
The supply function presented in Equation 2.4 assumes that supply relies only on
the price of the product. Including other relevant factors from among the six just pre-
sented makes the supply function more realistic. For now, this discussion focuses on
just two additional factors, but as you will see shortly, you can add any of the others
using a similar process. So assume that the supply of jeans depends on their price,
the cost of producing each pair, and the number of firms producing jeans. In this
case, a general equation for the supply function is

Qs = g1P, COST, NUMBER2
where Qs is quantity of jeans produced, g is the supply function, P is the price of
jeans, COST is the cost of producing the jeans, and NUMBER is the number of sup-
pliers. You can extend the linear supply function shown in Equation 2.5 to include
the effects of the cost and number of firms:

Qs = r + 1s * P2 – 1t * COST2 + 1u * NUMBER2
The coefficients in the linear supply equation are r, s, t, and u. The meanings of the
r and s coefficients are the analogous to those in Equation 2.5. For example, the
value of s is the change in the quantity of jeans supplied when the price changes by
$1. The new coefficients are t and u. The value of t is the Change in
the quantity supplied when the cost of producing jeans changes by $1. The nega-
tive sign in the equation for the 1t * COST2 term indicates that an increase in cost
decreases the supply of jeans. The value of u is the change in the quantity of jeans
supplied when the number of firms changes by one. The 1u * NUMBER2 term
has a positive sign because an increase in the number of firms leads to an increase
in the supply.

These new coefficients determine how much the supply changes and how
much the supply curve shifts if there is a change in the cost or number of firms.
For example, if the coefficient t is equal to 100 million pairs of jeans per dollar of
cost, then a $2 increase in cost changes the supply by – 100 million * 2, or
– 200 million pairs. In this case, the supply curve shifts to the left by 200 million
pairs, precisely the shift illustrated in Figure 2.5.

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50  CHAPTER 2 Demand and Supply

Figure 2.6 summarizes the effects that the factors just discussed have on supply
and the supply curve. Now that you have learned about the concepts of demand and
supply separately, it’s time to discover how they interact to determine the quantity
and price of a good or service.

Price (dollars per pair of jeans)

Quantity (millions of
pairs of jeans per year)

$120

$140

$20

500 600 700300 400100 200

$40

$60

$80

$100

0

S 0

S 1

Price (dollars per pair of jeans)

Quantity (millions of
pairs of jeans per year)

$120

$140

$20

500 600 700300 400100 200

$40

$60

$80

$100

0

S 0
S 1

Figure 2.6 Changes in Supply

(a) An Increase in Supply (b) A Decrease in Supply
Supply increases and the supply curve shifts to the
right when

• Cost decreases.
• The price of a substitute in production falls.
• The price of a complement in production rises.
• Technology advances.
• The state of nature is good.
• The expected future price falls.
• The number of suppliers increases.

Supply decreases and the supply curve shifts to the
left when:

• Cost increases.
• The price of a substitute in production rises.
• The price of a complement in production falls.
• The state of nature is bad.
• The expected future price rises.
• The number of suppliers decreases.

The Supply of Gasoline-Powered Cars
and the Price of Hybrid Cars

Suppose that the supply function for gasoline-powered cars is

Qs = 7,800,000 cars + 1300 cars * P2 − 1200 cars * P HYBRID2
where Qs is the quantity of gasoline cars supplied, P is the price of a gasoline-powered
car, and PHYBRID is the price of a hybrid car. Suppose the price of a hybrid car is $39,000.

a. Are hybrids a complement in production or a substitute in production for gasoline-
powered cars?

b. Suppose the price of a gasoline-powered car is $30,000 and the price of a hybrid car
rises by $2,000. What is the effect on the supply curve of gasoline-powered cars?
Draw a figure showing the initial supply curve and the new supply curve after the
increase in the price of the hybrid.

SOLVED
PROBLEM

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2.3 Market Equilibrium  51

2.3 Market Equilibrium
Learning Objective 2.3 Determine the market equilibrium price and quantity
using the demand and supply model.

In competitive markets, the actions of buyers and sellers jointly determine the price
and quantity of a given good or service. As you have learned, the demand curve
reflects the behavior of buyers, and the supply curve reflects the behavior of sellers.
Combining the two curves allows managers to determine the price and quantity of
the product.

Equilibrium Price and Equilibrium Quantity
Figure 2.7 combines the demand curve, D, shown in Figure 2.1 and the supply curve,
S, shown in Figure 2.4. The curves cross at a price of $60 per pair of jeans. This price,
called the equilibrium price, is the only price at which the quantity demanded
equals the quantity supplied.

If the price does not equal the equilibrium price, it will change so that it does. At
any price higher than the equilibrium price, there is a surplus of jeans—sellers offer
more jeans for sale than demanders want to buy. For example, at a price of $100 per
pair, the supply curve shows that the quantity of jeans supplied is 500 million pairs,
but the demand curve shows that the quantity of jeans demanded is only 100 million
pairs. At this price, there is a surplus of 400 million pairs (500 million minus 100 mil-
lion), resulting in undesired inventories of unsold jeans. The inventories, piling up

Equilibrium price The
price at which the quantity
demanded equals the
quantity supplied.

Price (thousands of dollars per car)

Quantity (millions of
gasoline-powered cars per year)

$33

$28

$29

9.69.49.29.08.88.68.4

$30

$31

$32

0

S 1

S 0

Answer

a. The term showing how the price of a hybrid car affects the supply of gasoline-powered
cars, 1200 cars * PHYBRID2, is preceded by a negative sign, so an increase in the
price of a hybrid decreases the supply of gasoline-powered cars. A hybrid is a
substitute in production
for gasoline-powered
cars.

b. The $2,000 increase in the
price of the hybrid car
decreases the supply of
gasoline-powered cars
by 200 cars * $2,000 =
400,000 cars, so the
supply curve of gasoline-
powered cars shifts to
the left by 400,000 cars.
In the figure, the initial
supply curve is S0. The
increase in the price of a
hybrid shifts the supply
curve left to S1, a shift
equal to 400,000 cars at
every price.

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52  CHAPTER 2 Demand and Supply

ever higher, lead the firms’ managers to lower the price. As the price falls, suppliers
cut their production plans, so the quantity supplied decreases and the quantity
demanded increases. Both of these changes help decrease the surplus, but as long as
there is a surplus, the unwanted inventories continue to accumulate, and the price
continues to fall. Eventually, the price falls to the equilibrium price. At this price,
there is no longer a surplus of jeans: The quantity of jeans supplied equals the quan-
tity of jeans demanded: 300 million pairs. Because there is no surplus, the price stops
falling once it equals the equilibrium price.

Similarly, at any price lower than the equilibrium price, there is a shortage of
jeans—the quantity of jeans offered for sale is less than the quantity demanders want
to buy. Suppose that the price is $20 per pair; at this price, the quantity of jeans
demanded is 500 million pairs, but the quantity supplied is only 100 million pairs. The
shortage is 500 million minus 100 million, or 400 million pairs of jeans. The shortage
means that producers cannot keep jeans in inventory; every pair they place on the
racks is gone almost immediately. So the managers raise the price of jeans. As the price
rises, the quantity demanded decreases, and producers increase their production
plans, so the quantity supplied increases. Although both changes reduce the shortage,
the price rises as long as a shortage exists. Eventually, the price rises to $60 per pair. At
this equilibrium price, there is no longer a shortage of jeans: The quantity of jeans
demanded equals the quantity supplied: 300 million pairs. Once the price equals the
equilibrium price, it stops rising because the shortage has been eliminated.

Because the only price that can persist and not change is the equilibrium price, it
is reasonable to assume that the market price equals the equilibrium price. Now that
you know the price, you need to determine the quantity. At the equilibrium price,
the quantity demanded equals the quantity supplied. The equilibrium quantity
is the quantity bought and sold at the equilibrium price, which equals both the
quantity demanded and the quantity supplied. In Figure 2.7, the equilibrium quan-
tity is 300 million pairs of jeans per year, the quantity bought and sold at the $60
equilibrium price.

Equilibrium quantity The
quantity bought and sold at
the equilibrium price.

Price (dollars per pair of jeans)

Quantity (millions of pairs of jeans per year)

$140

$20

$40

700600500400300200100

$60

$80

$100

$120

0

S

D

Equilibrium price: $60
Equilibrium quantity: 300 million

Figure 2.7 Equilibrium Price and Equilibrium
Quantity

The intersection of the demand curve, D, and
supply curve, S, determines the equilibrium price
and equilibrium quantity. As shown, the
equilibrium price is $60 per pair of jeans, and the
equilibrium quantity is 300 million pairs. At any
price higher than the equilibrium price, there is a
surplus, which forces the price lower until it falls
to the equilibrium price. At any price lower than
the equilibrium price, there is a shortage, which
forces the price higher until it rises to the
equilibrium price. Only at the equilibrium price is
there neither a surplus nor a shortage of jeans.

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2.3 Market Equilibrium  53

The equilibrium price and equilibrium quantity are examples of the general con-
cept of equilibrium: a situation in which no automatic forces lead to change. Once at
the equilibrium, the situation will persist until some factor changes. You will explore
the idea of equilibrium further in future chapters, such as Chapters 5, 6, 7, and 8,
when you learn how firms determine the price to charge and the quantity to
produce.

Demand and Supply Functions: Equilibrium
In Figure 2.7, the equilibrium price is $60 per pair of jeans, and the equilibrium
quantity is 300 million pairs of jeans. You can use the demand function that corre-
sponds to the demand curve in Figure 2.7, Qd = 600 million – 15 million * P2, and
the supply function that corresponds to the supply curve, Qs = 5 million * P, to
check that you get the same equilibrium price and quantity algebraically that you
did graphically. At the equilibrium price, the quantity demanded, Qd, equals the
quantity supplied, Qs, or Qd = Qs. Equating the demand function and the supply
function gives

600 million – 15 million * P2 = 5 million * P
To solve for the equilibrium price, first add 15 million * P2 to both sides:

600 million = 15 million * P2 + 15 million * P2
Next, add the terms on the right side of the equality:

600 million = 10 million * P

Finally, divide by 10 million to solve for the equilibrium price:

P =
600 million
10 million

= $60

precisely the same equilibrium price shown in Figure 2.7. Using the $60 equilibrium
price in either the demand or the supply function yields the equilibrium quantity. For
example, using the equilibrium price of $60 per pair of jeans in the supply function
shows that Q = 5 million * 60, or 300 million pairs per year, which also corre-
sponds to the equilibrium quantity shown in Figure 2.7.

More generally, if the demand function is linear and depends only on the price
of the product, it can be written as Qd = a – 1b * P2. If the supply function is also
linear and also depends only on the price, it can be written as Qs = r + 1s * P2.
Then equating the demand function and the supply function gives

a – 1b * P2 = r + 1s * P2
This equation can be solved for the equilibrium price as

P =
a – r
s + b

Use this value for the price in either the demand or the supply function and some
algebra to solve for the equilibrium quantity:

Q =
1a * s2 + 1b * r2

s + b

Equilibrium A situation in
which no automatic forces
lead to change; once at the
equilibrium, the situation
will persist until some
factor changes.

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54  CHAPTER 2 Demand and Supply

Now that you have learned how to determine the equilibrium price and quan-
tity in a competitive market, you are ready for a related topic: discovering why econ-
omists have a strong preference for competitive markets and, as a result, use them as
the standard of comparison for all other types of markets.

Equilibrium Price and Quantity of Plush Toys

You are a manager at Content Colleague, a company similar to Happy Worker, a Canadian
company that manufactures vinyl, plush, and resin toys and collectibles. Your research
specialist has given you demand and supply functions for one of your product lines, plush
toys. The demand function for plush toys is Qd = 30 million – 12 million * P2. The
supply function for plush toys is Qs = 3 million * P . Your supervisor asks you to
determine the equilibrium price and equilibrium quantity of plush toys.

Answer
To determine the equilibrium price and quantity, you need to set the demand function
equal to the supply function:

30 million – 12 million * P2 = 3 million * P
Now solve for the equilibrium price, P :

30 million = 13 million * P2 + 12 million * P2
30 million = 5 million * P

P = 130 million2>15 million2 = $6 per stuffed toy animal

Use this equilibrium price in either the demand or the supply function to determine
the equilibrium quantity. Using it in the supply function gives Q = 3 million * $6 =
18 million plush toys.

SOLVED
PROBLEM

2.4 Competition and Society
Learning Objective 2.4 Explain why perfectly competitive markets are
socially optimal.

Society has a limited amount of resources, such as labor and capital. This limitation
makes it impossible to produce unlimited amounts of a good or service, so it is
important for society to obtain the greatest benefit from its resources. This section
describes how competitive markets foster the optimal allocation of society’s scarce
resources.

Total Surplus
Figure 2.8 shows the demand and supply curves for jeans. You can use these to
determine what quantity of jeans is the socially best quantity to produce.

As we described earlier, the market demand curve, D, shows the maximum price
consumers are willing and able to pay for any particular pair of jeans. For example,
point A shows that some consumer is willing to pay a maximum price of $100

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2.4 Competition and Society  55

for the 100 millionth pair. The maximum price the consumer will pay for a pair of
jeans equals the consumer ’s marginal benefit from that pair, so the consumer ’s
marginal benefit from this pair is $100. Why is the maximum price equal to the
marginal benefit?

• If the marginal benefit exceeded $100, the consumer would be willing to pay
more than $100. But the consumer is not willing to pay more than $100.

• If the marginal benefit was less than $100, the consumer would not be willing to
pay $100. But the consumer is willing to pay $100.

Since the consumer’s marginal benefit from the pair of jeans cannot be greater than
$100 nor can it be less than $100, the marginal benefit must be equal to $100. Because
the consumer of this pair of jeans is the recipient of the benefit and is a member of
society, the marginal benefit to society is equal to the consumer’s marginal benefit.
So, society’s marginal benefit from the 100 millionth pair of jeans is $100.

The producer’s marginal cost of producing any particular pair of jeans can be
determined from the supply curve. For example, in Figure 2.8, point B on the supply
curve shows that the minimum price some firm is willing to accept to produce the
100 millionth pair of jeans is $20. The minimum price equals the producer’s mar-
ginal cost of producing this pair. Why does the minimum price equal the marginal
cost of producing the pair of jeans?

• If the marginal cost exceeded $20, the producer would not be willing to accept
$20 for the jeans because that price would inflict a loss on the producer. But the
producer is willing to accept $20.

• If the marginal cost was less than $20, then the producer would be willing
(but not eager!) to accept a lower price because at a lower price the producer
still would not incur a loss. But the producer is not willing to accept less
than $20.

Price (dollars per pair of jeans)

Quantity (millions of pairs of jeans per year)

$140

$20

$40

700600500400300200100

$60

$80

$100

$120

0

S

A

B
D

Figure 2.8 Marginal Benefit and Marginal Cost

The market demand curve, D, shows the highest
price a consumer is willing to pay for any particular
pair of jeans. This amount equals the marginal
benefit to the consumer of that particular pair. Point
A shows that the marginal benefit of the 100
millionth pair is $100. The supply curve, S, shows
the lowest price a supplier is willing to accept for
any pair of jeans. This amount equals the marginal
cost of that particular pair of jeans. Point B shows
that the marginal cost of the 100 millionth pair is
$20. For this pair of jeans, society gains a surplus of
marginal benefit over marginal cost of $80. For all
of the jeans up to 300 million pairs, society enjoys a
surplus of marginal benefit over marginal cost.

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56  CHAPTER 2 Demand and Supply

Since the producer’s marginal cost of producing the pair of jeans cannot be more
than $20 nor can it be less than $20, the marginal cost must be equal to $20. Because
the producer pays the marginal cost, the marginal cost to society is equal to the pro-
ducer’s marginal cost. In other words, society’s marginal cost of the 100 millionth
pair of jeans is $20.

The marginal benefit to society ($100) is greater than the marginal cost ($20).
Therefore, producing and consuming this pair of jeans gives society a surplus of
marginal benefit over marginal cost of $80. In Figure 2.8, the surplus is equal to the
length of the double-headed arrow. The figure also shows that all jeans up to the
300 millionth pair (the equilibrium quantity) have a surplus of marginal benefit
over marginal cost. If you apply the marginal analysis rule (produce each unit for
which the marginal benefit exceeds the marginal cost), you will see that each of the
300 million pairs of jeans should be produced. The total surplus of benefit over cost to
society from production of the 300 million pairs is the sum of the surpluses of all the
pairs of jeans produced. When all 300 million surpluses are added, their sum is
equal to the area of the green triangle in Figure 2.9.

The quantity of output that yields the largest total surplus for society is
called the efficient quantity. In a competitive market, the equilibrium quantity
equals the efficient quantity,8 so in Figure 2.9 the efficient quantity is 300 million
pairs of jeans.

Efficient quantity The
quantity of output that
yields the largest total
surplus of marginal benefit
over marginal cost for
society.

Price (dollars per pair of jeans)

Quantity (millions of pairs of jeans per year)

$140

$20

$40

700600500400300200100

$60

$80

$100

$120

0

S

D

Total
surplus

Figure 2.9 Total Surplus

When the equilibrium
quantity (300 million pairs
of jeans) is produced, the
total surplus of benefit over
cost to society is equal to
the area of the green
triangle. The quantity that
creates the largest total
surplus is the efficient
quantity.

8 There are exceptions to this rule. In particular, the rule fails if the producer does not pay some of the
costs of production. For example, if the production creates pollution, then part of the cost of production is
the cost of pollution, but the victims of the pollution rather than the producer pay this cost. The rule also
fails if the consumer does not receive some of the benefits of consumption. For example, a person who has
a flu shot benefits, but so, too, does everyone else who comes in contact with that person. In such cases,
the equilibrium quantity does not have the largest total surplus. These topics are beyond the scope of this
text, however, and are best left to courses covering microeconomic theory.

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2.4 Competition and Society  57

Underproduction and Overproduction
What happens to society’s total surplus if the quantity produced is not the efficient
quantity? Setting aside for a moment the question of why more or less might be
produced, marginal analysis can help answer this question. Let’s begin by consider-
ing the situation in which less than the efficient quantity of 300 million pairs of
jeans is produced (underproduction) and then move to the situation in which more
than efficient quantity of 300 million pairs is produced (overproduction).

• Underproduction. If production is less than 300 million pairs of jeans, some
pairs that would have a surplus of marginal benefit over marginal cost are not
produced. But according to marginal analysis, these units should be produced.
Because these units have a surplus, failure to produce them lowers the total sur-
plus, resulting in a smaller total surplus for society.

• Overproduction. If production is more than 300 million pairs of jeans, all of the
pairs beyond 300 million have a marginal benefit that is less than their marginal
cost. According to marginal analysis, from society’s perspective these units
should not be produced. The production of any of these units subtracts from the
total surplus, again resulting in a smaller total surplus for society.

Figure 2.10 shows the decrease in total surplus. The loss in total surplus from
producing less or more than the efficient quantity is called the deadweight loss. A
deadweight loss is a loss to society. No one gains from a deadweight loss.

At the most fundamental level, manufacturing jeans means that society is put-
ting resources to use. When the quantity of jeans produced is the efficient quantity,
resources are allocated optimally, with no deadweight loss and with the largest
total surplus. In contrast, when less than the efficient quantity of jeans is pro-
duced, a deadweight loss occurs because the marginal benefit of the last pair of
jeans exceeds its marginal cost, which means resources are misallocated: More

Deadweight loss The
loss in total surplus from
producing less or more
than the efficient quantity.

Price (dollars per pair of jeans)

Quantity (millions of pairs of jeans per year)

$140

$20

$40

700600500400300200100

$60

$80

$100

$120

0

S

D

Deadweight
loss from
underproduction

Deadweight
loss from
overproduction

Figure 2.10 Deadweight Loss

A deadweight loss is the loss in total surplus from
producing less (underproduction) or more
(overproduction) than the efficient quantity,
300 million pairs of jeans. Producing less (say,
200 million pairs) or more (say, 400 million pairs)
results in a deadweight loss.

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58  CHAPTER 2 Demand and Supply

resources should be directed to producing jeans and fewer to producing other
goods and services. When more than the efficient quantity of jeans is produced, a
deadweight loss occurs because the marginal benefit of the last pair of jeans is less
than its marginal cost, which again means resources are misallocated: Fewer
resources should be directed to producing jeans and more to producing other
goods and services.

Because the equilibrium quantity in a competitive market leads to the largest
total surplus for society, economists use competitive markets as the standard of com-
parison for other market structures. Although this conclusion has no direct implica-
tion for you as a manager, it is the basis for the nation’s antitrust laws, which
certainly do have important consequences for managerial decision making, as you
will learn in Chapter 9.

Consumer Surplus
Total surplus can be divided into consumer surplus and producer surplus. Keep in
mind that the equilibrium price is the actual price that consumers pay (and suppliers
receive). Some consumers are willing to pay more than this price, but the market
does not require them to do so. For example, point A in Figure 2.11 shows what you
saw in Figure 2.8—that some consumer is willing to pay $100 for the 100 millionth
pair of jeans. But that consumer actually pays only $60 (the equilibrium price). The
consumer surplus is the difference between the maximum price consumers are will-
ing and able to pay for each unit of a product and the price actually paid, summed
over the quantity of units purchased. For example, the consumer of the 100 millionth
pair of jeans has a consumer surplus equal to $100 – $60 = $40 for that pair. The
consumer surplus in the entire market is the total of all of these surpluses on all of
the pairs of jeans purchased.

The demand curve in Figure 2.11 shows the maximum price consumers are will-
ing to pay for each pair of jeans. The equilibrium price is the price consumers

Consumer surplus The
difference between the
maximum price consumers
are willing and able to pay
for each unit of a product
and the price actually paid,
summed over the quantity
of units purchased.

Price (dollars per pair of jeans)

Quantity (millions of pairs of jeans per year)

$140

$20

$40

700600500400300200100

$60

$80

$100

$120

0

S

A

D

Consumer
surplus

Figure 2.11 Consumer
Surplus

The consumer surplus is
the difference between the
maximum price consumers
are willing to pay for each
pair of jeans and the price
actually paid, summed over
the total number of pairs
of jeans purchased. The
consumer surplus in the
market is equal to the green
triangular area under the
demand curve (which shows
the maximum price the
consumer is willing to pay
for any pair) and above the
equilibrium price (which is
the price actually paid).

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2.4 Competition and Society  59

actually pay, so the consumer surplus in the market equals the green triangular area
under the demand curve and above the equilibrium price in Figure 2.11.

Consumer surplus presents an intriguing concept for managers. It reveals that
consumers are willing to pay more than the amount they actually pay. Future chap-
ters will explore pricing schemes that share the basic goal of transferring consumer
surplus from consumers to suppliers as increased profit.

Producer Surplus
The consumer surplus in Figure 2.11 is only part of the total surplus shown in
Figure 2.9. The remaining piece goes to producers as producer surplus. The
producer surplus is the difference between the actual price producers receive for
each unit and the minimum price they are willing to accept to produce that unit,
summed over the quantity of units produced. In Figure 2.12, as in Figure 2.8, point
B shows that some producer is willing to produce and sell the 100 millionth pair of
jeans for $20 (its marginal cost). But that producer actually receives $60 (the equilib-
rium price). The producer surplus on this pair is $60 – $20 = $40.9 The producer
surplus in the entire market is the total of the producer surpluses for all the units
produced. In Figure 2.12, the producer surplus is the green triangular area under
the equilibrium price and above the supply curve.

If you compare Figures 2.11 and 2.12, you will see that the consumer surplus
is equal to the producer surplus. This result is a fluke; it occurs only by chance.
However, if you compare Figures 2.9, 2.11, and 2.12, you will see that the total sur-
plus shown in Figure 2.9 equals the sum of the consumer surplus in Figure 2.11

Producer surplus The
difference between the
actual price producers
receive for each unit and
the minimum price they are
willing to accept to
produce that unit, summed
over the quantity of units
produced.

9 Producer surplus and economic profit are related. In particular, the economic profit for all of the firms
in the market equals the total producer surplus minus all of the firms’ fixed costs. But the details of this
relationship are best covered in a microeconomic theory course.

Price (dollars per pair of jeans)

Quantity (millions of pairs of jeans per year)

$140

$20

$40

700600500400300200100

$60

$80

$100

$120

0

S

B
D

Producer
surplus

Figure 2.12 Producer Surplus

Producer surplus is the difference between the
actual price suppliers receive for each unit and the
minimum price they would be willing to accept to
produce that unit (their marginal cost), summed
over the quantity of units produced. The producer
surplus in the market is equal to the green triangular
area under the equilibrium price (which is the
actual price the suppliers receive for each pair of
jeans) and above the supply curve (which shows
the minimum price the suppliers are willing to
accept to produce any pair).

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60  CHAPTER 2 Demand and Supply

and the producer surplus in Figure 2.12. This result is not a fluke; it is always the
case because the total surplus can always be divided into the part that goes to
consumers (the consumer surplus) and the part that goes to producers (the pro-
ducer surplus).

You have seen how to use the demand and supply model to determine the equi-
librium price and quantity and why producing the equilibrium quantity is socially
optimal because it maximizes the total surplus. The real power of the model, how-
ever, comes from its ability to predict what happens to price and quantity if some-
thing in the market changes, which is the topic of the next section.

Total Surplus, Consumer Surplus, and Producer
Surplus in the Webcam Market

When a market is producing the efficient quantity, must the consumer surplus always
equal the producer surplus? Use the market for webcams, and suppose that the equi-
librium price is $30 and the equilibrium quantity is 3 million. Then draw two graphs to
support your answer.

Answer
Your graphs should look similar to those below. When the market produces the efficient
quantity, 3 million webcams per year, the consumer surplus does not necessarily equal
the producer surplus. In Figure a, the consumer surplus exceeds the producer surplus,
while in Figure b, the producer surplus exceeds the consumer surplus. The amounts of
the consumer surplus and producer surplus depend on the slopes and shapes of the
demand and supply curves.

SOLVED
PROBLEM

Price (dollars per webcam)

Quantity (millions of
webcams per year)

$60

$10

5 63 41 2

$20

$30

$40

$50

0

S

D

Consumer
surplus

Producer
surplus

Price (dollars per webcam)

Quantity (millions of
webcams per year)

$60

$10

5 63 41 2

$20

$30

$40

$50

0

S

D

Consumer
surplus

Producer
surplus

(a) (b)

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2.5 Changes in Market Equilibrium  61

2.5 Changes in Market Equilibrium
Learning Objective 2.5 Use the demand and supply model to predict how
changes in the market affect the price and quantity of a good or service.

The demand and supply model is a powerful tool that can predict what happens to
price and quantity if something in the market changes. Making these predictions is
an important managerial skill. Once you become familiar enough with figures using
demand and supply curves, determining the impact of changes in demand or sup-
ply will become second nature—you will know the answer immediately without
needing a figure. Reaching that stage takes practice, however. This section begins by
outlining a four-step procedure that shows how to use a demand and supply figure
to predict the effect of a change. We then use this process to explore two scenarios:
(1) changes in demand with no change in supply and (2) changes in supply with no
change in demand. As a manager, however, you will often deal with situations in
which more than one factor changes. The section concludes by presenting and then
using a modified four-step procedure to deal with the more complex scenario of
simultaneous changes in demand and supply.

Let’s start with the four-step procedure that you can use when one factor that
affects the market changes:

1. Draw a demand and supply figure like the one shown in Figure 2.7, and label
everything—the curves, the axes, and the initial equilibrium price and quantity.

2. Determine which curve, the demand curve or the supply curve, is affected by
the factor that changes.

3. Determine whether the change shifts the curve to the right or to the left.
4. Add the new curve to your original diagram to determine the new equilibrium

price and quantity.

Now let’s apply this procedure, starting first with a change in demand.

Use of the Demand and Supply Model When
One Curve Shifts: Demand
What happens to the price and quantity of a good or service if demand increases or
decreases? Let’s begin by examining the effect of an increase in demand. Recall that
the factors that change demand and shift the demand curve include consumers’
income, the price of related goods and services, consumers’ preferences and adver-
tising, financial market conditions, the expected future price of the product, and the
number of demanders. The effect of the change in demand on the price and quantity
of a good or service is the same regardless of the factor involved, so let’s return to
our jeans example and presume that jeans are a normal good so that an increase in
consumers’ income will increase the demand for jeans.

Increase in Demand
Suppose that the economy enters a strong economic expansion, so people’s incomes
increase. As a manager at a company that produces jeans, you are interested in how
this change will affect the price in the market because that will affect the price you can
charge for your jeans. Start with step 1 of the four-step procedure by drawing a
demand and supply figure like that in Figure 2.13, with demand curve D0 and supply

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62  CHAPTER 2 Demand and Supply

curve S. The initial equilibrium price is $60 per pair, and the initial equilibrium quan-
tity is 300 million pairs of jeans. From Section 2.1, you know that an increase in
income for a normal good increases its demand (step 2) and shifts its demand curve
to the right (step 3). Finally, draw the new demand curve, D1, in your figure (step 4).
Figure 2.13 shows this as a shift of the demand curve to the right, from D0 to D1. The
increase in demand raises the equilibrium price of a pair of jeans from $60 to $80 and
increases the equilibrium quantity from 300 million to 400 million pairs per year.

Notice that the change in income shifts only the demand curve. There is a move-
ment along the supply curve rather than a shift because a change in income is not one
of the factors that shifts the supply curve. Regardless of the reason for an increase in
demand, the demand curve shifts to the right, there is a movement along the supply
curve, and the effects on the price and quantity are identical to what Figure 2.13
illustrates: The price rises and the quantity increases.

Decrease in Demand
A decrease in demand has the opposite effect of the scenario illustrated in Figure 2.13.
For example, suppose that people’s preferences change: They come to prefer yoga
pants more and jeans less. Now start the four-step process once again by drawing
your demand and supply diagram (step 1). From Section 2.1, you know that such a
change in preferences decreases the demand for jeans (step 2) and shifts the demand
curve for jeans to the left (step 3). Draw this new demand curve in your diagram,
and determine the effect on the price and quantity (step 4).

Figure 2.14 illustrates this process. The initial demand curve is D0, and the initial
supply curve is S. The change in preferences away from jeans decreases the demand
for jeans and shifts the demand curve left to D1. After the change in preferences
decreases the demand, the new equilibrium is where the new demand curve, D1,
and the supply curve, S, intersect. The new equilibrium price is $40 per pair, and the
new equilibrium quantity is 200 million pairs per year. As in the previous example,

Price (dollars per pair of jeans)

Quantity (millions of pairs of jeans per year)

$140

$20

$40

700600500400300200100

$60

$80

$100

$120

0

S

D0

D1

New
equilibrium

Initial
equilibrium

Figure 2.13 An Increase in
Demand for Jeans

When the demand for
jeans increases, the
demand curve shifts to the
right, from D0 to D1. This
shift increases the price of
jeans, from $60 to $80 per
pair, and increases the
quantity, from 300 million
to 400 million pairs per
year.

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2.5 Changes in Market Equilibrium  63

only the demand curve shifts because a change in preferences is not among the fac-
tors that shift the supply curve. Regardless of the reason for a decrease in demand,
the effects on the price and quantity are identical to what Figure 2.14 illustrates: The
price falls and the quantity decreases.

Use of the Demand and Supply Model When
One Curve Shifts: Supply
You have seen how to tackle changes that affect demand. Now you will learn how to
handle changes that affect supply using the same four-step procedure. Recall that
the factors that change supply and shift the supply curve include changes in cost, the
price of related goods and services, technology, the state of nature, the expected
future price of the product, and the number of suppliers. The effect on the price and
quantity is the same regardless of the factor involved.

Increase in Supply
Suppose that the producers of jeans develop new, more highly automated methods
of manufacturing jeans. To determine the effect on the price and quantity of jeans,
start by drawing a demand and supply diagram like that in Figure 2.15, with demand
curve D and supply curve S0 (step 1). The intersection of supply curve S0 and
demand curve D determines the initial equilibrium price ($60 per pair) and the ini-
tial equilibrium quantity (300 million pairs). The new methods of automation are a
technological advance, which affects the supply (step 2) by increasing it and causes a
rightward shift in the supply curve (step 3). As shown in Figure 2.15, the supply
curve shifts to the right, from S0 to S1 (step 4). The new equilibrium is where the new
supply curve, S1, and the demand curve, D, intersect. The equilibrium price falls
from $60 to $40 per pair, and the equilibrium quantity increases from 300 million to
400 million pairs per year.

Notice how the technological advance changes only the supply and shifts only the
supply curve. The demand curve does not shift because technology is not one of

Price (dollars per pair of jeans)

Quantity (millions of pairs of jeans per year)

$140

$20

$40

700600500400300200100

$60

$80

$100

$120

0

S

D0D1

New
equilibrium

Initial
equilibrium

Figure 2.14 A Decrease in
Demand for Jeans

When the demand for
jeans decreases, the
demand curve shifts to the
left, from D0 to D1. This
shift decreases the price of
jeans, from $60 to $40 per
pair, and decreases the
quantity, from 300 million
to 200 million pairs per
year.

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64  CHAPTER 2 Demand and Supply

the factors that affect demand. Instead, there is a movement along the demand curve.
Regardless of the reason for an increase in the supply, the effects on the price and quan-
tity are identical to what Figure 2.15 illustrates: The price falls and the quantity increases.

Decrease in Supply
Finally, suppose that the price of denim rises. This price hike increases the cost of
producing jeans. How will the increase in cost affect the price and quantity of jeans?
Again, use the four-step procedure to find the answer. Draw the initial supply curve,
S0, and the demand curve, D, as shown in Figure 2.16 (step 1). The initial equilibrium
is where the demand curve, D, intersects the original supply curve, S0. Now you
must determine which curve is affected by the increase in cost. Only the supply
curve shifts because a change in cost is not a factor that affects demand (step 2). The
increase in cost decreases the supply and shifts the supply curve to the left, from S0
to S1 in Figure 2.16 (step 3). After the supply decreases, the new equilibrium is where
the demand curve, D, intersects the new supply curve, S1 (step 4). Figure 2.16 shows
that the increase in cost raises the price from $60 to $80 per pair of jeans and
decreases the quantity from 300 million to 200 million pairs per year. The demand
curve does not shift because cost is not one of the factors that affect demand. Instead,
there is a movement along the demand curve. Regardless of the reason for a decrease
in the supply of a good or service, the effects on the price and quantity are identical
to what Figure 2.16 illustrates: The price rises and the quantity decreases.

Use of the Demand and Supply Model When
Both Curves Shift
So far you have learned about the effects of a shift in either the supply curve or the
demand curve. In real-world markets, two or more factors can change at the same time,
however, causing both curves to shift simultaneously. The ability to use the demand
and supply model to determine the effect on the price and quantity when there is a
change in both demand and supply is another important managerial skill. Although this
situation is slightly more complicated than the one in which only the demand or only

Price (dollars per pair of jeans)

Quantity (millions of pairs of jeans per year)

$140

$20

$40

700600500400300200100

$60

$80

$100

$120

0

S 0

S 1

D

New
equilibrium

Initial
equilibrium

Figure 2.15 An Increase in
Supply of Jeans

When the supply of jeans
increases, the supply curve
shifts to the right, from S0
to S1. This shift lowers the
price of jeans, from $60 to
$40 per pair, and increases
the quantity, from 300
million to 400 million pairs
of jeans per year.

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2.5 Changes in Market Equilibrium  65

the supply changes, if you practice solving problems when both change using the
demand and supply model, once again eventually you’ll be able to quickly determine
the answers without the model. Until that time, however, practice using figures and the
following modified version of the four-step procedure described earlier:

1. Draw two demand and supply figures, and label everything—the curves, the
axes, and the initial equilibrium price and quantity.

2. For the first factor that changes, determine (a) whether it is the demand curve or
the supply curve that is affected and (b) the direction of the change.

3. Repeat step 2 for the second factor that changes.
4. In one of your demand and supply figures, draw the new demand curve with a

large shift and the new supply curve with a small shift. In the other figure, draw
the new demand curve with a small shift and the new supply curve with a large
shift. This step might appear odd, but it is necessary because the effect on the
price or the quantity depends on which shift is larger. Then you must compare
the answers to see if the effect on the price or quantity is certain or ambiguous.

To see how this modified procedure works, we will begin with situations in
which demand and supply change in the same way: Both increase or both decrease.
Then we will move to situations in which demand and supply change in opposite
directions: One increases and the other decreases.

Similar Changes in Demand and Supply
Suppose that both the demand and the supply of a particular product increase. Con-
sider the following scenario: Jeans and denim skirts are substitutes for consumers
and the price of denim skirts rises at the same time that more firms start to produce
jeans. What will be the impact of these changes on the price and quantity of jeans?

Figure 2.17 demonstrates how to conduct the analysis of this scenario. Begin with
step 1 by drawing two demand and supply figures (in parts a and b), with initial
demand curve D0 and initial supply curve S0. The initial equilibrium price is $60 per pair

Price (dollars per pair of jeans)

Quantity (millions of pairs of jeans per year)

$140

$20

$40

700600500400300200100

$60

$80

$100

$120

0

S0
S1

D

Initial
equilibrium

New
equilibrium

Figure 2.16 A Decrease in
Supply of Jeans

When the supply of jeans
decreases, the supply
curve shifts to the left,
from S0 to S1. This shift
raises the price, from $60
to $80 per pair, and
decreases the quantity,
from 300 million to 200
million pairs of jeans per
year.

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66  CHAPTER 2 Demand and Supply

of jeans, and the initial equilibrium quantity is 300 million pairs of jeans. Next, move to
step 2: The increase in the price of denim skirts increases the demand for jeans and shifts
the demand curve for jeans to the right. Follow with step 3: The increase in the number
of firms increases the supply of jeans and shifts the supply curve to the right. Finally,
step 4 is drawing the shifts with different sizes. In both parts of Figure 2.17, the demand
curve shifts rightward from D0 to D1 and the supply curve shifts rightward from S0 to S1.
In Figure 2.17(a), however, the demand curve has shifted by more than the supply curve.
In this case, the price rises, from $60 to $80 per pair, and the quantity increases, from 300
million to 600 million pairs per year. Compare these results with those in Figure 2.17(b),
in which the supply curve has shifted by more than the demand curve. In this case, the
price falls, from $60 to $40 per pair, but the quantity still increases, from 300 million to
600 million pairs per year. (The result that the increase in quantity is the same in both
situations is a coincidence.)

When both curves shift to the right, the quantity always increases. But unless
you know which shift is larger, the impact on the price is ambiguous. If demand
increases by more than supply, the price rises. If supply increases by more than
demand, the price falls. In fact, in a third scenario, not illustrated in Figure 2.17, if
demand increases by the same amount as supply, the price does not change. Know-
ing the size of each effect—perhaps because your company’s research department
has determined the relative sizes of the changes—will allow you to determine which
result is appropriate so then you can predict the change in both price and quantity.

If both the demand and the supply decrease, the situation is the reverse of what
you just learned: Both curves shift to the left. The effect on the quantity is certain:
Quantity decreases. The effect on the price is uncertain. If demand decreases by
more than supply, the price falls. If supply decreases by more than demand, the price

Price (dollars per
pair of jeans)

Quantity (millions of
pairs of jeans per year)

$120

$140

$20

500 600 700300 400100 200

$40

$60

$80

$100

0

D1

S1

S0

D0

New
equilibrium

Initial
equilibrium

Price (dollars per
pair of jeans)

Quantity (millions of
pairs of jeans per year)

$120

$140

$20

500 600 700300 400100 200

$40

$60

$80

$100

0

D1

S1

S0

D0

New
equilibrium

Initial
equilibrium

Figure 2.17 Increase in Demand for Jeans and Increase in Supply of Jeans

(a) Large Increase in Demand, Small Increase in Supply (b) Small Increase in Demand, Large Increase in Supply
If the increase in demand exceeds the increase in
supply, the price rises and the quantity increases.

If the increase in supply exceeds the increase in
demand, the price falls and the quantity increases.

The quantity definitely increases. But without knowing which effect is larger, the price might rise (if the change
in demand is larger, as in part a), fall (if the change in supply is larger, as in part b), or not change (not illustrated
but occurs if the two changes are of the same magnitude).

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2.5 Changes in Market Equilibrium  67

rises. If demand and supply decrease by the same amount, the price does not
change. In all cases, the quantity decreases, but until you know which effect is larger,
the impact on the price is ambiguous.

Opposite Changes in Demand and Supply
You have just learned what happens if both the demand and the supply change in
the same direction. Let’s now examine what happens if one increases and the other
decreases. Consider this scenario: Jeans are a normal good, and people’s incomes
increase at the same time that significant flooding occurs in the regions where the
jean factories are located, damaging many of the factories. What will be the impact of
these two changes on the price and quantity of jeans?

Draw two demand and supply diagrams, such as those shown in parts a and b
in Figure 2.18 (step 1). The increase in income increases the demand for jeans and
shifts the demand curve to the right (step 2). The flooding, a bad state of nature,
decreases the supply of jeans and shifts the supply curve to the left (step 2). As in the
previous example, for step 4 you need to include the new demand and supply
curves in your diagrams, but, following step 3, in one, you make the demand shift
larger, and in the other, you make the supply shift larger. Figure 2.18 illustrates this.
In both parts of the figure, the demand curve shifts rightward, from D0 to D1, and
the supply curve shifts leftward, from S0 to S1. In Figure 2.18(a), the demand curve
has shifted by more than the supply curve. In this case, the price of jeans rises, from
$60 to $120 per pair, and the quantity increases, from 300 million to 400 million pairs
per year. In Figure 2.18(b), however, the supply curve has shifted by more than the
demand curve. The price of jeans still rises, coincidentally again from $60 to $120 per
pair, but now the quantity decreases, from 300 million to 200 million pairs per year.

Price (dollars per pair of jeans)

Quantity (millions of
pairs of jeans per year)

$120

$140

$20

500 600 700300 400100 200

$40

$60

$80

$100

0

D1

S0S1

D0

New
equilibrium

Initial
equilibrium

Price (dollars per pair of jeans)

Quantity (millions of
pairs of jeans per year)

$120

$140

$20

500 600 700300 400100 200

$40

$60

$80

$100

0

D1

S0S1

D0

New
equilibrium

Initial
equilibrium

Figure 2.18 Increase in Demand for Jeans and Decrease in Supply of Jeans

(a) Large Increase in Demand, Small Decrease in Supply (b) Small Increase in Demand, Large Decrease in Supply
If the increase in demand exceeds the decrease in
supply, the price rises and the quantity increases.

If the decrease in supply exceeds the increase in
demand, the price rises and the quantity decreases.

The price definitely rises. But without knowing which effect is larger, the quantity might increase (if the change
in demand is larger, as in part a), decrease (if the change in supply is larger, as in part b), or not change (not
illustrated but occurs if the two changes are of the same magnitude).

M02_BLAI8235_01_SE_C02_pp033-085.indd 67 23/08/17 9:49 AM

68  CHAPTER 2 Demand and Supply

When the demand increases and the supply decreases, the price always rises, but the
impact on the quantity is ambiguous. If demand increases by more than supply decreases,
the quantity increases. If, on the other hand, supply decreases by more than demand
increases, the quantity decreases. In a third scenario, not illustrated in Figure 2.18,
the quantity does not change if demand increases by the same amount that supply
decreases. Until you know the relative magnitudes of the shifts, the effect on the quan-
tity is uncertain. Of course, if you are working for a large company, your research
department might be able to provide you with estimates of the sizes of the changes.

You have probably already guessed that the result of a decrease in demand
and an increase in supply will be the opposite of what you just learned. With a
decrease in demand and an increase in supply, the demand curve shifts to the left,
and the supply curve shifts to the right. Regardless of the magnitude of the shifts,
the effect on the price is certain: The price falls. The effect on the quantity is ambig-
uous. If demand decreases by more than supply increases, the quantity decreases. If
supply increases by more than demand decreases, the quantity increases. If the
decrease in demand is the same size as the increase in supply, the quantity does not
change. You must determine the relative sizes of the shifts in order to determine the
impact on the quantity.

Demand and Supply Functions: Changes
in Market Equilibrium
As a manager, it is unlikely that you will use algebraic demand and supply functions
to determine how the price and quantity of a good or service change when some
relevant factor changes. But understanding how to solve for changes in price and
quantity helps reinforce the graphical analysis just presented. To keep the algebra
straightforward, let’s explore the effect of a single change—namely, how an increase
in income affects the price and quantity of jeans.

The demand function that depends on the price and income is

Qd = a – 1b * P2 + 1d * INCOME2
and a simple supply function that depends only on the price is

Qs = r + 1s * P2
At the equilibrium price, the quantity demanded, Qd, equals the quantity sup-

plied, Qs. Equating the quantity demanded and the quantity supplied gives

a – 1b * P2 + 1d * INCOME2 = r + 1s * P2 2.6
Solving this equation for the equilibrium price10 gives

P =
a + 1d * INCOME2 – r

s + b
2.7

Use this price in either the demand or the supply function to solve for the equilib-
rium quantity. Using it in the supply function gives

Q = r + c s * a + 1d * INCOME2 – r1s + b2 d 2.8

10 To solve for the price, first add 1b * P2 to both sides of Equation 2.6 to get a + 1d * INCOME2 =
r + 1s * P2 + 1b * P2. Then subtract r from both sides to get a + 1d * INCOME2 – r =
1s * P2 + 1b * P2. Next, collect the terms on the right side to give a + 1d * INCOME2 – r = 1s + b2 * P .
Finally, divide both sides by 1s + b2 to get the expression for the price, P = 1a + 1d * INCOME2 – r21s + b2 .

M02_BLAI8235_01_SE_C02_pp033-085.indd 68 23/08/17 9:49 AM

2.5 Changes in Market Equilibrium  69

After some algebra, Equation 2.8 can be written as

Q =
1r * b2 + 1s * a2 + 1s * d * INCOME2

s + b
2.9

The equilibrium price and quantity can now be determined using the values of
the coefficients, a, b, d, r, and s, and the level of income. For example, suppose that
a = 200 million pairs of jeans, b = 5 million pairs per dollar, d = 10,000 pairs per
dollar of income, r = 0, s = 5 million pairs per dollar, and INCOME = $40,000.
Using the values for the coefficients and income in the equations for the equilibrium
price, Equation 2.7, and equilibrium quantity, Equation 2.9, gives P = $60 per pair
and Q = 300 million pairs per year.

These equations for the equilibrium price and quantity show the effect of a
change in income on the price and the quantity. If income falls to $20,000, you can
plug this new value into the equations for the equilibrium price and quantity to
show that the decrease in income changes the price, P, to $40 per pair and the quan-
tity, Q, to 200 million pairs per year. Just as illustrated in Figure 2.14, a decrease in
income decreases both the price and the quantity of a normal good.

Table 2.1 summarizes the results when both demand and supply change, so that
both curves shift.

So now you know how the equilibrium price and quantity are determined in
competitive markets and how they change with a change in a factor that influences
those markets. In some markets, however, the government imposes price controls
that place restrictions on the price so that it cannot reach its equilibrium. Price con-
trols are covered in the next section.

Table 2.1 Summary of the Effects of Changes in Both Demand and Supply

DEMAND INCREASES, SUPPLY
INCREASES

DEMAND DECREASES, SUPPLY
DECREASES

Demand
Increase

+
Supply

Increase

Demand
Increase

=
Supply

Increase

Demand
Increase

*
Supply

Increase

Unknown
if Demand
Increase

+, =, or *
Supply

Increase

Demand
Decrease

+
Supply

Decrease

Demand
Decrease

=
Supply

Decrease

Demand
Decrease

*
Supply

Decrease

Unknown
if Demand
Decrease

+, =, or *
Supply

Decrease

Price c No change T Ambiguous T
No

change c Ambiguous

Quantity c c c c T T T T
DEMAND INCREASES, SUPPLY

DECREASES
DEMAND DECREASES, SUPPLY

INCREASES

Demand
Increase

+
Supply

Decrease

Demand
Increase

=
Supply

Decrease

Demand
Increase

*
Supply

Decrease

Unknown
if Demand
Increase

+, =, or *
Supply

Decrease

Demand
Decrease

+
Supply

Increase

Demand
Decrease

=
Supply

Increase

Demand
Decrease

*
Supply

Increase

Unknown
if Demand
Decrease

+, =, or *
Supply

Increase

Price c c c c T T T T
Quantity c No change T Ambiguous T

No
change c Ambiguous

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70  CHAPTER 2 Demand and Supply

2.6 Price Controls
Learning Objective 2.6 Explain the effects of price ceilings and price floors.

You have learned how to determine the equilibrium price and quantity using the
demand and supply model. Sometimes, however, laws prevent the market price
from reaching its equilibrium. For example, in Takoma Park, Maryland, the local
government has passed an ordinance that limits the maximum rent landlords can
charge. This is an example of a price ceiling, which is a government regulation that
sets the maximum legal price. The federal government has also passed laws estab-
lishing minimum prices. In 2017, the minimum price for runner peanuts is $354 per
ton throughout the United States. Such laws are examples of a price floor, which is a
government regulation that sets the minimum legal price. These types of govern-
ment regulations can affect the market by making the equilibrium price illegal. As a
manager, you need to know how they affect your firm. Let’s begin by examining the
effects from a price ceiling and then move to those from a price floor.

Price Ceiling
Figure 2.19 shows the market for apartments in a city like Takoma Park. The price
measured along the vertical axis is the rent per month, and the quantity measured
along the horizontal axis is the number of apartments rented per month. With no
price ceiling, the equilibrium rent is $800 per month, and the equilibrium quantity is
1,200 apartments rented per month.

Suppose, however, that the city government sets a price ceiling of $600 per
month. Because the price ceiling is below the equilibrium rent, the price ceiling

Price ceiling A
government regulation that
sets the maximum legal
price.

Price floor A government
regulation that sets the
minimum legal price.

Demand and Supply for Tablets Both Change

The demand function for tablets is

Qd = 240 million – 10.5 million * P2 + 11,000 * INCOME2
where P is the price of a tablet and INCOME is average income. The supply function for
tablets is

Qs = 1400,000 * P2 – 1200,000 * COST2
where COST is the cost of producing a tablet. Without calculating the values of the equilib-
rium price and quantity, if the cost of producing a tablet rises by $1 and average income
rises by $1, what is the effect on the equilibrium price and equilibrium quantity of tablets?

Answer

The increase in cost decreases the supply, which raises the price and decreases the quantity;
the increase in income increases the demand, which also raises the price but increases the
quantity. Clearly, the price rises. The effect on the quantity depends on which change is
larger. The $1 increase in cost decreases the supply by – 200,000 * $1, or – 200,000 tablets,
so the supply curve shifts to the left by 200,000 tablets. The $1 increase in income increases
the demand by 1,000 * $1, or 1,000 tablets, so the demand curve shifts to the right by
1,000 tablets. The decrease in supply is larger than the increase in demand, so the quantity
of tablets decreases.

SOLVED
PROBLEM

M02_BLAI8235_01_SE_C02_pp033-085.indd 70 23/08/17 9:49 AM

2.6 Price Controls  71

makes the equilibrium rent illegal.11 The law forces the rent down, from $800 to $600.
As the rent falls, there is a movement along the demand curve from point A to point
C, so that the quantity demanded increases from 1,200 to 1,500 apartments. Simulta-
neously, there is a movement along the supply curve from point A to point B, repre-
senting a decrease in the quantity supplied to 900 apartments. With the lower rent,
some landlords will convert their buildings from apartments to condominiums; oth-
ers may elect to stop renting their basements as apartments because they decide that
with the lower rent, it is simply not worth the hassle. With the rent control, although
tenants want to rent 1,500 apartments, only 900 are rented because that is the quan-
tity supplied. There is a shortage of 600 apartments, or 1,500 demanded minus 900
supplied. If there is no price control, a shortage pushes the price higher. With a price
ceiling, the price cannot rise, however, so the shortage persists indefinitely.

A shortage has two effects:

• Search. Because many buyers are frustrated in their attempt to buy the product,
they search to find it. Search, the activity of finding a seller who has the good or
service available for sale, is costly in terms of both the time and effort spent and
the direct costs, including gasoline and other transportation costs.

• Black markets. As a result of a persistent shortage and the frustration of buyers
who cannot find the product to buy, black markets—markets in which buyers
and sellers illegally purchase and sell goods or services at unlawful prices—
frequently arise.

Price ceilings harm the affected suppliers because they receive a lower price for
their product. Demanders who buy the product at the lower ceiling price and do not
have to undertake much search benefit from a price ceiling. Demanders who either can-
not find the product at all or wind up paying substantial search costs before buying it
are harmed. As you learned in Section 2.4, society is worse off because the rent control
forces the quantity away from the efficient amount, thereby creating a deadweight loss.

Search The activity of
finding a seller who has
the product available for
sale.

Black market A market in
which buyers and sellers
illegally purchase and sell
goods or services at
unlawful prices.

Price (rent per month)

Quantity (apartments per month)

$200

$400

$600

$800

$1,000

$1,200

300 600 900 1,200 1,500 1,800 2,1000

Shortage

S

A

B C

D

Price
ceiling

Figure 2.19 A Price Ceiling

Without a price ceiling, the equilibrium rent is $800
per month, and the equilibrium quantity is 1,200
apartments rented per month. If the government
imposes a price ceiling of $600 per month, the
quantity of apartments demanded is 1,500 (point C),
and the quantity supplied is only 900 (point B). There
is a shortage equal to the length of the light red
double-headed arrow, which is 1,500 apartments
minus 900 apartments, or 600 apartments per month.

11 If the price ceiling is set above the equilibrium price, it has no effect: Because the equilibrium price
remains legal, the price remains at its equilibrium.

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72  CHAPTER 2 Demand and Supply

Price Floor
The government has imposed price floors in the markets for some agricultural prod-
ucts. The minimum wage in the labor market is another example of a price floor. In
this section, we examine the effects of both of these price floors.

Price Floor in an Agricultural Market
Figure 2.20 shows the market for peanuts. Suppose that in the absence of government
intervention, the equilibrium price is $520 per ton of peanuts, and the equilibrium
quantity is 1.6 million tons per year. Further suppose that the government imposes a
price floor of $535 per ton. This price floor is above the equilibrium price of $520 and
makes the equilibrium price illegal.12 The price must rise from the equilibrium price
to the floor price of $535. As Figure 2.20 shows, the price rise creates a movement
along the supply curve from point A to point C and increases the quantity supplied to
2.2 million tons per year. The price rise also creates a movement along the demand
curve from point A to point B and decreases the quantity demanded to 1.0 million
tons per year. With the price floor, peanut consumers buy only 1.0 million tons of pea-
nuts. There is a surplus of peanuts equal to 2.2 million tons supplied minus 1.0 mil-
lion tons demanded, or 1.2 million tons. If there was no price floor, a surplus would
push the price lower. With a price floor, the price cannot fall, so the surplus persists
indefinitely.

To maintain the price floor in agricultural markets, the government must some-
how take the surplus off the market. At times, it has done so by paying farmers not
to grow the crop, which decreases the supply and eliminates the surplus before it
occurs. At other times, it has purchased the surplus and either stored it or used it as
food aid abroad. Because the government removes the surplus, all producers gain
from a price floor because they receive a higher price. All demanders lose from a
price floor because they pay a higher price.

12 If the price floor is set below the equilibrium price, it has no effect: Because the equilibrium price
remains legal, the price remains at its equilibrium.

Price (dollars per ton of peanuts)

Quantity (millions of tons of peanuts per year)

$510

$520

$530

$540

$550

$560

0.4 0.8 1.2 1.6 2.0 2.4 2.80

Surplus

S

B C

A

D

Price
floor

Figure 2.20 A Price Floor

Without a price floor, the
equilibrium price is $520
per ton of peanuts, and the
equilibrium quantity is
1.6 million tons of peanuts
per year. If the government
imposes a price floor of $535
per ton, the quantity of
peanuts supplied is 2.2 million
tons (point C), and the quantity
demanded is only 1.0 million
tons (point B). There is a
persistent surplus of peanuts
equal to the length of the
green doubled-headed arrow,
1.2 million tons of peanuts
per year.

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2.6 Price Controls  73

Minimum Wage in the Labor Market
To this point, the discussion has dealt exclusively with markets for the products
firms produce. But there also are markets for the inputs firms use, such as labor.
These markets are often highly competitive, especially for low-skilled labor. There is
a significant difference between product markets and input markets: In a product
market, households demand the product, and firms supply it. In an input market,
such as the labor market, households supply labor, and firms demand it. Even with
this difference, the law of demand and the law of supply still apply in labor markets:

• The law of demand in the labor market. When the wage rate rises and nothing
else changes, workers become more expensive to employ. Managers respond to
the increased cost by decreasing the quantity of labor they demand. Similarly,
when the wage rate falls and nothing else changes, managers increase the quan-
tity of labor they demand. The downward slope of the labor demand curve, LD,
in Figure 2.21 shows this inverse relationship between wage rate and quantity of
labor demanded.

• The law of supply in the labor market. When the wage rate rises and nothing
else changes, some people respond by increasing the hours they will work. In addi-
tion, people who were not working at the lower wage rate decide that the higher
wage rate will make it worthwhile to take a job. As a result, workers increase the
quantity of labor supplied when the wage rate rises. Conversely, when the wage
rate falls and nothing else changes, workers decrease the quantity of labor they sup-
ply. This direct relationship between wage rate and quantity of labor supplied is
illustrated by the upward slope of the labor supply curve, LS, in Figure 2.21.

The minimum wage can have an effect in the market for low-skilled labor. In the
absence of government intervention, in Figure 2.21 the equilibrium wage rate and
employment are determined at point A, where the labor demand and labor supply
curves intersect. In this case, the equilibrium wage rate is $10 an hour, and the equi-
librium quantity is 40 million hours of labor per year.

Wage rate (dollars per hour)

Quantity (millions of hours of labor per year)

$5

$10

$15

$20

$25

$30

10 20 30 40 50 60 700

Unemployment

LS

B C

A

LD

Minimum
wage

Figure 2.21 A Minimum Wage

Without a minimum wage, the equilibrium wage
rate is $10 per hour, and the equilibrium quantity is
40 million hours of labor per year. If the government
sets a minimum wage of $20 per hour, the quantity of
labor supplied is 50 million hours (point C), and the
quantity demanded is only 20 million hours (point B)—
that is, 20 million hours of labor are employed. There
is a surplus, or unemployment, of 30 million hours
per year, equal to the length of the light red double-
headed arrow.

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74  CHAPTER 2 Demand and Supply

The federal government and many state and local governments have estab-
lished minimum wage laws for the labor market. A minimum wage is the lowest
legal wage rate an employer can pay a worker. It is effectively a price floor in the
labor market. Proponents of minimum wages sometimes call them “living
wages.”

Suppose that the government imposes a minimum wage of $20 per hour in the
labor market, as illustrated in Figure 2.21. Because the minimum wage is set above
the equilibrium wage rate, it makes the equilibrium wage rate illegal and therefore
changes the outcome in the labor market.13 The lowest wage rate that can be paid (or
received) is $20 per hour, so the wage rate must rise from its equilibrium value of $10
per hour. The rise in the wage rate creates a movement along the labor supply curve
from point A to point C and increases the quantity of labor supplied to 50 million
hours per year. The rise in the wage rate also creates a movement along the labor
demand curve from point A to point B and decreases the quantity of labor demanded
to 20 million hours per year. The quantity of labor employed with the $20 minimum
wage is 20 million hours per year, the quantity that firms demand. At the minimum
wage, there is a surplus of 30 million hours of labor, equal to 50 million hours of
labor supplied minus 20 million hours of labor employed. This surplus of hours rep-
resents unemployment: Workers are searching for work but are unable to find it
because of the lower demand.

Unlike the situation in agricultural markets, the government does not employ
the surplus of labor. The workers remain unemployed. Consequently, not all low-
skilled workers gain from the minimum wage. Workers who retain their jobs receive
a higher wage rate, so they gain. Workers who lose their job and cannot find
another or find one only after a long and costly search lose. Of course, all employers
who hire low-skilled workers lose because they must pay a higher wage rate.

Minimum wage The
lowest legal wage rate an
employer can pay a
worker.

13 Similar to the situation with a price floor, if the minimum wage is set below the equilibrium wage rate,
the minimum wage has no effect: Because the equilibrium wage rate remains legal, the wage rate remains
at its equilibrium.

The Effectiveness of a Minimum Wage

In Figure 2.21, the initial equilibrium wage is $10 per hour, and employment is 40 mil-
lion hours per year.

a. Suppose that the government sets a minimum wage of $5 per hour. What effect
does this minimum wage have on the wage rate and quantity of employment? Draw
a graph to support your answer.

b. Suppose that the government sets a minimum wage at $15 per hour. What effect
does this minimum wage have on the wage rate and quantity of employment? Draw
a graph to support your answer.

Answer

a. The minimum wage has been set below the equilibrium wage so it will have no
effect. In particular, your figure should look similar to Figure a. It shows that at the
minimum wage of $5 per hour, the quantity of labor demanded, 50 million hours,
exceeds the quantity supplied, 35 million. At this wage rate, there is a shortage.
Nothing prevents the wage rate from rising, so the shortage pushes the wage rate

SOLVED
PROBLEM

M02_BLAI8235_01_SE_C02_pp033-085.indd 74 23/08/17 9:49 AM

Wage rate (dollars per hour)

Quantity (millions of hours of labor per year)

$5

$10

$15

$20

$25

$30

10 20 30 40 50 60 700

LS

LD

Minimum
wage

back to its initial equilibrium level, $10 per hour. Once at the equilibrium wage,
employment remains equal to 40 million hours per year.

b. The minimum wage has been set above the equilibrium wage, so it will have an effect.
Your figure should look similar to Figure b. The wage becomes $15 per hour, the minimum
wage. At this wage rate, the quantity of labor supplied, 45 million hours, exceeds the
quantity demanded, 30 million. So employment is 30 million hours per year, the quantity
of labor firms will hire, and unemployment (a surplus) is 15 million hours per year,
shown in Figure b by the double-headed arrow. Unemployment persists because the
wage rate cannot fall, since $15 per hour is the minimum legal wage.

(a) (b)

Wage rate (dollars per hour)

Quantity (millions of hours of labor per year)

$5

$10

$15

$20

$25

$30

10 20 30 40 50 60 700

LS

LD

Minimum
wage

2.7 Managerial Application: Using the Demand and Supply Model  75

2.7 Using the Demand and Supply Model
Learning Objective 2.7 Apply the demand and supply model to make better
managerial decisions.

As a manager, you can use the demand and supply model to predict how the costs or
the price of your product might change. Let’s begin by exploring how the model can
help you predict your costs and thereby increase your profit.

Predicting Your Costs
Kellogg Company, a major cereal and cookie manufacturer based in Battle Creek,
Michigan, buys tons of corn annually. Because corn is a significant expense for the
firm, its purchasing managers carefully monitor corn prices. Although Kellogg is a
major corn buyer, the market for corn is so huge that the firm has no influence on its
price. Suppose that a similar company employs you in its purchasing department.
Your company also has no influence on the price of corn, but just like Kellogg’s pur-
chasing managers, you, too, will carefully monitor the market for corn.

MANAGERIAL
APPLICATION

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76  CHAPTER 2 Demand and Supply

Between 2004 and 2008, oil prices rose from $40 per barrel to near $90. In response,
the U.S. Congress passed the Energy Policy Act of 2005 and the much more ambitious
Energy Independence and Security Act of 2007. These laws required refineries to add
renewable fuels, largely ethanol, to the gasoline they refined. Within four years, this
legal requirement nearly tripled the amount of ethanol produced, from 3.5 billion gal-
lons in 2004 to 9.3 billion gallons in 2008. In the United States, corn is the primary input
used to produce ethanol. The demand and supply model provides a straightforward
way to determine how passage of these laws affected the price (and quantity) of corn.

As ethanol producers stepped up their purchases of corn to make more ethanol,
there was a vast increase in the number of buyers of corn. You have learned that an
increase in the number of buyers increases the demand and shifts the demand curve
to the right. As illustrated in Figure 2.22, from 2006 to 2007 the increase in demand
raised the price of corn from an average of about $3.50 per bushel to $5.00 per
bushel. This change also increased the quantity, but the key for you as a purchaser is
the higher price you will be forced to pay. Knowing that the price of corn will rise in
response to the passage of these laws gives you a potential edge: If you can buy corn
using a long-term contract before the price rises, you can save your company a sub-
stantial sum of money. Of course, people in the purchasing departments of other
companies and major growers of corn will also be alert to the possibility of a higher
price, so you will need to act quickly to scoop up any savings. But it’s clear how
using the demand and supply model gives you an opportunity to reduce your costs.

Predicting Your Price
In addition to providing information about the inputs you buy, the demand and sup-
ply model can give you key insights into changes in the price of the products and
services you sell. Suppose that you are an executive working for a company like Toy-
ota. You are overseeing the pricing and production of hybrid cars like Toyota’s Prius.
Your firm, of course, is one of many automakers producing and selling hybrids. A
crucial selling point of hybrids is their notable fuel economy. For example, many

Price (dollars per bushel of corn)

Quantity (billions of bushels of corn per year)

$1.00

$2.00

$3.00

$4.00

$5.00

$6.00

$7.00

2.5 5.0 7.5 10.0 12.5 15.0 17.50

S

D1

New
equilibrium

Initial
equilibrium

D0

Figure 2.22 The Market for
Corn

When the government
passed laws requiring that
refineries add ethanol to
gasoline, the demand for
corn increased, and the
demand curve for corn
shifted to the right, from D0
to D1. This shift raised the
price of corn, which has
the potential to raise your
company’s costs
dramatically.

M02_BLAI8235_01_SE_C02_pp033-085.indd 76 23/08/17 9:49 AM

hybrid models have EPA fuel economy ratings over 50 mpg. Consumers view hybrids
as substitutes for gasoline-powered cars—they buy hybrids to avoid buying as much
gasoline as they would if they purchased a gasoline-powered car. So the demand for
hybrids depends on the price of gasoline. Since it reached its peak of near $4.00 per
gallon in 2012, the price of gasoline has fallen substantially. This remarkable decrease
in price has reduced the cost of operating a gasoline-powered car. Suppose that gov-
ernment analysts forecast that gasoline prices will remain low for the next several
years and your research department agrees with this prediction. How can you use the
demand and supply model to increase your profit?

Because hybrids are a substitute for gasoline-powered cars, the lower price of
gasoline decreases the demand for hybrids. In Figure 2.23, the demand curve for
hybrids shifts left, from D0 to D1. The decrease in demand lowers the price and
quantity of hybrid cars. Knowing that the price and quantity will decrease in the
future allows you to make better, more informed decisions. You can take several
approaches in order to produce fewer hybrids:

• You might begin planning to run one shift a day on the assembly lines produc-
ing hybrids rather than two.

• You could explore converting assembly lines away from producing hybrids and
toward producing more popular vehicles.

• You might try to make deals with your suppliers to decrease purchases of hybrid
components, such as batteries, so they will not pile up in inventory, where they
could depreciate due to technological obsolescence or simply aging.

• The federal government has imposed Corporate Average Fuel Economy regula-
tions that automakers must meet. These standards set average-miles-per-gallon
requirements for the automakers’ fleets of small cars, small trucks, large cars,
and large trucks. Knowing that the demand for high-mpg hybrid cars will
decrease means you must take other actions to meet these targets.

Using the demand and supply model can allow you to make decisions such as
these that can help increase your firm’s profit.

Price (thousands of dollars per hybrid car)

Quantity (thousands of hybrid cars per year)

$15

$20

$25

$30

$35

$40

50 100 150 200 250 300 3500

S

D0

Initial
equilibrium

New
equilibrium

D1

Figure 2.23 The Market for
Hybrid Cars

When the price of gasoline
falls, the demand for hybrid
cars decreases, so the
demand curve shifts to the
left, from D0 to D1. This shift
lowers both the price and the
quantity of hybrid cars.

2.7 Managerial Application: Using the Demand and Supply Model  77

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78  CHAPTER 2 Demand and Supply

Revisiting How Managers at Red Lobster Coped with Early
Mortality Syndrome

At the start of the chapter, you learned that early mor-tality syndrome (EMS) in Asia affected the supply
of shrimp. Using what you have learned in this chapter,
you can classify EMS as a bad state of nature. A bad
state of nature decreases supply, so you know that the
supply curve for shrimp shifts to the left. Thailand is the
world’s largest shrimp exporter. EMS caused the price
of Thai shrimp to rise about 40 percent, from $4,500 to
$6,000 per ton of shrimp, as shown in Figure 2.24. It also
decreased the quantity of shrimp from 600 thousand tons
to 300 thousand tons per year.

Using this sort of analysis, Red Lobster’s managers
realized that EMS was a potentially severe problem even

before it spread from its initial location in China. Using
demand and supply analysis, the managers knew that the
price of shrimp might soar. They quickly arranged to buy
shrimp under long-term contracts at a fixed price, lock-
ing in the price before other buyers and sellers of shrimp
realized that the price was soon to skyrocket. Once other
buyers and sellers learned that the price of shrimp was
heading up, its price under new long-term contracts also
rose. As EMS spread, the price of shrimp rose, as analyzed
above. But the long-term contracts temporarily insulated
Red Lobster from the higher price. The managers’ use of
the demand and supply model significantly increased profit
for Red Lobster.

Price (dollars per ton of shrimp)

Quantity (thousands of tons of shrimp per year)

$1,500

$3,000

$4,500

$6,000

$7,500

$9,000

150 300 450 600 750 900 1,0500

S0

Initial
equilibrium

New
equilibrium

D

S1

Figure 2.24 A Decrease in the Supply of Shrimp

When the supply of shrimp decreases, the supply
curve shifts to the left, from S0 to S1. This shift
raises the price of shrimp, from $4,500 per ton to
$6,000 per ton, and decreases the quantity of
shrimp, from 600 thousand tons to 300 thousand
tons per year.

Summary: The Bottom Line

2.1 Demand
• The law of demand states that, everything else remain-

ing the same, a higher price decreases the quantity
demanded and a lower price increases the quantity
demanded. This law explains the downward slope of
the demand curve.

• A change in the price of a product results in a change in
the quantity demanded and a movement along the

demand curve. Changes in other relevant factors—
including consumers’ income, the price of related goods
and services, consumers’ preferences and advertising,
financial market conditions, the expected future price of
the product, and the number of demanders—change the
demand and shift the demand curve. If demand
increases, the demand curve shifts to the right. If
demand decreases, the demand curve shifts to the left.

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Key Terms and Concepts  79

2.2 Supply
• The law of supply states that, every else remaining the

same, a higher price increases the quantity supplied
and a lower price decreases the quantity supplied. This
law explains the upward slope of the supply curve.

• A change in the price of a product results in a change in
the quantity supplied and a movement along the sup-
ply curve. Changes in other relevant factors—including
cost, the price of related goods or services, technology,
the state of nature, the expected future price of the
product, and the number of suppliers—change the
supply and shift the supply curve. If supply increases,
the supply curve shifts to the right. If supply decreases,
the supply curve shifts to the left.

2.3 Market Equilibrium
• In the demand and supply model, the intersection of

the demand and supply curves determines the equilib-
rium price and quantity. The equilibrium price sets the
quantity demanded equal to the quantity supplied. The
equilibrium quantity is the quantity bought and sold at
the equilibrium price.

• The market price is the equilibrium price, and the mar-
ket quantity transacted is the equilibrium quantity.

2.4 Competition and Society
• Perfectly competitive markets are socially optimal

because the equilibrium quantity maximizes society’s
total surplus of benefit over cost from the product. Pro-
ducing more or less than the equilibrium quantity
decreases the total surplus by creating a deadweight loss.

• Consumer surplus is the difference between the maxi-
mum price consumers are willing to pay and the price
they actually pay, summed over the quantity con-
sumed. Producer surplus is the difference between the
price the firm actually receives and the lowest price it
would be willing to accept to produce the product,
summed over the quantity produced. The total surplus
is the sum of the consumer surplus and the producer
surplus.

2.5 Changes in Market Equilibrium
• To use the demand and supply model to predict how

changes in relevant factors affect the price and quantity
of a product, determine whether the factor changes
demand and/or supply and whether it causes an
increase or a decrease.

• If only demand or only supply changes, the demand
and supply model shows how both the price and the
quantity change. If both the demand and the supply
change, the demand and supply model unambiguously
predicts changes in either price or quantity. Without
information about the relative size of the changes, the
change in the other variable is ambiguous.

2.6 Price Controls
• Price ceilings set the maximum legal price. If a price

ceiling is set below the equilibrium price, the new
price in the market becomes the ceiling price, and a
shortage results. The shortage leads to increased
search and the creation of black markets.

• Price floors set the minimum legal price. Price floors are
often set in agricultural markets and in the labor mar-
ket. If a price floor is set above the equilibrium price,
the new price in the market becomes the floor price,
and a surplus of the product results. In agricultural
markets, the government buys the surplus to maintain
the price floor. In the labor market, the labor surplus is
unemployment.

2.7 Managerial Application: Using the
Demand and Supply Model

• The demand and supply model can help guide pur-
chasing and production decisions.

• The demand and supply model can help you predict
when the price of inputs will rise or fall, thereby leading
you toward profitable decisions about when to buy them.
The model can also help you predict the future price of a
product, enabling you to make profitable decisions about
whether to expand or contract your business or when to
increase or decrease your production.

Key Terms and Concepts
Black market

Complements

Complements in production

Consumer surplus

Deadweight loss

Demand curve

Demand function

Efficient quantity

Equilibrium

Equilibrium price

Equilibrium quantity

Income effect

Inferior good or service

Market

Minimum wage

Normal good or service

Price ceiling

Price floor

Producer surplus

Search

Substitutes

Substitutes in production

Substitution effect

Supply curve

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80  CHAPTER 2 Demand and Supply

Questions and Problems
All exercises are available on MyEconLab; solutions to even-numbered Questions and Problems appear in the back of

this book.

2.1 Demand
Learning Objective 2.1 Describe the factors
that affect the demand for goods and services.

1.1 Which represents the law of demand: a shift of
the demand curve or a movement along the
demand curve? Explain your answer.

1.2 “Romaine lettuce is far more nutritious than ice-
berg lettuce. Therefore, iceberg lettuce is an infe-
rior good.” Is this description of iceberg lettuce
as an inferior good correct in economic terms?
Explain your answer.

1.3 Suppose that banks increase the amount of infor-
mation they require from potential borrowers
before approving car loans. How would this
change affect the demand curve for automobiles?

1.4 What effect does each of the following have on
the demand curve for jeans?
a. A decrease in income if jeans are a normal good
b. A fall in the price of jeans
c. A rise in the price of cargo pants, a substitute

for jeans
d. A widespread perception that wearing jeans

is not as fashionable as it once was

1.5 Your firm, Content Colleague, is similar to Happy
Worker, a Canadian company that designs and
manufactures toys and collectibles. Your research
analyst has estimated the demand function for
your stuffed toy animals is

Qd = 30 million – 12 million * P2
a. If you set the price of a plush toy at $5, how

many will consumers buy?
b. If you increase the price of a plush toy by $1,

how will this change the quantity that your
customers buy?

2.2 Supply
Learning Objective 2.2 Describe the factors
that affect the supply of goods and services.

2.1 What is the difference between cost and price? If
the cost of producing a good or service rises,
what is the effect on the supply curve? What is
the effect on the supply curve of an increase in
the price of the good or service?

2.2 How does an increase in the price of the cheese
used to produce pizza affect the supply curve of
pizza?

2.3 Toyota’s factory in Georgetown, Kentucky, can
use its assembly lines to produce either the Toy-
ota Camry or the Camry Hybrid.
a. For this Toyota factory, are the Camry and

Camry Hybrid substitutes in production or
complements in production?

b. How will the supply of the Camry respond to
an increase in the price of the Camry Hybrid?

2.4 What effect does each of the following have on
the supply curve of jeans?
a. A rise in the price of transporting the jeans

from Thailand, where they are made, to the
United States, where they are sold

b. A fall in the wages paid the workers who sew
jeans

c. A rise in the price of jeans
d. An increase in the number of companies

manufacturing jeans

2.3 Market Equilibrium
Learning Objective 2.3 Determine the market
equilibrium price and quantity using the
demand and supply model.

3.1 Among all possible prices, what makes the equi-
librium price unique?

3.2 If the price in a market is less than the equilibrium
price, what happens to restore the equilibrium price?

3.3 The figure shows a hypothetical market for
NFL-caliber punters.
a. How many punters will the NFL hire?

Explain your answer.
b. What salary will these punters receive?

Explain your answer.

Salary (millions of dollars per year)

Quantity (punters per year)

$1

$2

$3

$5

$6

$4

$7

10 20 30 40 50 60 700

S

D

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Questions and Problems  81

3.4 The demand function for a product is
Qd = 1,000 – 10P, and its supply function is
Qs = 100 + 2P. Calculate the equilibrium price
and equilibrium quantity of the good. Check
your answer by drawing the demand and supply
curves in a figure.

2.4 Competition and Society
Learning Objective 2.4 Explain why perfectly
competitive markets are socially optimal.

4.1 Carefully explain how economists
a. Use the demand curve to measure the mar-

ginal social benefit of a good or service.
b. Use the supply curve to measure the mar-

ginal social cost of a good or service.
c. Measure the total surplus of a unit of a good

or service.

4.2 Describe the social gains from competitive
markets.

4.3 Explain how producing less than the equilibrium
quantity decreases society’s total surplus and
how producing more than the equilibrium quan-
tity also decreases society’s total surplus.

2.5 Changes in Market Equilibrium
Learning Objective 2.5 Use the demand and
supply model to predict how changes in the
market affect the price and quantity of a
good or service.

5.1 Does an increase in the price of jet fuel shift the
demand curve for airline travel, the supply
curve of airline travel, or both? Explain your
answer.

5.2 How does a change in people’s preferences in
favor of wearing jeans shift the demand curve
for jeans? The supply curve? How does a
decrease in the number of producers of jeans
shift the demand curve for jeans? The supply
curve?

5.3 High-quality pasta products are made from 100
percent semolina, which is made from durum
wheat. Suppose that a drought decreases the
quantity of durum wheat. Answer each of the
following questions. Draw demand and supply
diagrams to illustrate each answer.
a. How will the drought affect the equilibrium

price and quantity of high-quality spaghetti?
b. How will the drought affect the equilibrium

price and quantity of spaghetti sauces?
c. For consumers, pasta and rice are substitutes.

How will the drought affect the equilibrium
price and quantity of rice?

Price (dollars per television)

Quantity (millions of televisions per year)

$250

$500

$750

$1,000

$1,250

$1,500

20 40 60 80 100 120 1400

S1

D

S0

5.4 Peanut butter and jelly are complements for
consumers. What happens to the equilibrium
price and quantity of jelly if the peanut har-
vest is especially bountiful? Explain your
answer, and illustrate it with a demand and
supply figure.

5.5 The figure shows the market for televisions. The
initial supply curve is S0. After a change occurs,
the supply curve becomes S1.

a. Before the change occurs, what were the ini-
tial equilibrium price and quantity? After
the change occurs, what are the new equilib-
rium price and quantity?

b. Give an example of a change that could lead
to the shift illustrated in the figure.

c. Based on your answer to part b, if you are an
executive at a firm like LG Corporation, a
Korean manufacturer of televisions, what
managerial decisions will you make?

5.6 Baseball gloves are made from cowhide. Sup-
pose that reports of bovine spongiform encepha-
lopathy (mad cow disease) have decreased the
demand for beef. Using a demand and supply
diagram, explain the impact of mad cow disease
on the equilibrium price and quantity of base-
ball gloves.

5.7 Suppose that you own Lauderdale Aerial Spray-
ing, a large Texas crop-dusting company.
Drones are able to spray crops at lower cost
than manned planes. Currently, Federal Avia-
tion Administration (FAA) regulations prohibit

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82  CHAPTER 2 Demand and Supply

the use of drones for crop dusting or other preci-
sion agricultural use.
a. If the FAA eliminates these regulations, what

will happen to the price and quantity of crop
spraying? Explain your answer using a
demand and supply figure.

b. If the FAA eliminates these regulations, what
will happen to the price and quantity of soy-
beans, which require regular spraying?
Explain your answer using a demand and
supply figure.

5.8 As an executive with KB Home, a large home
builder, you know that new homes are a normal
good and that incomes are growing. Builders
use plywood in the construction of new homes,
and the price of plywood has soared because of
environmental restrictions on logging. What do
you expect will happen to the equilibrium price
and quantity of new homes? Use demand and
supply figures to help explain your answer.

5.9 The demand function for pork is Qd = 300 –
100P + 0.01INCOME, where Qd is the tons of
pork demanded in your city per week, P is
the price of a pound of pork, and INCOME
is the average household income in the city.
The supply function for pork is Qs = 200 +
150P – 30COST, where Qs is the tons of pork
supplied in your city per week, P is the price of a
pound of pork, and COST is the cost of pig food.
a. If INCOME is $50,000 and COST is $5, what

are the equilibrium price and quantity of
pork?

b. If INCOME falls to $40,000 and COST does
not change, what are the new equilibrium
price and quantity of pork?

c. If INCOME is $50,000 and COST rises to $10,
what are the new equilibrium price and
quantity of pork?

d. If INCOME is $40,000 and COST is $10, what
are the new equilibrium price and quantity of
pork?

5.10 Suppose that a competitive market is in equilib-
rium and the firms in this industry employ many
workers who are paid the minimum wage.
a. If Congress raises the minimum wage that

the firms must pay their workers, what hap-
pens to the equilibrium price and output?

b. What happens to the consumer surplus?

2.6 Price Controls
Learning Objective 2.6 Explain the effects of
price ceilings and price floors.

6.1 Why does a price ceiling set above the equilib-
rium price have no effect on the market?

6.2 Why is an increase in the minimum wage apt to
affect teenagers more than other age groups?

6.3 Suppose that you are a manager working for Yum
in the Taco Bell division. Taco Bell employs many
employees at the minimum wage. If the mini-
mum wage is already set above the equilibrium
wage rate and then the government raises it still
higher, what are the effects in the labor market?
How do the changes in the labor market affect
Taco Bell?

2.7 Managerial Application: Using The
Demand and Supply Model
Learning Objective 2.7 Apply the demand
and supply model to make better manage-
rial decisions.

7.1 You are a manager at a firm like Whirlpool in a
market with other manufacturers of refrigerators.
The figure shows the initial market demand and
supply curves for refrigerators. You know that
refrigerators are a normal good and income is
increasing, so the demand for refrigerators will
change by 100,000 at every price.

Price (dollars per refrigerator)

Quantity (thousands of refrigerators per year)

$250

$500

$750

$1,000

$1,250

$1,500

50 100 150 200 250 300 3500

S

D

a. What are the initial equilibrium price and
quantity of refrigerators? After the change in
income, what are the new equilibrium price
and quantity?

b. Based on your answer to part a, what mana-
gerial decisions might you make?

7.2 In Section 2.7, you learned how to analyze the
effect on cereal producers of laws that required

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MyLab Economics Auto-Graded Excel Projects  83

the addition of significant amounts of ethanol to
gasoline. Suppose that at the same time these
laws were passed, consumers’ incomes increased.
If name-brand cereal, such as that produced by
Kellogg, is a normal good, what will be the
impact on the price and quantity? Use a demand
and supply figure as part of your answer.

7.3 Ethanol producers persistently lobby the govern-
ment to issue regulations increasing the amount
of ethanol that oil refiners must add to gasoline.
Using the demand and supply model, explain
why ethanol producers lobby the government for
these regulations.

7.4 Young adult males drink more beer than other
age and gender groups. Why do executives at
breweries track the demographics of the various
nations in which they operate?

7.5 Say that you are a manager working for a casual
dining chain similar to Brinker International
Restaurants’ chain of Chili’s restaurants. Just
like Chili’s, baby back ribs are one of your major
sale items. Baby back ribs come from pigs.
Answer each of the following questions inde-
pendently; that is, when answering part b,
assume that the situation in part a is not occur-
ring. Use demand and supply figures to explain
your answers.
a. You read that droughts are raising the price

of corn and soy, both major foodstuffs for
pigs. What action(s) should your firm take?

b. Dining out at casual restaurants such as
Chili’s or your restaurant is a normal good.
You read predictions that the economy will
soon sink into a recession, with people’s
incomes falling. What do you expect will hap-
pen to the price and quantity of dining at
casual restaurants?

c. Upper management has asked you to pre-
pare recommendations for the next one to
two years. You read that droughts are raising
the price of corn and soy and that the econ-
omy will soon enter a recession. Based on
what you have discovered, what will happen
to the price and quantity of casual dining?
What managerial recommendation(s) will
you make to your superiors?

7.6 Increased consumption of natural foods by pet
owners has led to increased demand for natural
foods for their pets. The Colgate-Palmolive
Company produces and sells Hill’s Science Diet
cat food. Suppose that you work for a similar
company, also producing “scientific” cat food.
Your marketing team presents research showing
that consumers do not consider so-called scien-
tific cat food natural. Based on the trend toward
natural cat foods, what do you expect will hap-
pen to the equilibrium price and quantity of sci-
entific cat food? Based on this result, what
recommendation(s) would you make to top
management?

MyLab Economics Auto-Graded Excel Projects
2.1 Saxum Vineyard, in Paso Robles, CA, is one of

the more than 8,000 wineries in the United States.
While Saxum produces a number of different
kinds of wine, it focuses its production on Syrah
(also known as Shiraz). Saxum sells its wines all
over the United States. Suppose the market
demand function for Syrah is as follows.

Qd = 200 – 38.18P + 8.35PS – 2PC +
10INC + 0.8TS + 0.5M21

where Qd is the monthly demand for bottles of
Syrah (in millions), P is the price of Syrah, PS is
the average price of substitute bottles of wine
(other varieties), PC is the average price of a
pound of cheese and is used to gauge the price
of complementary goods, INC is average U.S.
income (in thousands of dollars), TS is the num-
ber of wine trade shows and competitions each
year that firms can attend to market their wines,
and M21 is the number (in millions) of millenni-

als over the age of 21. This last variable captures
a change in consumer preferences; millennials are
drinking wine at a much higher rate than previ-
ous generations.
The market for Syrah also has supply, pro-
duced by Saxum Vineyard and other wineries,
which can be stated as follows:

Qs = – 100 + 22.93P – 5PPI – 10PS +
8TEMP + 1SUP

where Qs is the monthly supply of bottles of
Syrah (in millions), P is the price of Syrah, PPI
is the Producer Price Index (an index used to
gauge changes in the costs of production in the
United States), PS is the price of substitute wines
that could easily be produced instead of Syrah,
TEMP is the expected temperature during the
harvest season for grapes, and SUP is the number
of wineries that supply Syrah in the market (in
thousands).

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84  CHAPTER 2 Demand and Supply

Using the market supply and demand func-
tions for Syrah, fill in the template provided with
the coefficient for each function. Using the infor-
mation below, fill in the value for each of the vari-
ables except Price of Syrah. Then set up your Qd
and Qs to automatically calculate as you adjust
the values for each variable.

Demand:

• Price of substitutes: $18
• Price of cheese: $15
• Income: $53,000
• Trade shows: $3
• Millennials = 43 million

Supply:

• PPI: 111
• Price of substitutes: $18
• Temperature: 60
• Number of suppliers: 8,000

Now that you have set up your demand and
supply functions, answer the following questions:
1. When the price of Syrah increases by $1, what

is the effect on quantity demanded and quan-
tity supplied?

2. How much does a $1 decrease in the price of
substitute bottles of wine shift the demand
and supply curves?

3. Suppose that the price of Syrah is currently
$22 per bottle. How many bottles will be
demanded and supplied monthly? Is there a
shortage or surplus and of how much?

4. If the market price of Syrah falls to $16 per
bottle, how many bottles will be demanded
and supplied monthly? Is there a shortage or
surplus and of how much?

5. Trying prices in $1 increments between $16
and $22, at what price and quantity does the
market equilibrium occur?

6. Suppose that the PPI increases to 123.222.
If the price of wine stays at $20 per bottle,
what quantity will be supplied in the mar-
ket, and will the increase in the PPI create
a shortage?

7. With the increase in PPI to 123.222, at what
price will the market be in equilibrium? What
quantity will be demanded and supplied at
this price?

2.2 We are going to use Excel to examine changes in
the consumer and producer surpluses in a
competitive market when the market is not in
equilibrium. Consider the market for corn in
the United States. Suppose the demand and
supply functions for corn are as follows:

Qd = 100 – 14.5P
Qs = 0 + 5.5P

where Q is bushels of corn (in billions) and P is
the market price per bushel.
Using the template provided, enter the coef-
ficients for demand and supply, and set up
your Qd and Qs to automatically calculate as
you adjust the value for price. When the mar-
ket is not at its equilibrium, the amount sold in
the market will be the minimum of the quan-
tity demanded and the quantity supplied. So
to determine the quantity sold, use Excel ’s
MIN function, and set the cell reference to Qd
and Qs.
Set up Excel to calculate consumer surplus
(CS), producer surplus (PS), and total surplus
(TS) for you using the following formulas:

CS = .5*(Demand Intercept – Price)*Total Sold
in Market
PS = .5*Price*Total Sold in Market
TS = CS + PS

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Once you have this set up, answer the following
questions:
1. Start at a price of $3 per bushel, and increase

the price in $0.50 increments until you reach
market equilibrium. What are the equilib-
rium price and quantity?

2. What happens to the consumer, producer,
and total surpluses as you increase the price
from $3 to the equilibrium?

3. Now increase the price from the equilibrium
by $0.25 two times. What happens to the
market quantity and the consumer, producer,
and total surpluses as you increase the price
to a level higher than the equilibrium?

4. Do these results support the discussion in
the text about overproduction, underpro-
duction, and the efficient market quantity?
Explain why or why not.

MyLab Economics Auto-Graded Excel Projects  85

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C
H

A
P

T
E

R

3 Measuring and Using Demand
Learning Objectives
After studying this chapter, you will be able to

3.1 Explain the basics of regression analysis.
3.2 Interpret the results from a regression.
3.3 Describe the limitations of regression analysis and how they affect its use by managers.
3.4 Discuss different elasticity measures and their use.
3.5 Use regression analysis and the different elasticity measures to make better managerial

decisions.

Managers at the Gates Foundation Decide to Subsidize
Antimalarial Drugs

The Bill and Melinda Gates Foundation (Gates Foundation) is the world’s largest philanthropic organization, with
a trust endowment of nearly $40 billion. The foundation
provides grants for education, medical research, and vac-
cinations around the world. As of 2015, the foundation
had made total grants of $37 billion. The goal of the Gates
Foundation is not maximizing profit. Instead, its goal is to
save lives and improve health in developing countries.

In 2010, the Global Fund to Fight AIDS, Tuberculosis
and Malaria presented proposals to the Gates Foundation
to subsidize antimalarial drugs in Kenya and other nations
of sub-Saharan Africa. Although the Gates Foundation pro-
vides nearly $4 billion in grants per year, there are more
than $4 billion worth of competing uses for its resources.
Consequently, before the managers accepted these
proposals, they needed to determine their expected
impact: How many people would these projects save
compared to alternative uses of the funds? The managers

realized that lives hinged on their decision, so they wanted
to be certain that they were getting the most value for
their money.

The proposed subsidy programs would lower
the price patients pay for the drugs. As you learned in
Chapter 2, according to the law of demand, a decrease in
the price of a product increases the quantity demanded.
Antimalarial drugs are no exception; if their price falls,
more patients will buy them. To make the proper decision
about the proposals, however, the foundation’s manag-
ers needed a more quantitative estimate: Precisely how
many additional patients would buy the drugs when their
prices were lower?

This chapter explains how to answer this and other
questions that require quantitative answers. At the end
of the chapter, you will learn how the Gates Foundation’s
managers could forecast the number of patients they
would help by subsidizing the drugs.

Sources: Karl Mathiesen, “What Is the Bill and Melinda Gates Foundation?” The Guardian. March 16, 2015;
Gavin Yamey, Marco Schaferhoff, and Dominic Montagu, “Piloting the Affordable Medicines Facility-Malaria:
What Will Success Look Like?” Bulletin of the World Health Organization, February 3, 2012, http://www.who
.int/bulletin/volumes/90/6/11-091199/en; Erinstar, “Availability of Subsidized Malaria Drugs in Kenya,” Social and
Behavioral Foundations of Primary Health Care Policy Advocacy, March 11, 2012, https://sbfphc.wordpress
.com/2012/03/11/availability-of-subsidized-malaria-drugs-in-kenya-18-2.

86

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3.1 Regression: Estimating Demand  87

Introduction
According to the law of demand, when you raise the price of your product, the
quantity your customers buy decreases. In some cases, this qualitative information is
all you need to know, but in other cases, you need a more precise estimate. Your de-
cision to raise the price of your product by 10 percent might depend on its impact on
the quantity demanded: Will it decrease by 5 percent or by 20 percent? To make the
best decision, you need more precise information about the demand for your prod-
uct. Understanding how to obtain this information and what it means is important,
but as a manager, knowing how to use it is even more important.

Chapter 3 features two important quantitative concepts: regression analysis
and elasticity. Regression analysis (or, more simply, regression) is a statistical
method used to estimate the relationship between two or more variables.
Regression analysis can be used to estimate the coefficients of the demand func-
tion, the a and b in the equation Qd = a – 1b * P2, or the coefficients of any other
relationship. As a manager, you will probably not conduct the actual regression
analysis, but you will quite likely rely on demand estimates from your marketing
research department. This chapter will help you understand how to interpret those
estimates and use the results of the regression to make predictions and forecasts
that can be important for your business.

Sometimes you will not have the data necessary to use regression analysis. In
those cases, you may be able to use elasticity to help predict consumer response to a
change in your price. For instance, the price elasticity of demand will help you deter-
mine whether your 10 percent price hike will decrease your sales by 5 percent or by
20 percent.

Regression and elasticity build on the concepts presented in Chapter 2 by allow-
ing you as a manager to gain a more quantitative understanding of demand as well
as other important relationships between key variables, such as cost and total pro-
duction. To achieve these important goals, Chapter 3 includes five sections:

• Section 3.1 explains regression analysis, the most common technique for estimating rela-
tionships such as those represented by a demand curve.

• Section 3.2 demonstrates how to interpret regression results, including how to calculate the
range of values within which a regression coefficient is likely to fall, test the hypothesis that
the value of a coefficient equals zero, and measure the fit of the regression.

• Section 3.3 describes weaknesses of regression analysis and how they affect its use.
• Section 3.4 introduces the price elasticity of demand, income elasticity of demand, and

cross-price elasticity of demand, which deal with how strongly consumers respond to
changes in the price of the product, income, and the price of a related good, respectively.

• Section 3.5 demonstrates how you can use regression analysis, price elasticity of de-
mand, income elasticity of demand, and cross-price elasticity of demand to make better
managerial decisions.

3.1 Regression: Estimating Demand
Learning Objective 3.1 Explain the basics of regression analysis.

Chapter 2 illustrated a demand curve for jeans, described algebraically as

Qd = a – 1b * P2

Regression analysis
A statistical method used
to estimate the relationship
between two or more
variables.

Elasticity A measure of
the responsiveness of the
demand for a product to a
change in a factor
affecting the demand.

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88  CHAPTER 3 Measuring and Using Demand

In Figure 2.1 in Chapter 2, the linear demand curve was used to calculate that
the coefficient a was equal to 600 million pairs of jeans and that the coefficient b
was equal to 5 million pairs of jeans per dollar. The negative sign in the equation
reflects the law of demand: A higher price reduces the quantity demanded. As a
manager, however, you will never be given a figure with a linear demand curve
for use to compute these values. Instead, you must use data on the quantity sold
and the price charged to calculate the best estimates for the coefficients. The
method used to make these estimates is regression analysis. Regression is used to
estimate the coefficients of a demand function as well as many important eco-
nomic relationships, such as the relationship between a firm’s quantity and its
cost. Studying the details of regression will help you understand the strengths
and weaknesses of reports submitted to you and thereby help you make better
decisions.

The Basics of Regression Analysis
The Capital Grille is a chain of upscale steak restaurants. Suppose that you are an
upper-level executive working for a similar chain. To make better decisions, you
want to know the demand for your company’s dinners. Assume that the demand
function for steak dinners at your restaurants can be written as

Qd = a – 1b * P2
where Qd is the dependent variable we are predicting and P is the independent variable,
also called the explanatory variable. This is a univariate equation because there is only
one independent variable. Adding other independent variables that affect customer
demand, such as income or the price of a related good, transforms a univariate equation
into a multivariate equation because it includes more than one independent variable.
We use the simpler univariate case to explain regression analysis because the more
complicated—and probably more realistic—multivariate case is similar. The goal of
regression analysis is to estimate the coefficients of the demand function, a and b in
the equation we are using, so that we can find how the dependent variable, Qd,
changes when the independent variable(s) change(s).

The demand equation in this example has only one independent variable, the
price of a dinner (P). Even if you included many other independent variables,
however, you would not be able to precisely replicate the quantities demanded.
There always will be some error because there are inevitably random elements in
demand that you cannot capture. For example, a particularly severe snowstorm
might lead some consumers to eat at home rather than drive to the restaurant.
Alternatively, the popularity of dining at this restaurant chain might skyrocket af-
ter a popular rap artist mentions it in an interview. Because these factors occur
randomly, you will never be able to accurately capture their impact on the demand
for dinners. So you add a random error term to the demand equation to account
for the randomness and get

Qd = a – 1b * P2 + h
where h is the random error term. You will never know for sure what h equals. But
assume that h is random, has a mean (average) of zero, and is normally distributed,
which means it has the usual bell-shaped distribution that you have undoubtedly
seen for variables such as weight or height.

Your goal of obtaining the best estimates for the coefficients a and b now must
take into account the random error term. If you knew that the error term was always
zero, so that a – 1b * P2 always equaled Qd, the restaurant chain’s managers could
set different prices at a few of its locations and collect data on the quantity of dinners

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3.1 Regression: Estimating Demand  89

sold. They could then plot quantities and prices in a standard demand and supply
graph and determine the a and b coefficients from the straight line plotted—a would
equal the horizontal intercept, and b would equal the inverse of the slope, as shown
in Figure 2.1 in Chapter 2.

The presence of the random error term complicates your task. For example,
Figure 3.1 shows 21 hypothetical data points for the price and quantity of steak din-
ners demanded at your restaurants. You can obtain these types of data by setting
different prices at different locations and then collecting data over several months on
the average quantity of dinners sold each day.

The random element of demand makes it impossible to draw a straight line
connecting the scattered points. Even so, Figure 3.1 shows that the points lie
around a negatively sloped straight line, which would be the demand curve.
However, it is possible to draw many lines through this cluster of points. Each
line would give slightly different estimates of the a and b coefficients and there-
fore different estimates of the demand function, Qd = a – 1b * P2. Using only
Figure 3.1, we cannot determine which of these lines best approximates the actual
demand curve.

Regression Analysis
Regression analysis gives estimates for the a and b coefficients—say, an and bn —thereby
choosing one of the many lines through the data points. But which line should it
select? Intuitively, the line that is closest to the data points seems desirable—that is, the
line that makes the difference between the actual quantities, Qd, and the predicted
quantities—say, Qd—as small as possible. Using the actual prices and the estimated an
and bn coefficients in the demand function will give the predicted quantities,
Qd = an – 1bn * P2. The differences between the actual quantities and the predicted
quantities, Qd – Qd, are called the residuals. The goal of regression is to make the resid-
uals as small as possible.

8

8

8

Figure 3.1 Price and Quantity Data for Dinners

The figure plots the price of dinners and the quantity
demanded per day at different restaurants in the
chain. Because there is a random element to demand,
the points on this scatter diagram do not fall precisely
on a straight line; however, the data do cluster around
a negatively sloped straight-line demand curve.

Price (dollars per dinner)

Quantity (dinners per day)

$75

$45

$50

1,1001,000900800700600500

$55

$60

$65

$70

0

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90  CHAPTER 3 Measuring and Using Demand

There are various ways of minimizing the residuals. The most common regres-
sion technique is ordinary least squares (OLS) regression. OLS regression locates the
line through the scatter of data points that minimizes the sum of the squared resid-
uals between the actual quantities and the predicted quantities. We called the ac-
tual random term h, so let’s call the estimated residual for the first quantity hn 1, for
the second quantity hn 2, and so forth. OLS regression minimizes the sum of the
squared residuals. Figure 3.1 includes 21 data points, so the sum of the squared
residuals OLS minimizes is

hn 21 + hn 22 + hn 23 + Á + hn 221
You can use one of many statistical programs to calculate the regression coeffi-

cients, an and bn . Microsoft Excel can perform OLS regressions. Other statistical soft-
ware programs go further, allowing calculation of even more sophisticated
regressions. We’ll restrict ourselves to OLS regression because that is by far the
most commonly used technique in business. Let’s use Microsoft Excel 2013 to
demonstrate how to calculate the OLS regression line for the 21 data points in
Figure 3.1, so that you can see and interpret the reported results.

The first step in using Microsoft Excel is to click the “Data” tab. Then make sure
the “Data Analysis” icon is present (see the arrow in Figure 3.2). If the icon is not
present, follow the instructions in Figure 3.2 to install it.

To conduct the regression, start by entering the data. Use two columns in your
spreadsheet. Label the first “Quantity” and the second “Price.” Next, enter the data.
First, enter the dependent variable, quantity. Then enter the independent variable,
price. Figure 3.3 illustrates this process for the data in Figure 3.1 about the price and
quantity of steak dinners at your restaurant chain. Once you have entered all the
data,

1. Click the “Data” tab and then the “Data Analysis” icon.
2. When the “Data Analysis” box pops up, highlight the “Regression” entry, and

click “OK.”

Figure 3.2 Microsoft Excel: The Data Analysis Icon

The “Data Analysis” icon (see the arrow) is necessary to conduct regression analysis using Microsoft Excel. If the
icon is missing, you must install the Analysis ToolPak, an add-in included in Excel. To install the Analysis ToolPak:

• Click on the “File” tab.
• Click on “Options.”
• When the “Excel Options” window opens, click on “Add-ins.”
• At the bottom of the “Add-ins” screen, click “Go.”
• Find the “Analysis ToolPak” box, check it, and click “OK.”

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3.1 Regression: Estimating Demand  91

Figure 3.3 Microsoft Excel: Entering Data

The dependent variable is entered in column A under the heading “Quantity.”
The independent variable is entered in column B under the heading “Price.”

3. The “Regression” box, which enables you to specify the range of data you
want to use and where you want to display the results, will pop up. For the
data you are using, complete the “Regression” box as illustrated and ex-
plained in Figure 3.4.

4. In the “Regression” box, click “OK,” and Excel will estimate the regression.

The procedure just outlined estimates a univariate regression. Frequently,
however, you will want to estimate a multivariate regression. For example, in-
stead of price alone, you might want to explore whether the demand for dinners
at your chain also depends on the price charged by Sea’s Harvest, a competitive
upscale fish restaurant. So suppose that you also have data on the prices for a dinner
at Sea’s Harvest for each of the 21 quantity/price observations given in Figure 3.3.
In this case, you would enter the heading “Competitor Price” in cell C1 and the
data on these prices directly below it. You now have two independent,

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92  CHAPTER 3 Measuring and Using Demand

or X, variables. Consequently, in the “Regression” box, you would specify the
“Input X Range” as $B$1:$C$22, which is the new range for the independent vari-
ables. Click “OK,” and Excel now estimates your multivariate regression.

Regression Results: Estimated Coefficients and Estimated
Demand Curve
Figure 3.5 shows the results from the univariate regression analysis of the data on
price and quantity of steak dinners. Excel also includes a section of results enti-
tled “Analysis of Variance (ANOVA).” Because we do not need this section for our
regression analysis, it is not displayed in Figure 3.5. The results shown have been
limited to two decimal places. Often analysts report the results with many more
decimal places, but that is false precision.

Figure 3.4 Microsoft Excel: The “Regression”
Box

The “Input Y Range” refers to the dependent
variable, the quantity. The “Input X Range”
refers to the independent variable, the price.
For this example and these data, use the
ranges shown. Be certain to include the cell
with the title of the variable as part of the
range. Also, check the “Labels” box as shown.

Figure 3.5 Microsoft Excel: Results of Regression

These are the results of the Excel regression
using the data in Figure 3.1.

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3.1 Regression: Estimating Demand  93

The first result to note is the “Coefficients” column. The coefficient labeled
“Intercept” is our an (recall that an is the horizontal intercept of the demand equation).
The estimate from the regression is that an equals 1,999.82. This value for an means that
the estimated demand curve crosses the horizontal axis at a quantity of 1,999.82 din-
ners per day. The coefficient labeled “Price” is our bn (recall that bn is the coefficient
that multiplies the price variable). Excel estimates that bn equals −20.04, which means
that for every dollar increase in the price, consumers decrease the quantity of steak
dinners they demand at your restaurant chain by 20.04 dinners per day. So, using
these estimated coefficients, we find that the estimated demand curve is

Qd = 1,999.82 – 120.04 * P2
Figure 3.6 uses these coefficients to plot the estimated demand curve, labeled D,

and shows its relationship to the actual data points. Although the estimated de-
mand curve is closer to some data points than to others, this demand curve mini-
mizes the sum of the squared residuals between the actual quantities and the pre-
dicted quantities.

As a manager, you can use the estimated demand curve for dinners
at your restaurant chain to forecast the quantity of steak dinners demanded at
different prices. For example, if you set a price of $62 per dinner, the estimated
demand curve predicts that the quantity of dinners demanded is
1,999.82 – 120.04 * $622, or 757.3 dinners per day. This prediction represents a
point on the estimated demand curve—specifically, the white point in Figure
3.6. The actual quantity for the price of $62 (from the data in Figure 3.3) is 793.4
dinners per day. The difference between the actual quantity and the predicted
quantity, 793.4 dinners – 757.3 dinners = 36.1 dinners, is the estimated residual.
This difference results from the effect of the random factors on the actual
quantity.

Figure 3.6 An Estimated Demand Curve for Steak
Dinners

The demand curve estimated using ordinary least
squares regression is labeled D. The white dot shows
that at the price of $62 per dinner, the predicted
quantity of dinners demanded is 757.3.

Price (dollars per dinner)

Quantity (dinners per day)

$75

$45

$50

1,100

D

1,000900800700600500

$55

$60

$65

$70

0

Estimated
demand
curve

Predicted
quantity for
P 5 $62 is
757.3 dinners
per day.

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94  CHAPTER 3 Measuring and Using Demand

As a manager, you need to know how to interpret the results from a regression.
For example, you need to know how close the estimated coefficients are to the true
coefficients. This topic is covered in the next section.

Regression Analysis at Your Steak Chain

You are an upper-level executive at an upscale steak restaurant chain. Suppose that you
have the same data shown in Figure 3.3 but only for prices from $70 to $55 per dinner.
Using those 17 data points of price/quantity, estimate a univariate regression, and use
it to answer the following questions:

a. What are the estimated coefficients? What is the new estimated demand function?

b. Did the omission of the data points with prices from $54 to $50 per dinner make a
large change in the estimated demand function?

Answer

a. The estimate from the regression is that an equals 1,990.48 and bn equals −19.90. The
new estimated demand function is Qd = 1990.48 – 119.90 * P2.

b. Omitting the five data points did not lead to a large change in the estimated coeffi-
cients. The estimated an changes from 1,999.82 to 1,990.48, a change of 0.5 percent,
and the estimated bn changes from −20.04 to −19.90, a change of 0.7 percent. These
changes are very small.

SOLVED
PROBLEM

3.2 Interpreting the Results of Regression
Analysis

Learning Objective 3.2 Interpret the results from a regression.

The estimated demand curve shown in Figure 3.6 might not be the same as the actual
demand curve. In other words, the estimated coefficients from the univariate
regression, an = 1,999.82 and bn = −20.04, might not be identical to the actual coeffi-
cients. Of course, the same is true when your analysts estimate a multivariate
regression. Consequently, before you use the estimated demand curve, you need to
know how confident you are that the estimated coefficients are close to the true
coefficients. Measuring that confidence is the first step in interpreting the results
from a regression. Fortunately, the procedure used is the same for the coefficients
from both multi variate and univariate regressions.

Estimated Coefficients
The estimated coefficients from any regression depend on the data, which in turn
depend in part on the random element of the demand. Consequently, reestimating
the regression with new data means the estimated coefficients will change randomly
because the new data will contain new values of the random element. For example,

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3.2 Interpreting the Results of Regression Analysis  95

if your analysts ran the same pricing experiment reported in Figure 3.3 a second
time, setting the same 21 different prices at the same locations they used before, they
would gather 21 new quantity data points which would differ from the original
quantities due to the random fluctuations in demand. Your analysts could use these
new data points to estimate a new regression. This new regression would have new
estimates for an and bn that would differ from the initial estimates because of the ran-
dom element. Indeed, if your chain ran this experiment a large number of times,
you would wind up with a large number of estimates for an and bn . The large number of
estimates would create a distribution that would allow you to use statistics to
make inferences about the true values of a and b. But as a manager, you know it is
simply not feasible to run this pricing experiment more than once, much less a
“large number” of times!

Fortunately, such replication is unnecessary. If you look again at the regression
results in Figure 3.5, you will see that next to the column for “Coefficients” is a col-
umn labeled “Standard Error.” The standard error reflects the fact that the estimated
coefficients have a random element. The standard error of a coefficient is a measure
of how much the estimated coefficient is likely to change if another set of data is col-
lected and another regression estimated. For example, the estimated coefficient for
price, bn, is −20.04, with a standard error of 1.37. Compared to the coefficient esti-
mate, this standard error is relatively small. A small standard error means that the
change from reestimation of the regression probably will be small, which, in turn,
means that the estimated coefficient is likely close to the true value. A large standard
error, however, means that the change may be large, which suggests that the esti-
mated coefficient might not be particularly close to the true value. You can go
beyond this qualitative description of the effect of the size of the standard error to
construct a range that for repeated samples has a pre-selected probability of con-
taining the true value of the coefficient. For example, you can construct a range that
will contain the true value of the coefficient 95 percent of the time. Such a range is
called a confidence interval.

Confidence Intervals
In randomized pricing experiments like the one we suppose that your restaurant
chain conducted, OLS regression has a very nice statistical property: The esti-
mated coefficients are unbiased, meaning that they are systematically neither
greater than nor less than the actual true values. Moreover, the statistical proper-
ties of OLS regression mean that if you gather many data samples and reestimate
the regression many times, all the new estimated coefficients you obtain will cre-
ate a range that is centered around the true value of the coefficients. These facts
provide a starting point for the confidence interval. Because the estimated coeffi-
cients from your regression are unbiased, they are your best estimate of the true
value of the coefficients. Consequently, the range of the confidence interval will
be centered around the estimated coefficients. For instance, if you are calculating
a confidence interval for the b coefficient, the range of the confidence interval will
be centered around −20.04, the estimated value bn from the regression.

The range for a confidence interval depends on two factors:

1. The size of the standard error. Because the standard error measures how much
the estimated coefficient is likely to change with reestimation of the regression
using a new data sample, the larger the standard error, the larger the possible
change of the coefficient. It follows that the larger the standard error, the larger
the confidence interval.

Confidence interval
A range that for repeated
samples has a pre-selected
probability of containing
the true value of the
coefficient.

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96  CHAPTER 3 Measuring and Using Demand

2. How confident the manager wants to be that the range contains the true
value of the coefficient. The more confident the manager wants to be,
the larger the confidence interval. Conventionally, 95 percent or 99 percent
is used as the desired level of confidence, though nothing prevents
managers from using other levels. A 95 percent confidence level means
that if the pricing experiment is run over and over, each time estimating
the demand function regression, 95 percent of the time the confidence in-
terval from any regression will contain the true value of the coefficient.

Analysts can use a statistical formula to calculate a confidence interval.
Happily, however, most statistical software automatically calculates and reports
the endpoints of the confidence interval. Excel automatically reports the two
ends of the 95 percent confidence interval for the estimated coefficients, called
“Lower 95%” and “Upper 95%.” For example, in Figure 3.5, the 95 percent confi-
dence interval for bn runs from −22.92 to −17.17. This result means that you can
be 95 percent confident that this range contains the true value of b. This range
has an important managerial implication: You are 95 percent confident that in
response to a dollar increase in price, your customers will decrease the quantity
of dinners they demand by an amount that lies between 22.92 and 17.17 dinners
per day.

Figure 3.5 also reports the two ends of the 95 percent confidence interval for the
estimated intercept, an. In a multivariate regression with more than one independent
variable, the statistical software will usually present the lower and upper ends of a
confidence interval for each coefficient separately. Calculating a confidence region
for two or more coefficients jointly requires a more sophisticated test, which is best
covered in a class devoted to business statistics.

Hypothesis Testing
Often you will be interested in the impact of a particular variable on your predic-
tion. For example, we mentioned earlier that as a manager of a steak restaurant
chain, you might be interested in determining whether the demand for steak
dinners depends not only on the price you set but also on the price charged by
Sea’s Harvest, the competing fish restaurant. Let’s suppose that a multivariate
regression results in the estimated coefficient for the price of meals at Sea’s Harvest
presented in Table 3.1.

The estimated coefficient, 8.04, is positive and indicates that a $1 increase
in the price of a dinner at Sea’s Harvest increases the demand at your restaurant
chain by 8.04 dinners per day. But the standard error of this coefficient is
large compared to the coefficient, so the 95 percent confidence interval ranges
all the way from −4.83 dinners per day up to 20.91 dinners per day. Given
this broad range, you might wonder if the price charged at Sea’s Harvest actu-
ally affects the demand for your steak dinners. In particular, if the true

Table 3.1 Results for an Estimated Coefficient for Meals at Sea’s Harvest

Coefficient Standard Error t Stat P-value Lower 95% Upper 95%

Competitor
Price

8.04 6.12 1.31 0.21 −4.83 20.91

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3.2 Interpreting the Results of Regression Analysis  97

coefficient turns out to be zero (which is among the values included in the confi-
dence interval), then the price charged at Sea’s Harvest has no effect on the de-
mand for your steak dinners. In this case, as a manager you can ignore the price
charged at Sea’s Harvest. So you want to know if the estimated coefficient—
which is your best estimate of the true coefficient—is different from zero.
Fortunately, there is a statistical test to determine whether an estimated coeffi-
cient is significantly different from zero. This test, like all statistical tests, begins
with two fundamental steps:

1. The test starts by posing the null hypothesis, which in this case is that “the true
coefficient equals zero.” For example, as a manager at the steak chain, your
null hypothesis is that in the demand for your meals, the true coefficient for
Sea’s Harvest’s price is zero, in which case the price of fish dinners does not
affect the demand for your steak dinners. If you reject (or “nullify”) the hy-
pothesis that the true coefficient equals zero, then you have rejected the null
hypothesis in favor of the alternative hypothesis, that the true coefficient is not
equal to zero, so that the price of fish dinners affects the demand for your steak
dinners.

2. You can never know for sure what the true coefficient equals, so there is
some probability that you might draw the wrong conclusion. Accordingly,
you must select how confident you want to be that rejecting (nullifying) the
null hypothesis is the correct decision. The most common confidence levels
are the same as those you saw before for confidence intervals, 95 percent
and 99 percent. When you reject the null hypothesis at a confidence level of,
say, 95 percent, you know that 95 percent of the time rejecting the null hy-
pothesis is the correct decision. Of course, that means that 5 percent of the
time you are making the incorrect decision—5 percent of the time the null
hypothesis is correct, but you are rejecting it. The significance level of a
test is the probability that you are making the wrong decision. For example,
the 95 percent confidence level has a significance level of 1 – 0.95 = 0.05, or
5 percent.

In our restaurant example, you want to test the null hypothesis that the true
value of the coefficient for the price of meals at Sea’s Harvest is zero. To do this,
you use what is called a t test by calculating a measure called a t-statistic. The
t-statistic equals the estimated coefficient divided by its estimated standard
error.

Regression software, such as Excel, reports the t-statistic for each coeffi-
cient. In Table 3.1, the competitive price coefficient for meals at Sea’s Harvest
has a t-statistic of 1.31, calculated from 8.04/6.12. The t-statistic is positive if
the estimated coefficient is positive, and it is negative if the estimated coeffi-
cient is negative. The sign of the t-statistic is unimportant; what is important is
its magnitude (absolute value). If the magnitude of the t-statistic is large, then
the definition of the t-statistic shows that the estimated coefficient is large com-
pared to its estimated standard error. In this case, the confidence interval is
unlikely to include zero, so it is unlikely that the true coefficient equals zero.1

Significance level The
probability of making the
wrong decision, which is
equal to 1 minus the
confidence level.

t-statistic The estimated
coefficient divided by its
estimated standard error.

1 The t test is closely related to the confidence interval. If the 95 (99) percent confidence interval includes
zero, the t test will not reject the null hypothesis that the true coefficient equals zero at the 95 (99) percent
confidence level.

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98  CHAPTER 3 Measuring and Using Demand

So a large t-statistic leads you to reject the null hypothesis (that the true coeffi-
cient equals zero) in favor of the alternative hypothesis (that the true coefficient
is not zero).

How large must the t-statistic be to reject the null hypothesis? Statisticians
have calculated the probability of each value of the t-statistic when the
null hypothesis is true. This distribution provides the critical value of the
t-statistic—that is, the value of the t-statistic above which the null hypothesis is
rejected.

The critical value depends on the confidence level, with a higher confidence
level (a lower significance level—that is, a lower probability of error) leading to
a larger critical value. The critical value also depends on the number of obser-
vations, but it does not change much once there are more than 40 or 50 observa-
tions. For a large number of observations, the 95 percent confidence level (the
5 percent significance level) has a critical value of 1.96. (For the 99 percent con-
fidence level, the critical value is 2.58.) If the computed value of the t-statistic
exceeds 1.96, you can reject the null hypothesis, knowing that you are making
the correct decision at least 95 percent of the time.

In Table 3.1, the computed value of the t-statistic is 1.31, which is below the
95 percent confidence level critical value, so you cannot reject the null hypothesis.
Instead, you retain the null hypothesis that the true coefficient is zero, which means
that the price of meals at Sea’s Harvest has no effect on the demand for steak dinners
at your restaurant chain. Contrast this result with the t-statistic for the price coeffi-
cient (the bn ), reported in Figure 3.5 as −14.59. The absolute value of the t-statistic,
14.59, is well above the 95 percent confidence level critical value of 1.96, so you can
easily reject the null hypothesis in favor of the alternative hypothesis that the true
coefficient is not zero.

Table 3.1 (along with Figure 3.5) reports one other result: the P-value. Assuming
that the null hypothesis is correct (the true coefficient equals zero), the P-value is
the probability in repeated samples of obtaining a value of the t-statistic equal to
or larger than the computed t-statistic reported in the results. Table 3.1 shows that
when the t-statistic is 1.31, the P-value is 0.21, or 21 percent. So even when the true
coefficient equals zero, if you repeatedly re-estimated the regression each time using
new data you gather, 21 percent of the time the computed t-statistic would be 1.31 or
larger. If you rejected the null hypothesis that the true coefficient is zero based on a
t-statistic equal to 1.31 or larger, you would be making an error 21 percent of the
time. So, the P-value is equal to the significance level of testing the null hypothesis;
that is, it is equal to the probability of erroneously rejecting the null hypothesis.
Conventionally, users reject a null hypothesis when the significance level is 0.05
(5 percent) or less, which makes the confidence level 0.95 (95 percent) or more. Only
when the P-value is 0.05 or less should you reject the null hypothesis in favor of the
alternative hypothesis that the coefficient is not zero.

The P-value is useful because it gives you finer detail than the t-statistic about
how strongly you reject (or do not reject) a hypothesis. The results of a t-statistic are
usually reported simply as “reject” or “do not reject” and that is it. Returning to
Figure 3.5 dealing with the univariate demand function for steak dinners, you see
that the estimated coefficient for the price of a steak dinner has a P-value so small that
it is rounded to 0.00 (0 percent). In other words, there is virtually a 0 percent chance
you are making a mistake by rejecting the null hypothesis that the true coefficient is
zero. In this case, you can very confidently reject the null hypothesis, which means
you can be very confident that the price of a steak dinner affects the quantity of steak
dinners demanded.

Critical value The value of
the t-statistic above which
the null hypothesis is
rejected.

P-value Assuming the null
hypothesis is true, the
probability in repeated
samples of obtaining a
value of the t-statistic
equal to or larger than the
computed t-statistic.

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3.2 Interpreting the Results of Regression Analysis  99

The following box summarizes guidelines for interpreting regression coefficients.

t test
If the magnitude of the t-statistic is larger than the critical value:

• Reject the null hypothesis that the true value of the coefficient equals zero.

• Accept the alternative hypothesis that the true value of the coefficient is nonzero.

If the magnitude of the t-statistic is less than the critical value:

• Fail to reject (accept) the null hypothesis that the true value of the coefficient
equals zero.

P-value
If the P-value is less than the significance level (typically 0.05 or 0.01):

• Reject the null hypothesis that the true value of the coefficient equals zero.

• Accept the alternative hypothesis that the true value of the coefficient is nonzero.

If the P-value is larger than the significance level (typically 0.05 or 0.01):

• Fail to reject (accept) the null hypothesis that the true value of the coefficient
equals zero.

TESTING REGRESSION COEFFICIENTS

Fit of the Regression
In addition to establishing your confidence in the values of the regression coefficient,
you may want to know how accurate the regression is overall—that is, how close the
predicted values are to the actual data points. For the estimated demand curve
shown in Figure 3.7(a), you can see that the predicted values (the points on the esti-
mated demand curve) are close to the actual data points. The estimated demand
curve shown in Figure 3.7(b) is not particularly close to the data points, so the pre-
dicted values are not close to the actual values. Is it possible to measure how well the
regression fits the data? The answer is yes: One of the results reported by Excel in
Figure 3.5 provides a measure of the fit between the regression and the data. The
R2 statistic (R-squared statistic), more commonly called simply R2 (R squared), is a
measure of how much of the variation in the observed values of the dependent
variable is captured by the predicted values of the regression. Specifically, R2 is the
fraction of the data points’ variation accounted for by the regression’s predicted val-
ues. It ranges from 1.00 (100 percent) to 0.00 (0 percent). The closer R2 is to 100 per-
cent, the more closely the predicted values fit the actual data.

The R2 statistic for the demand curve in Figure 3.7(a) is 0.92. The predicted val-
ues from the regression account for 92 percent of the variation in the observed values
of the dependent variable, which indicates a very good fit. The R2 statistic for the
demand curve in Figure 3.7(b) is 0.52. The predicted values from this regression ac-
count for only 52 percent of the variation in the observed values of the dependent
variable, which indicates a poorer fit.

R2 statistic A measure of
how much of the variation
in the observed values of
the dependent variable is
captured by the predicted
values of the regression.

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100  CHAPTER 3 Measuring and Using Demand

Confidence Intervals and Predictions for the Demand for Doors

You are a manager of a company similar to Pella Corporation, a producer of high-quality
doors and windows. The members of your marketing group give you the results of their
research into the demand for your company’s doors. They report that the estimated
coefficient for the effect of price on the demand for doors is – 700 doors per dollar, with
a standard error of 200 doors per dollar and a 95 percent confidence range of – 1,092
doors per dollar to – 308 doors per dollar.
a. Is the estimated coefficient significantly different from zero at the 95 percent confi-

dence level? Explain your answer.

b. If you raise the price of a door by $10, what decrease in quantity do you expect?
Using the 95 percent confidence interval, what would be the largest decrease in
quantity? The smallest?

SOLVED
PROBLEM

Figure 3.7 Fit of Estimated Demand Curves

(a) Demand Curve with a High R 2

The estimated demand curve, D, is close to
the data points, so it has a higher R2 statistic.

(b) Demand Curve with a Low R 2

The estimated demand curve, D, is not close to the
data points, so it has a lower R2 statistic.

Price (dollars per dinner)

Quantity (dinners per day)

$75

$45

$50

1,100

D

900700500 1,000800600

$55

$60

$65

$70

0

Estimated
demand
curve

Price (dollars per dinner)

Quantity (dinners per day)

$75

$45

$50

1,100

D

900700500 1,000800600

$55

$60

$65

$70

0

Estimated
demand
curve

When you receive a report based on regression analysis, you must be con-
cerned with R2. If it is small—say, 0.12 (12 percent)—you need to be aware that the
predicted values do not capture much of the variation in the actual values of the
dependent variable. In other words, the predicted values are not particularly
close to the observed, actual values. If R2 is large—say, 0.88 (88 percent)—you can
be more confident in the results because the predicted values are close to the
observed, actual values.

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3.3 Limitations of Regression Analysis  101

3.3 Limitations of Regression Analysis
Learning Objective 3.3 Describe the limitations of regression analysis and
how they affect its use by managers.

When you receive a report including analysis based on a regression equation, you
need to know the potential limitations of the regression. We will discuss two possi-
ble weaknesses: (1) the specification of the regression—that is, which variables are
included; and (2) its functional form—that is, how the variables are entered in the
function the analyst estimated.

Specification of the Regression Equation
Whenever you examine regressions you must always consider whether they include
all of the relevant factors. If not, you should view the results and analysis with at least
a touch of skepticism. For example, as a manager at your high-end steak restaurant
chain, you might receive a regression analysis from your market research team, using
data accumulated over 21 years, that shows how the price of a steak dinner affects the
quantity of steak dinners demanded. Price is the only independent variable, so the
regression equation is similar to what you have already seen, Qd = a – 1b * P2. In
the last section, the research department collected the data at several locations at a
single point in time. In the current case, the data have been accumulated over more
than two decades. Because the data cover 21 years, a long period of time, another
relevant variable that affects consumer demand is surely missing: their incomes.
As you learned in Chapter 2, income is a factor that affects demand, and income
has definitely changed over the last 21 years. Omitting this important variable
could result in a low R2, which means predictions using the equation might not be
very accurate. Its omission might also bias the estimated price coefficient because,
if both price and income have been trending higher over the past 21 years, then the
price coefficient could be capturing both the effect of changes in price and also the
effect of changes in income. Because analysts may be able to obtain income data,
you should probably return the report to the market research team with a request
to include income as an additional independent variable in the regression.

Unlike income, some potentially relevant variables are simply not measurable.
For example, there may have been a couple of years during the 21-year period when
there was a substantial scare about mad cow disease, an untreatable and fatal disease
that attacks the brain. If enough consumers believed that they might catch mad cow
disease by eating steaks, their preferences would have changed, decreasing the
demand for steak dinners. Perfectly measuring this type of change in preferences is

Answer

a. The estimated coefficient is significantly different from zero because the magnitude of
its t-statistic, which equals 700>200 = 3.5, easily exceeds the critical value of 1.96.

b. Using the estimated coefficient, you expect the increase in price to change the
quantity demanded by – 700 doors * $10 = – 7,000 doors. Using the range of the
95 percent confidence interval, the largest decrease would occur if the coefficient
equaled – 1,092 doors, in which case the decrease in quantity demanded would be
1,092 doors * $10 = 10,920 doors. The smallest decrease in the quantity demanded
would occur if the coefficient equaled −308 doors, in which case the decrease in
quantity demanded would be 308 doors * $10 = 3,080 doors.

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102  CHAPTER 3 Measuring and Using Demand

impossible. In the short run, the only course of action is to omit this variable and hope
that its omission does not have a large effect on the results. In the long run, it might be
possible to accumulate more data for years not affected by this factor and ultimately
omit from the regression analysis those years that could be anomalous.

Functional Form of the Regression Equation
So far, all of the figures showing price and quantity data points for steak dinners have
strongly suggested a straight-line demand curve. But what if the price and quantity
data points looked like those in Figure 3.8? In this case, you might suspect that the true
demand curve is not a straight line because the data points seem to lie around a con-
vex (bowed inward) curve. Analysts can use various transformations of the data to
account for the nonlinearity of a demand curve. One of the most common is to take the
natural logarithms of both the price and the quantity data and then assume that the
true demand curve is linear in the natural logarithms, a specification called log-linear:

ln Qd = a – 1b * ln P2 + h
where ln Qd is the natural logarithm of the quantity, ln P is the natural logarithm of
the price, a and b are coefficients, and h is the random error term. This functional
form results in a demand curve with an inward bow, as illustrated in Figure 3.8. For
a log-linear demand curve, the regression is estimated using the transformed data
series ln Qd for the dependent variable and the transformed data series ln P for the
independent variable. Figure 3.9 illustrates the estimated demand curve that results
from this regression.

Figure 3.9 shows that a log-linear specification yields a demand curve that can fit
the convex shape of the data points. The log-linear specification has an additional
advantage: When the data are in logarithms, the estimated bn coefficient is equal to
the price elasticity of demand, a concept you will learn about in the next section. For
now, you just need to know that this result can be useful.

The predictions from the log-linear regression are for ln Qd. However, the
result usually desired is Qd; that is, you want to know the predicted quantity, not

8

8

Figure 3.8 Alternative Data for Steak Dinners

The data points in this scatter diagram of an
alternative data set for the price of dinners and the
quantity demanded per day do not seem to cluster
around a negatively sloped straight-line demand
curve.

Price (dollars per dinner)

Quantity (dinners per day)

$75

$45

$50

1,1001,000900800700600500

$55

$60

$65

$70

0

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3.3 Limitations of Regression Analysis  103

its logarithm. Mathematically, you can change the logarithm of a number to the
number itself by raising e to the logarithm of the number. So to obtain Qd itself, it is
common to use elnQd. For reasons dealing with the statistics of the error term, this
procedure is an approximation, but any error is usually small and therefore is typi-
cally ignored.

The examples of regression we have used all focus on estimating the demand
function. But regression is used for much more than simply estimating demand
functions. For example:

• Every 5 to 10 minutes, at the front of each popular attraction, The Walt Disney
Company posts estimated wait times for the attraction. Regression is used to
help forecast these wait times.

• The Portland Trailblazers have used a sophisticated type of regression to help
forecast the probability that college basketball players will have successful NBA
careers.

• Schneider Logistics, a part of the large transportation company Schneider
National, uses regression models to help predict the profitability of different
freight flows.

Clearly, regression analysis plays an important role in many aspects of many dif-
ferent businesses.

Using regression to estimate the coefficients of the demand for your product
results in precise estimates of how much consumers respond to changes, enabling
you to make better decisions about pricing and production. There will be times,
however, when you do not have enough data to use regression analysis to estimate
the demand for your product. In other situations, you might want precise estimates
of, say, the effect of a change in supply on the price you must pay for an input, and
again you may not have enough data to estimate a regression. In these and other
cases, another tool, called elasticity, sometimes can provide the valuable informa-
tion you need.

8

8

Figure 3.9 Estimated Nonlinear Demand Curve

A nonlinear (log-linear) demand curve best fits the
data points in Figure 3.8.

Price (dollars per dinner)

Quantity (dinners per day)

$75

$45

$50

1,100

D

1,000900800700600500

$55

$60

$65

$70

0

Estimated
demand
curve

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104  CHAPTER 3 Measuring and Using Demand

SOLVED
PROBLEM Which Regression to Use?

Your research department gives you the following two estimated demand curves. The
estimated demand curve to the left is log-linear, and the estimated demand curve to
the right is linear.

Price (dollars per dinner)

Quantity (dinners per day)

$75

$45

$50

1,100

D

1,000900800700600500

$55

$60

$65

$70

0

Price (dollars per dinner)

Quantity (dinners per day)

$75

$45

$50

1,1001,000900800700600500

$55

$60

$65

$70

0

D

a. Which regression do you think has the highest R2—the one with the log-linear speci-
fication or the one with the linear specification? Explain your answer.

b. Are the predicted quantities from one demand curve always closer to the actual
quantities than the predicted quantities from the other demand curve?

c. Which estimated demand curve would you use to make your decisions? Why?

Answer

a. The log-linear specification is closer to more of the data points than the linear speci-
fication. So the R2 of the log-linear specification exceeds that of the linear
specification.

b. Even though the predicted quantities from the log-linear specification are closer to
most of the actual quantities, there are a few predicted quantities that are closer
when using the linear specification. In particular, for prices of $67 and $64, the pre-
dicted quantities from the linear specification are closer to the actual quantities than
the predictions from the log-linear specification.

c. As a manager, you want to base your decisions on the most accurate information
possible. The log-linear specification has the higher R2, which means that it does a
better job of capturing the variation in the actual quantities than does the linear
specification. Consequently, you should use the log-linear specification as the basis
for your decisions.

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3.4 Elasticity  105

3.4 Elasticity
Learning Objective 3.4 Discuss different elasticity measures and their use.

At its most basic level, elasticity measures responsiveness: How strongly does the
quantity demanded of a product respond to a change in one of the factors affecting
demand? This section describes elasticity for three of these factors: the price of the
product, income, and the price of a related good. Elasticity gives a quantitative mea-
sure of the strength of the demand response to all three factors.

The Price Elasticity of Demand
The most fundamental elasticity is the price elasticity of demand. The price elasticity
of demand measures how strongly the quantity demanded changes when the price
of the product changes—it measures the movement along a demand curve resulting
from a change in the price. More specifically, the price elasticity of demand (e)
is the absolute value of the percentage change in the quantity demanded divided by
the percentage change in the price:

e = `
Percentage change in quantity demanded

Percentage change in price
` 3.1

Recall that, according to the law of demand, whenever the price of a product rises,
the quantity demanded falls, and whenever the price falls, the quantity demanded
rises. So in the formula the sign of one of the changes is always positive and that of
the other is always negative. Because the resulting elasticity would always be nega-
tive, it is common to take the absolute value to eliminate the negative sign.2

The percentage change in the quantity demanded is (∆Qd>Qd2 * 100, where the
∆ means “change in.” The percentage change in price is 1∆P>P2 * 100. Combining
these shows that the price elasticity of demand equals

e = ` 1∆Q
d>Qd2 * 100

1∆P>P2 * 100 ` = `
1∆Qd>Qd2
1∆P>P2 ` 3.2

Why does the price elasticity of demand use percentages? For a linear demand
curve, such as Qd = a – 1b * P2, it might seem more logical to use the estimated
value of b as the measure of elasticity because, as you learned in Chapter 2, b tells you
how much the quantity demanded changes in response to a $1 change in the price.
For example, the estimated demand function for steak dinners at your restaurant
chain had an estimated value for bn of −20.04, which meant that a $1 increase in the
price of a steak dinner decreased the quantity demanded by approximately 20 dinners
per night. But suppose that you were interested in the decrease per week rather than
the decrease per day. In that case, you would estimate the demand function using
quantity data accumulated for seven days rather than for a single day. With this
change, a $1 increase in the price decreases the quantity of steak dinners demanded
(for the week) by approximately 140 dinners per week. The estimated value of bn
would increase sevenfold, to 7 * −20.04, or −140.28. If you used bn as your measure of
elasticity, you would see that it changed by merely switching the quantity from daily
demand to weekly demand. Indeed, any change in the units of quantity or price af-
fects the estimated value of bn. If your chain of steak restaurants had locations in

Price elasticity of demand
A measure of how strongly
the quantity demanded
changes when the price
changes, equal to the
absolute value of the
percentage change in the
quantity demanded divided
by the percentage change
in the price.

2 Some sources, however, retain the negative sign. In those cases, you can convert the elasticities you find
there to the elasticity we discuss by dropping the negative sign.

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106  CHAPTER 3 Measuring and Using Demand

England, the estimated value of bn for the U.K. demand function would be different
from that of the U.S. demand function simply because the price in the United Kingdom
is measured in pounds and the price in the United States is measured in dollars even if
the response to a $1 change in the price is identical for the two demand functions.

To avoid the problems of using a measure of elasticity that changes with the
units, economists have defined the price elasticity of demand using percentages
because percentages do not change when the units change.

Using the Price Elasticity of Demand
Equation 3.1 enables you to calculate the price elasticity of demand using information
on the percentage change in the quantity demanded and the percentage change in the
price. For instance, if a 10 percent increase in the price of a good leads to a 5 percent
decrease in the quantity demanded, the price elasticity of demand for the good equals

`
– 5 percent
10 percent

` = 0.5

Equation 3.1 can also be rearranged to calculate (or predict) the percentage
change in the quantity demanded that results from a percentage change in the
price or the percentage change in the price that results from a percentage change in
the quantity. For example, suppose that at your steak restaurants you determine
the price elasticity of demand for steak dinners is 1.3 and the price of a dinner rises
by 6 percent. What does the decrease in the quantity of dinners demanded equal?
To answer this question, rearrange the formula for price elasticity of demand to
isolate the percentage change in the quantity demanded:

e * 1Percentage change in price2 = 1Percentage change in quantity demanded2 3.3
Using the value for the price elasticity of demand and the percentage change in the
price in Equation 3.3, the percentage change in the quantity demanded will be
1.3 * 6 percent = 7.8 percent. With the knowledge that you will sell 7.8 percent
fewer dinners, you can now make better managerial decisions.

In addition to your steak dinners, suppose that your restaurants also serve
chicken. Because of lower food costs for chicken, suppose that analysts predict the
quantity of chicken will increase by 10 percent. The price elasticity of demand for
chicken is approximately 0.4. Managers at your restaurant chain will be interested in
how much the price of chicken will fall with the increase in quantity. Once again,
you can use the equation for price elasticity of demand to forecast the fall in the
price. This time you rearrange the equation to isolate the percentage change in price:

1Percentage change in price2 =
1Percentage change in quantity2

e

In the rearranged equation, two changes have been made:

• The calculation uses the percentage change in the quantity rather than the per-
centage change in the quantity demanded. This change reflects the fact that at
equilibrium the percentage change in the quantity demanded must equal the
percentage change in the quantity.

• Because you already know that an increase in the quantity lowers the price,
there is no negative sign in the percentage change in price term.

You can combine the rearranged equation with the elasticity and the predicted
change in quantity to predict that the percentage fall in the price will be
10 percent/0.4 = 25 percent. This information is valuable to managers of the chain

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3.4 Elasticity  107

because it helps them make better decisions about potential menu specials—featuring
more dishes with chicken might increase profit!

Elasticity Along a Linear Demand Curve
Rearranging the formula for the price elasticity of demand from Equation 3.2,
e = |1∆Qd>Qd2>1∆P>P2|, helps demonstrate a possibly unforeseen result in the
behavior of the price elasticity of demand at different points along a linear, down-
ward-sloping demand curve:

e = 4 ∆QdQd
∆P
P

4 = ` ∆Qd
Qd

*
P
∆P

` = ` ∆Q
d * P

Qd * ∆P
` = ` ∆Q

d * P
∆P * Qd

` = ` ∆Q
d

∆P
*

P
Qd

`

In this string of equalities, the second equality reflects the division of ∆Qd>Qd by ∆P>P;
the third equality is the result of multiplying the two fractions; the fourth equality
switched the terms in the denominator; and the last equality breaks the fraction into
two components. In the last expression, |1∆Qd>∆P2 * 1P>Qd2|, the term 1∆Qd>∆P2
is the change in the quantity demanded brought about by a $1 change in the price.
Sound familiar? In the algebraic equation for the linear demand function you have
been using, Qd = a – 1b * P2, the coefficient b is the change in the quantity
demanded brought about by a $1 change in the price. So in the last expression, substi-
tute the coefficient b for the 1∆Qd>∆P2 term to show that for a linear demand curve3

e = |b * 1P>Qd2| 3.4
You can use Equation 3.4 to calculate the price elasticity of demand at any one point

on a linear, downward-sloping demand curve, so Equation 3.4 is called the point elasticity
formula. In Figure 3.10, a linear demand curve showing the price and quantity of

3 Section 3.A of the Appendix at the end of this chapter uses calculus to derive a general version of
Equation 3.4 for any demand function.

Figure 3.10 Price Elasticity of Demand Along a Linear
Demand Curve

The point elasticity formula, e = |b * 1P>Qd2|, can be
used to calculate the price elasticity of demand at
each of the points on a linear demand curve. On a
linear, downward-sloping demand curve, the price
elasticity of demand falls in value moving down the
curve.

Price (dollars per baseball cap)

Quantity (baseball caps per day)

$35

$5

$10

70
D

605040302010

$15

$20

$25

$30

0

B

A

e 5 5.0

e 5 2.0

e 5 1.0

e 5 0.5

e 5 0.2
e . 1

e 5 1

e , 1

M03_BLAI8235_01_SE_C03_pp86-137.indd 107 23/08/17 9:53 AM

108  CHAPTER 3 Measuring and Using Demand

baseball caps, the price elasticity of demand can be calculated at any of the points on the
demand curve. The value of b for the demand curve illustrated in the figure is −2 base-
ball caps per dollar. Using the point elasticity formula, you find that at point A on the
demand curve, the elasticity equals � – 2 * 1$20>202 � = 2.0. And at point B, the elastic-
ity is � – 2 * 1$10>402 � = 0.5. Equation 3.4 and Figure 3.10 show a remarkable result:
The price elasticity of demand changes with movements along the linear demand
curve. In particular, moving downward along the demand curve, the price elasticity of
demand falls in value. At the midpoint of the demand curve, the price elasticity
of demand equals 1.0. At points above the midpoint, it exceeds 1.0, and at points below
the midpoint, it is less than 1.0. As a manager, keep in mind that the price elasticity of
demand will be different at each point on a linear demand curve. If your decision revolves
around a certain price, you must be certain that you use the elasticity at that price.

You can also use Equation 3.4 to calculate the elasticity at points on an estimated
demand curve. Assuming that the demand curve is linear, the regression analysis
gives Qd = an – 1bn * P2, where bn is the estimated value of the b coefficient and Qd is
the predicted quantity demanded. Then for any price (P), you can use the estimated
value of bn and the predicted quantity demanded, Qd, in Equation 3.4 to calculate the
estimated value of the price elasticity of demand at that point on the demand curve:

en = � bn * 1P>Qd2 � 3.5

Elasticity Along a Log-Linear Demand Curve
Calculating the price elasticity of demand for a log-linear demand curve,
ln Qd = a – (b * ln P), is immediate: The elasticity equals the value of the b coeffi-
cient. Refer to the Appendix at the end of this chapter to see a proof of this result
using calculus. In Figure 3.11, the b coefficient for the illustrated demand curve for
baseball caps is −1.00, so the price elasticity of demand equals 1.00 at points A and B.
In fact, at all points on this demand curve, the price elasticity of demand is equal to
1.00. Demand curves for which the price elasticity of demand is the same at all
points are called constant elasticity of demand curves.

88

8

8

Figure 3.11 Price Elasticity of Demand Along a
Log-Linear Demand Curve

The price elasticity of demand is constant at all points
along a log-linear demand curve.

Price (dollars per baseball cap)

Quantity (baseball caps per day)

$35

$5

$10

70

DB

A

605040302010

$15

$20

$25

$30

0

M03_BLAI8235_01_SE_C03_pp86-137.indd 108 23/08/17 9:53 AM

3.4 Elasticity  109

If a log-linear demand curve has been estimated, such as ln Qd = an – 1bn * ln P2,
the estimated price elasticity of demand is bn and is the same at all points on the esti-
mated demand curve.

Elastic, Unit-Elastic, and Inelastic Demand
The price elasticity of demand measures how strongly demanders respond to a
change in the price of the good. For example, economists have estimated the price
elasticity of demand for coffee to be 0.25. Rearranging the formula for the price elas-
ticity of demand,

e = `
Percentage change in quantity demanded

Percentage change in price
`

shows that

e * (Percentage change in price) = (Percentage change in quantity demanded)

Using the rearranged formula, if the price of coffee rises by 10 percent, you can calcu-
late that the percentage change in the quantity of coffee demanded is 0.25 * 10 per-
cent = 2.5 percent. In other words, a 10 percent increase in the price of coffee leads to
a 2.5 percent decrease in the quantity of coffee demanded. In contrast, economists
have estimated the price elasticity of demand for Pepsi to be 1.55. If the price of Pepsi
rises by 10 percent, then the quantity of Pepsi demanded decreases by
1.55 * 10 percent = 15.5 percent. There is a significant difference between the
strength of the consumer response to a change in the price of coffee and the consumer
response to a change in the price of Pepsi. The definitions of elastic demand, unit-elas-
tic demand, and inelastic demand formalize this difference.

Elastic demand means that consumers respond strongly to a change in price.
For a product with elastic demand, the percentage change in the quantity demanded
exceeds the percentage change in the price, so the definition of the price elasticity of
demand shows that it is greater than 1.00. Using this definition, we see that the de-
mand for Pepsi is elastic.

Unit-elastic demand means that consumer response to a change in price is one-
to-one; that is, a 10 percent increase in the price creates a 10 percent decrease in the
quantity demanded. In this case, the definition of elasticity shows that the price elas-
ticity of demand is equal to 1.00.

Inelastic demand means that consumers respond weakly to a change in price.
The percentage change in the quantity demanded is less than the percentage change
in the price, so the price elasticity of demand is less than 1.00 for a product with in-
elastic demand. Using this definition, we see that the demand for coffee is inelastic.

When two demands have different elasticities, how is the difference reflected in
their demand curves? Figure 3.12 answers this question for the case in which two
demand curves cross. Starting from point A, the figure shows that in response to a
$5 increase in the price of baseball caps, the decrease in the quantity demanded
along demand curve D2 (20 caps) exceeds the decrease in the quantity demanded along
demand curve D1 (5 caps). This difference in response means that the elasticity on
demand curve D2 at point A is larger than the elasticity on demand curve D1 at point A.
This result is precisely in line with the intuitive meaning of elasticity as responsiveness:
At the point where the demand curves cross, the percentage change in price from $15 to
$20 is exactly the same for both demand curves, but along the (flatter) demand curve,
D2, the percentage response from consumers is stronger than along the (steeper)
demand curve, D1.

8

Elastic demand Demand
is elastic when the
percentage change in
the quantity demanded
exceeds the percentage
change in the price; the
price elasticity of demand
is greater than 1.00.

Unit-elastic demand
Demand is unit elastic
when the percentage
change in the quantity
demanded equals the
percentage change in the
price; the price elasticity of
demand is equal to 1.00.

Inelastic demand Demand
is inelastic when the
percentage change in the
quantity demanded is less
than the percentage
change in the price; the
price elasticity of demand
is less than 1.00.

M03_BLAI8235_01_SE_C03_pp86-137.indd 109 23/08/17 9:53 AM

110  CHAPTER 3 Measuring and Using Demand

Perfectly Elastic Demand and Perfectly Inelastic Demand
At the point where two demand curves cross, the flatter demand curve has a larger
elasticity. This observation leads to the definitions of two extreme elasticities: per-
fectly elastic demand and perfectly inelastic demand. Perfectly elastic demand
means consumer response to a change in the price is the largest possible response
in the quantity demanded: A rise in the price decreases the quantity demanded to
zero, and a fall in the price increases the quantity demanded to infinity. The
demand for milk from a particular dairy is very close to perfectly elastic. If the
dairy’s managers raise its price, no one buys from the dairy because they can buy
from hundreds of thousands of other dairies, so the quantity demanded falls to
zero. If the dairy’s managers lower its price, everyone in the world will want to
buy from it. When demand is perfectly elastic, the elasticity is defined to equal
infinity 1∞2. A horizontal demand curve is the flattest possible demand curve,
showing the largest possible response. As illustrated in Figure 3.13(a), all points on
a horizontal demand curve are perfectly elastic.

Perfectly inelastic demand means consumer response to a change in the
price is the smallest possible response: no change in the quantity demanded. The
demand for a lifesaving drug can be perfectly inelastic: Whether managers raise
the price or lower the price, consumers will buy the same quantity. When
demand is perfectly inelastic, the price elasticity of demand equals 0. A vertical
demand curve is the steepest possible demand curve, showing the smallest pos-
sible response. As Figure 3.13(b) shows, all points on a vertical demand curve are
perfectly inelastic.

Factors Affecting the Size of the Price Elasticity of Demand
Skilled managers often try to change the price elasticity of demand for their product
to increase their firm’s profit. But to be able to affect the price elasticity of demand,
you must understand the factors involved.

Perfectly elastic demand
Demand is perfectly elastic
when a change in the price
creates the largest
possible response in the
quantity demanded: A rise
in the price decreases the
quantity demanded to zero,
and a fall in the price
increases the quantity
demanded to infinity.

Perfectly inelastic demand
Demand is perfectly
inelastic when a change in
the price creates the
smallest possible response:
There is no change in the
quantity demanded.

Figure 3.12 Elastic Demand and Inelastic Demand

At point A, where the demand curves cross, the
difference in the lengths of the arrows shows that the
quantity demanded along demand curve D2 responds
more strongly to the price hike from $15 to $20 than
the quantity demanded along demand curve D1. So, the
price elasticity of demand at point A is larger on demand
curve D2 than on demand curve D1.

Price (dollars per baseball cap)

Quantity (baseball caps per day)

$35

$5

$10

70605040302010

$15

$20

$25

$30

0

D2
D1

A

M03_BLAI8235_01_SE_C03_pp86-137.indd 110 23/08/17 9:53 AM

3.4 Elasticity  111

Two general factors influence the size of the price elasticity of demand: the num-
ber of close substitutes and the fraction of the budget spent on the product. There is
no formula into which you can plug these factors to calculate a precise value.
Nonetheless, these factors provide valuable insights into the size of the price elastic-
ity of demand for a product and how you might be able to change it to your
advantage.

The Number of Close Substitutes The larger the number of close substitutes for
a product, the larger its price elasticity of demand. You probably already under-
stand intuitively that the existence of a large number of close substitutes means
that consumers will respond strongly to a price change. For example, New Balance
athletic shoes have many substitutes, including Nike, Converse, and Puma. When
the price of New Balance shoes rises, the quantity demanded will decrease sub-
stantially because consumers can switch to one of the many other substitute shoes.
Alternatively, when the price falls, the quantity demanded will increase as con-
sumers switch away from the many other brands of shoes they had been buying to
the now-cheaper New Balance shoes.

Of course, the reverse also applies: The smaller the number of close substitutes,
the smaller the price elasticity of demand. The same intuition applies: When the
price rises, consumers cannot decrease the quantity they demand by much because

Figure 3.13 Perfectly Elastic Demand and Perfectly Inelastic Demand

(a) Perfectly Elastic Demand
At any point on the horizontal demand curve for
the milk from a particular dairy demand is perfectly
elastic, so the elasticity equals ∞ at all points on
the demand curve.

(b) Perfectly Inelastic Demand
At any point on the vertical demand curve for a
lifesaving drug demand is perfectly inelastic, so
the elasticity equals 0 at all points on the demand
curve.

Price (dollars per gallon of milk)

Quantity (thousands of gallons
of milk per month)

$1.75

$0.25

$0.50

700

D

500 600300 400100 200

$0.75

$1.00

$1.25

$1.50

0

Price (dollars per dose)

Quantity (millions of
doses per year)

$140

$20

$40

7

D

5 63 41 2

$60

$80

$100

$120

0

M03_BLAI8235_01_SE_C03_pp86-137.indd 111 23/08/17 9:53 AM

112  CHAPTER 3 Measuring and Using Demand

of a lack of alternatives. And when the price falls, there is not much switching away
from other substitutes precisely because there are not many substitutes. This result is
why the price elasticity of demand for gasoline, a product with few substitutes, is
much smaller than the price elasticity of demand for New Balance shoes, a product
with many substitutes.

The general principle that the availability of more substitutes leads to a larger
price elasticity of demand has three implications:

1. The more broadly defined the product, the smaller the price elasticity of de-
mand. For instance, soda is a broadly defined product that includes all types
of carbonated beverages, including Pepsi-Cola, Coca-Cola, and Mountain
Dew. In contrast, Pepsi-Cola is narrowly defined to only that drink. Economists
have estimated that the price elasticity of demand for soda is 0.80, while that
for Pepsi is 1.55. Why is the price elasticity of demand for soda so much
smaller than the price elasticity of demand for Pepsi? The answer is that soda
has fewer substitutes than Pepsi. Fruit drinks, energy drinks, coffee, and other
liquids serve as substitutes for soda. All of these other products can substitute
for Pepsi, plus all other types of soda also can substitute for Pepsi. So a nar-
rowly defined, specific product such as Pepsi has many more substitutes and
hence a larger price elasticity of demand than a broadly defined, general
product such as soda.

This distinction can save you from making erroneous decisions. For exam-
ple, suppose that you are the brand manager for the Ford Focus and are con-
sidering raising the price by 2 percent. To help with the decision, you want to
forecast how the change in price will affect sales. Suppose that you do not
have an estimate of either the demand curve or the price elasticity of demand
for the Focus. Analysts have estimated the price elasticity of demand for the
broader category of automobiles to be 0.9. You might be tempted to use this
elasticity as your estimate of the price elasticity of demand for the Focus. If
you use this number, your forecast is that sales of the Focus will decrease by
0.9 * 2 percent = 1.8 percent. But you want the elasticity for the Ford Focus,
not the elasticity for automobiles in general. The Focus is a more specific
product, so its price elasticity of demand is larger than the price elasticity of
demand for automobiles. Indeed, the price elasticity of demand for a Ford
compact car, such as the Focus, has been estimated to be 6.0, changing the
forecasted decrease in sales to 6.0 * 2 percent = 12.0 percent. Using the price
elasticity of demand for a general product category such as cars rather than
the specific product under consideration (the Focus) could lead you to a bad
decision!

2. A luxury good has a larger price elasticity of demand than does a necessity.
Luxury goods have more substitutes than necessities. For instance, compare
a cruise vacation to toothpaste. A cruise easily qualifies as a luxury. Most
people (hopefully) classify toothpaste as a necessity. There are many more
substitutes for cruises than for toothpaste. Instead of going on a cruise, peo-
ple can tour Europe by rail, go on a safari in Africa, trek through Alaska,
spend time at a beach house, or enjoy any number of alternatives. There are
not nearly as many substitutes for toothpaste. Baking soda might qualify, but
it is not a close substitute for toothpaste (and it does not taste as good!). The
fact that there are more substitutes for luxuries than necessities helps explain
why the price elasticity of demand for luxuries is larger than that for
necessities.

M03_BLAI8235_01_SE_C03_pp86-137.indd 112 23/08/17 9:53 AM

3.4 Elasticity  113

3. The more time that has elapsed since a price change, the larger the price elas-
ticity of demand. This result again hinges on the number of substitutes.
Consider a price hike. The quantity demanded immediately decreases a little,
but many consumers who are buying the good will not immediately know of
substitutes. As time passes, consumers will search for, find, and buy substitutes.
This additional switch away from the now-higher-priced good makes the de-
crease in its quantity demanded larger. Consequently, the price elasticity of de-
mand increases in size as time passes. The effect of a price cut is analogous:
Immediately after the price of an item falls, few consumers are aware of the
price drop, so the increase in the quantity demanded is small. As time passes,
more consumers learn of the lower price and switch from other alternatives to
the good with the lower price, so its quantity demanded and its price elasticity
of demand both increase. The managerial implication is clear: Advertise price
reductions so that more consumers know of them immediately, thereby increas-
ing the price elasticity of demand for your product. On the flip side, conceal
price hikes so that fewer consumers are immediately aware of them, thereby
delaying the inevitable increase in the price elasticity of demand.

The effect on the demand and the price elasticity of demand for existing
products is not immediate when a firm introduces a new substitute product to
the marketplace for the same reason that the effect of a price change is spread
out over time: It takes consumers time to learn of the new product and its prop-
erties. For example, in 2011, Bayer AG, a large German pharmaceutical company,
received approval to market a first-in-its-class drug, Xarelto, to combat deep
vein thrombosis (DVT). (A deep vein thrombosis occurs when a blood clot in a
vein deep in the body forms. If part of the clot breaks free, it may travel to the
lungs with fatal consequences.) Although other drugs existed to fight DVT, be-
cause of its unique attributes, Xarelto had no close substitutes and, consequently,
a relatively small price elasticity of demand. In 2014, Pfizer and Bristol-Meyers
Squibb received approval to combat DVT with their similar drug, Eliquis.
Because the presence of Eliquis gave Xarelto a close substitute, analysts believed
that Xarelto’s market share would quickly fall and its price elasticity of demand
would quickly rise. This forecast turned out to be incorrect. Xarelto’s three-year
lead over Eliquis meant that physicians were familiar with Xarelto and its ef-
fects. It took physicians some time to become as familiar with the new substitute,
Eliquis. As time passed and physicians learned about Eliquis’s effects, Xarelto’s
market-share growth slowly fell, and due to the increased knowledge and use of
the new substitute, presumably its price elasticity of demand slowly rose.

As a manager, you can attempt to alter elasticity to your benefit. For example, if
you are planning to boost your price, you definitely want consumers to believe that
your product has no close substitutes because a lack of substitutes will lower
the price elasticity of demand for your product and limit the decrease in sales from
the price hike. To create this view, you want your advertisements to stress the
unique properties of your product and make consumers believe that it is irreplace-
able. Alternatively, you want consumers to think that your product will readily take
the place of many other products if you are planning to cut your price. If consumers
believe that your product can serve as a substitute for many alternatives, the price
elasticity of demand for your product will be larger, which in turn means your sales
increase will be larger after the price cut. If you are planning to introduce a new
product, you need to get information out to potential consumers rapidly so that
they can see how your product will substitute for products already on the market.

M03_BLAI8235_01_SE_C03_pp86-137.indd 113 23/08/17 9:53 AM

114  CHAPTER 3 Measuring and Using Demand

The Fraction of the Budget Spent on the Product The second general factor
affecting the size of the price elasticity of demand is the fraction of buyers’ bud-
gets spent on the product. The larger the fraction, the larger the price elasticity of
demand. Intuitively, if a product accounts for only a small fraction of consumers’
budgets, they are less likely to react to a price change. The change in the quantity
demanded and the price elasticity of demand will be small. However, if the prod-
uct accounts for a large fraction of consumers’ budgets, they notice and respond
to the price change, which makes the price elasticity of demand larger. This effect
goes a long way toward understanding the difference in the price elasticity of
demand for housing (1.2) and that for salt (0.1). Of course, you need to keep in
mind that salt is a larger fraction of the budget for some consumers than for others.
For instance, the City of Rochester, New York, spends a bit more than 1 percent of
its total budget, or near $7 million per year, on snow and ice removal; a substantial
part of that amount goes toward the purchase of salt to help remove snow and ice.
Salt accounts for a larger part of Rochester ’s budget than for most consumers, so
Rochester ’s price elasticity of demand for salt is probably larger than that of most
consumers.

Price Elasticity of Demand and Total Revenue
Managers who know whether the demand for their product is elastic or inelastic
find it easier to make good decisions. Sometimes these decisions revolve around
the total revenue of their product. As you learned in Chapter 1, the total revenue
of a product (TR) is the total amount collected from sales of the product; it equals
the price of the product (P) multiplied by the quantity sold (Q). In equilibrium,
the quantity sold equals the quantity consumers demand 1Qd2, so TR = P * Qd.
Total revenue is not the same as total profit. To get the total profit, you must sub-
tract the total opportunity cost from the total revenue. In some cases, however,
the total revenue rather than total profit can be relevant to your decisions. Here
are some examples:

• Authors and musicians receive royalties based on a percentage of the total reve-
nue from their creation.

• Universities and professional sports teams often negotiate royalties based
on the total revenue from sales of paraphernalia or clothing adorned with
their logo.

• Small biotech companies frequently license their drugs to large pharmaceutical
companies in exchange for a percentage of the total revenue from sales of the
drug.

In all of these cases, understanding the relationship among total revenue,
changes in price, and price elasticity of demand enhances decision making. Consider
an increase in the price of a product. What will be the effect on the total revenue?
Using the definition of total revenue, TR = P * Qd, the answer might seem clear:
The increase in price boosts the total revenue. But that quick answer is too simple
because it neglects the fact that an increase in price decreases the quantity de-
manded, which offsets the effect of the higher price. The net effect of a price hike on
total revenue depends on whether the increase in price or the decrease in quantity is
larger. In turn, that depends on how strongly consumers respond to the increase in
price: Do they respond strongly (with a substantial decrease in the quantity de-
manded), or do they respond weakly (with only a minor decrease in the quantity
demanded)?

M03_BLAI8235_01_SE_C03_pp86-137.indd 114 23/08/17 9:53 AM

3.4 Elasticity  115

Because the price elasticity of demand measures the strength of the response, it
plays a key role in determining the effect of a price change on the total revenue. Take
the case of a price increase:

• Elastic demand. If the demand for the good is elastic, then the response to a
price hike will be a large decrease in the quantity demanded, so that the total
revenue decreases.

• Inelastic demand. If the demand for the good is inelastic, then the response
to a price hike will be a small decrease in the quantity demanded, so that the
total revenue increases.

• Unit-elastic demand. If the demand for the good is unit-elastic, then the
response to a price hike will be a decrease in the quantity demanded by a pro-
portionally equal amount, so that the total revenue does not change.

Clearly, the effect of a change in the price on total revenue depends on the price
elasticity of demand. The following box summarizes this relationship in what is
called the total revenue test.

If E 7 1 1 Demand is elastic (consumers respond strongly to a price change).
• Price hike 1 Larger percentage decrease in quantity 1Total revenue decreases:

P c , Qd T 1 TR T
• Price cut 1 Larger percentage increase in quantity 1 Total revenue increases:

P T, Qd c 1 TR c
If E = 1 1 Demand is [email protected] (consumers respond one-to-one to a price change).
• Price hike 1 Equal percentage decrease in quantity 1 Total revenue does not

change: P c , Qd T 1 TR S
• Price cut 1 Equal percentage increase in quantity 1 Total revenue does not

change: P T , Qd

T

1 TR S

If E 6 1 1 Demand is inelastic (consumers respond weakly to a price change).
• Price hike 1 Smaller percentage decrease in quantity 1 Total revenue

increases: P c , Qd T 1 TR c
• Price cut 1 Smaller percentage increase in quantity 1Total revenue decreases:

P T , Qd c 1 TR T

TOTAL REVENUE TEST

Although the total revenue test can be proven mathematically, the intuition
behind the test is extremely strong. (If you’re interested in the proof, see Section 3.B
of the Appendix at the end of this chapter.) The test is divided into three parts:

1. Elastic demand. An increase in the price 1P T2 leads to a decrease in the quan-
tity demanded 1Qd T 2. Because the demand is elastic, the percentage decrease in
the quantity demanded exceeds the percentage increase in the price, so the T
quantity arrow is larger than the

T

price arrow. Consequently, total revenue,
P * Qd, decreases 1TR T 2 because the percentage decrease in the quantity
exceeds the percentage increase in the price.

M03_BLAI8235_01_SE_C03_pp86-137.indd 115 23/08/17 9:53 AM

116  CHAPTER 3 Measuring and Using Demand

2. Unit-elastic demand. The percentage increase in the price equals the percentage
decrease in the quantity demanded, which makes the arrows next to P and Qd
the same size. In this case, the effect on total revenue from the decrease in the
quantity demanded exactly offsets the effect from the higher price, so the total
revenue does not change 1TR S 2.

3. Inelastic demand. An increase in the price 1P c 2 leads to a decrease in the quan-
tity demanded 1Qd T 2, but the percentage decrease in the quantity demanded is
less than the percentage increase in the price, so the c price arrow is larger than
the T quantity arrow. The total revenue increases 1TR c 2.

Figure 3.14(a) uses the linear demand curve from Figure 3.10 to show the relation-
ship of the changes in total revenue and elasticity along a linear, downward-sloping
demand curve. When demand is elastic, the range from $30 to $15 per baseball cap,
lowering the price and increasing the quantity demanded increase the total revenue.
When demand is inelastic, the range from $15 to $0 per cap, lowering the price and
increasing the quantity demanded decrease the total revenue. As the figure illus-
trates, along a linear demand curve, the total revenue equals its maximum when the
price elasticity of demand equals 1.0.

Suppose that you are an executive in a biotech company that has licensed a
drug to Pfizer and will receive a royalty of 10 percent of the total revenue Pfizer
collects from the sale of the drug. Your goal is to have Pfizer set the price that

Figure 3.14 Relationship Between Total Revenue and Elasticity Along a Linear, Downward-Sloping Demand Curve

(a) Linear Demand Curve
Moving down along a downward-sloping linear
demand curve by lowering the price, the price
elasticity of demand falls in value.

(b) Total Revenue
When demand is elastic, moving down along the
demand curve by lowering the price increases the
total revenue. When demand is inelastic, however,
moving down along the demand curve by lowering
the price decreases the total revenue. The total
revenue reaches its maximum when the price
elasticity of demand equals 1.0.

Price (dollars per baseball cap)

Quantity (baseball caps per day)

$35

$5

$10

70
D

605040302010

$15

$20

$25

$30

0

A

B

e 5 5.0

e 5 2.0

e 5 1.0

e 5 0.5

e 5 0.2e . 1

e 5 1

e , 1

Total Revenue (dollars)

Quantity (baseball caps per day)

$525

$75

$150

70
TR

605040302010

$225

$300

$375

$450

0

e , 1e . 1 e 5 1

e 5 5.0

e 5 2.0 e 5 0.5

e 5 1.0

e 5 0.2

M03_BLAI8235_01_SE_C03_pp86-137.indd 116 11/09/17 10:36 AM

3.4 Elasticity  117

maximizes Pfizer ’s total revenue because that will maximize your royalty and
profit. Knowing the price elasticity of demand for your drug is important to
you. For example, if your drug is the only one to treat an illness, Pfizer has a
monopoly. In other words, it is the only seller in the market. You will learn in
Chapter 6 that because Pfizer has a monopoly, its profit-maximizing price for
the product will fall in the elastic range of the demand. Accepting this result,
you can see that when you license your drug to Pfizer, you need to push Pfizer
to cut the price from what it wants to set because the total revenue test shows
that when demand is elastic, a decrease in the price increases total revenue. If
Pfizer ’s total revenue increases, the royalty revenue your company receives will
get a boost as well. Of course, Pfizer will resist lowering the price, but because
you know that the demand for the drug is elastic, your biotech company will
keep pressuring Pfizer.

Your marketing department estimates that at the current price and quantity, your
firm’s product has a price elasticity of demand of 1.1. You run an advertising cam-
paign that changes the demand, so that at the current price and quantity the elas-
ticity falls to 0.8. In response to this change, would you raise the price, lower it, or
keep it the same? Explain your answer.

Answer
You should raise your price. Before the advertising campaign, the demand for
your product was elastic, so according to the total revenue test, a price hike
would lower your firm’s total revenue. After the campaign, the demand became
inelastic. You now will be able to increase your firm’s profit by raising the price.
Because the demand is inelastic, a price hike raises your firm’s total revenue. A
price hike also decreases the quantity demanded, so your firm produces less,
which decreases your costs. Raising revenue and lowering cost unambiguously
boost your firm’s profit!

DECISION
SNAPSHOT

Advertising and the Price Elasticity
of Demand

Income Elasticity and Cross-Price Elasticity of Demand
So far, you have learned about only one type of elasticity, the price elasticity of
demand. Although this is the most important elasticity, there are two others to
keep in mind: the income elasticity of demand and the cross-price elasticity of
demand. You are unlikely to use either of these two measures often, but under-
standing the different types of elasticity will help you avoid confusing them. In
addition, learning about income elasticity and cross-price elasticity will help rein-
force your understanding of the price elasticity of demand because all elasticities
have four points in common: (1) changes are expressed as percentages, (2) fractions
are used, (3) the factor driving the change is in the denominator, and (4) the factor
responding to the change is in the numerator. (The Appendix at the end of this
chapter presents a calculus treatment of these elasticities.)

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118  CHAPTER 3 Measuring and Using Demand

Income Elasticity of Demand
The income elasticity of demand measures how strongly the quantity demanded
responds to a change in consumers’ income. The income elasticity of demand 1eINC2
is defined as the percentage change in the quantity demanded divided by the per-
centage change in income:

eINC =
1Percentage change in the quantity demanded2

1Percentage change in income2
The definition differs from that of the price elasticity of demand in one import-

ant respect: The price elasticity of demand uses the absolute value, but the income
elasticity of demand does not. The reason for this difference is straightforward. The
price elasticity of demand is always negative, so its sign is inconsequential. In con-
trast, the income elasticity of demand is positive for a normal good and negative for
an inferior good. Recall that an increase in income (a positive change in income)
leads to an increase in demand for a normal good (which, for a given price, means a
positive change in the quantity demanded). Therefore, the income elasticity of de-
mand for a normal good equals one positive number divided by another, so the re-
sulting elasticity is positive. In contrast, an increase in income leads to a decrease in
demand for an inferior good. Therefore, the income elasticity of demand for an infe-
rior good equals a negative number divided by a positive number, and the resulting
elasticity is negative. Because the sign of the income elasticity of demand indicates
whether the good is normal or inferior, the absolute value is not used.

Goods with income elasticities that exceed 1.0 are called luxury goods. Air travel,
Caribbean cruises, and fine dining are examples of luxury goods. If you are a man-
ager of a company producing a luxury good, such as steak dinners, you must keep
an eye on forecasts of how income is changing. Any change in income will affect the
demand for your product, and the change in demand will be larger than the change
in income. So the effect on your business will be very important.

Goods with income elasticities between zero and 1.0 are called necessities.
Groceries, gasoline, and shampoo are examples of necessities. If you are a manager of
a company producing a necessity, changes in consumers’ income are not as important

to you. Any change in income will affect the
demand for your product, but the change will be
smaller than the change in income. It will affect
your business, but the effect will be minor.

Table 3.2 summarizes the key points about the
income elasticity of demand, including its formula
and the meaning of a positive or negative sign.

Cross-Price Elasticity of Demand
The cross-price elasticity of demand measures how strongly the quantity demanded
responds to a change in the price of a related product. The cross-price elasticity of
demand 1eCROSS2 is equal to the percentage change in the quantity demanded di-
vided by the percentage change in the price of the related good:

eCROSS =
1Percentage change in the quantity demanded2

1Percentage change in the price of the related good2
The cross-price elasticity of demand is similar to the income elasticity of

demand—and different from the price elasticity of demand—with regard to

Cross-price elasticity of
demand A measure of
how strongly the quantity
demanded changes when
the price of a related
product changes; it equals
the percentage change in
the quantity demanded
divided by the percentage
change in the price of the
related product.

Table 3.2 Income Elasticity of Demand

• eINC =
1Percentage change in the quantity demanded2

1Percentage change in income2
• eINC is positive for a normal good.

• eINC is negative for an inferior good.

Income elasticity of
demand A measure of
how strongly the quantity
demanded responds to a
change in consumers’
income; it equals the
percentage change in the
quantity demanded divided
by the percentage change
in income.

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3.4 Elasticity  119

absolute value. The cross-price elasticity of demand does not use the absolute
value because the sign of the elasticity again provides information about the rela-
tionship of the products. Consider substitutes. Nike athletic shoes are a substitute
for New Balance athletic shoes. A rise in the price of the substitute good, Nike
athletic shoes, leads to an increase in demand (and, for any price, an increase the
quantity demanded) for New Balance athletic shoes. For substitutes, the cross-
price elasticity of demand equals one positive number divided by another, so the
resulting elasticity is positive. For complementary goods, such as hot dogs and
hot dog buns at a grocery store, an increase in the price of a complement leads to a
decrease in the quantity demanded of the first good. For complements, the cross-
price elasticity of demand equals a
negative number divided by a positive
number, so the cross-price elasticity of
demand is negative for complements.

Table 3.3 summarizes the key points
about the cross-price elasticity of
demand, including its formula and the
meaning of a positive or negative sign.

The Price Elasticity of Demand for a Touch-Screen Smartphone

When Apple introduced the iPhone in 2007, it was one of the first smartphones to have
a touch screen. You are a manager at a smartphone company similar to Apple and your
company has quickly introduced its own smartphone with a touch screen.

a. Suppose your marketing department tells you that the demand curve for your
smartphone is Qd = 9,900,000 – 19,000 * P2. The price is $650, and the
predicted quantity demanded is 4,050,000. At that price and estimated quantity,
what is the price elasticity of demand for your smartphone?

b. At a sales meeting, some of the participants ask you what would happen to total
revenue if you raised the price by 2 percent. Do not calculate the change in revenue;
instead, just indicate whether your total revenue would rise, fall, or not change.

c. It’s now a few years later, and other companies, like HTC and Samsung, have introduced
smartphones with touch screens. How did introduction of these new phones affect the
price elasticity of demand for your touch-screen smartphone? Explain your answer.

Answer

a. The price elasticity of demand can be calculated using the estimated demand
function and Equation 3.5. Using this equation, the price elasticity of demand equals

� – 9,000 * 1$650/4,050,0002 � = 1.44
b. At this point on the demand curve, the demand is elastic. The total revenue test shows

that when the demand is elastic, an increase in price decreases total revenue. So if you
raised the price of your smartphone by 2 percent, your total revenue would decrease.

c. The new smartphones with touch screens are substitutes for your smartphone. The
presence of more substitutes increases the price elasticity of demand, so as time
passed after the new phones were introduced, the price elasticity of demand for
your smartphone increased.

SOLVED
PROBLEM

Table 3.3 Cross-Price Elasticity of Demand

• eCROSS =
1Percentage change in the quantity demanded2

1Percentage change in the price of the related good2
• eCROSS is positive for substitute goods.

• eCROSS is negative for complementary goods.

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120  CHAPTER 3 Measuring and Using Demand

3.5 Regression Analysis and Elasticity
Learning Objective 3.5 Use regression analysis and the different elasticity
measures to make better managerial decisions.

Regression analysis and the different elasticity measures are important to managers
because they help quantify decision making. As a manager, you will face situations
in which you need to know the exact amount of a change in the price of an input,
the precise change in your cost when you change your production, or the actual
decrease in quantity demanded when you raise the price of your product.
Regression analysis and the application of the different elasticity measures can help
you answer these and many other important questions.

Using Regression Analysis
Using the results from regression analysis is an essential task in many managerial
positions. Analysts can use regression analysis for much more than estimating a
demand curve. For example, you can use it to estimate how your costs change when
production changes. We explain this important concept, called marginal cost, in
Chapter 4 and use it in all future chapters. Large companies with demand that
depends significantly on a specific influence often use regression analysis to forecast
changes in such factors as personal income (important to automobile manufacturers
such as General Motors and Honda) or new home sales (important to home improve-
ment stores such as Home Depot and Lowe’s).

The ultimate goal of regression analysis is to help you make better decisions. For
example, as a manager at the high-end steak restaurant chain, you can use an esti-
mated demand function to help you make both immediate decisions about the price
to set and long-term decisions about whether to open a new location. Suppose that
an analyst for your firm has used regression to determine that the nightly demand
for your chain’s steak dinners depends on the following factors:

1. The price of the dinners, measured as dollars per dinner
2. The average income of residents living within the city, measured as dollars per

person
3. The unemployment rate within the city, measured as the percentage unemploy-

ment rate
4. The population within 30 miles of the restaurant

Suppose that Table 3.4 includes the estimated coefficients and their standard er-
rors, t-statistics, and P-values.4 The R2 of the regression is 0.72, so the regression pre-
dicts the data reasonably well. In the table, the t-statistics for all five coefficients are
greater than 1.96, and accordingly all five P-values are less than 5 percent (0.05).
Therefore, you are confident that all the variables included in the regression affect
the demand for steak dinners. The coefficient for the price variable, −12.9, shows that
a $1 increase in the price of a dinner decreases the quantity demanded by – 12.9 * $1,
or 12.9 dinners per night. Similarly, the coefficient for the average income variable,
0.0073, shows that a $1,000 increase in average income increases the demand by
0.0073 * 1,000, or 7.3 dinners per night. The coefficient for the unemployment rate

MANAGERIAL
APPLICATION

4 Often regression results are written with the standard errors in parentheses below the estimated coefficients:
Qd = 139.2 – 112.9 * PRICE2 + 10.0073 * INCOME2 – 110.0 * UNEMPLOYMENT2 + 10.0005 * POPULATION2
(11.9) (1.8) (0.0012) (3.2) (0.0002)

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3.5 Managerial Application: Regression Analysis and Elasticity  121

variable, – 10.0, shows that a one percentage point increase in the unemployment
rate decreases the demand by – 10.0 * 1, or 10 dinners per night. And the coefficient
for the population variable, 0.0005, shows that a 1,000-person increase in population
increases the demand by 0.0005 * 1,000, or 0.5 dinners per night.

Short-Run Decisions Using Regression Analysis
Although a more detailed explanation of how managers determine price must wait until
Chapter 6, intuitively it is clear that demand must play a role. The estimated demand
function can help determine what price to charge in different cities because you can use
it to estimate the nightly quantity of dinners your customers will demand in those cities.
Suppose that one of the restaurants is located in a city of 900,000 people, in which aver-
age income is $66,300 and the unemployment rate is 5.9 percent. If you set a price of $60
per dinner, you can predict that the nightly demand for steak dinners equals

Qd = 139.2 – 112.9 * $602 + 10.0073 * $66,3002 – 110.0 * 5.92 + 10.0005 * 900,0002
or 240 dinners per night. You can now calculate consumer response to a change in
the price. For example, if you raise the price by $1, then the quantity of dinners de-
manded decreases by 12.9 per night, to approximately 227 dinners.

Long-Run Decisions Using Regression Analysis
You can also use the estimated demand function to forecast the demand for your
product. Such forecasts can help you make better decisions. For example, you and the
other executives at your steak chain might be deciding whether to open a restaurant
in a city of 750,000 residents, with average income of $60,000 and an unemployment
rate of 6.0 percent. Using the estimated demand function in Table 3.4 and a price of
$60 per dinner, you predict demand of about 118 meals per night. Suppose this quan-
tity of sales is too small to be profitable, but you expect rapid growth for the city: In
three years, you forecast the city’s population will rise to 950,000, average income will
increase to $70,000, and the unemployment rate will fall to 5.8 percent. Three years
from now, if you set a price of $60 per dinner, you forecast the demand will be 293
dinners per night. This quantity of dinners provides support for a plan to open a
restaurant in three years. You might start looking for a good location!

Other companies can use an estimated demand function to forecast their future
input needs. General Motors, for example, can use an estimated demand function
for their automobiles to forecast the quantity of steel it expects to need for next
year’s production. This information can help its managers make better decisions
about the contracts they will negotiate with their suppliers.

Table 3.4 Estimated Demand Function for Steak Dinners

The table shows the results of a regression of the demand for meals at an upscale steak restaurant, with the
estimated coefficients for the price, average income in the city in which the restaurant is located, unemployment
rate in the city, and population of the city.

Coefficient Standard Error t Stat P-value Lower 95% Upper 95%

Constant 139.2 11.9 11.7 0.00 117.3 163.1

Price of dinner −12.9 1.8 7.2 0.00 −9.4 −16.4

Average income 0.0073 0.0012 6.1 0.00 4.9 9.7

Unemployment rate −10.0 3.1 3.1 0.00 −3.9 −16.5

Population 0.0005 0.0002 2.5 0.02 0.0001 0.0009

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122  CHAPTER 3 Measuring and Using Demand

5 This estimate is from Lihong McPhail and Bruce Babcock, “Impact of US Biofuel Policy on US Corn and
Gasoline Price Variability,” Energy, January 2012, p. 509.

Using the Price Elasticity of Demand
There might be situations in which you need information about a demand but can-
not obtain what you need from regression analysis, perhaps because you lack the
necessary data. In such cases, you might be able to take advantage of preexisting
estimates of the price elasticity of demand, based on either your previous experience
or one of the many available estimates in print or on the Internet.

Suppose that your career leads you to an executive position with a company similar
to Pacific Ethanol, an ethanol producer with plants located in the western United States.
Because your company uses field corn to make ethanol, corn is a significant expense.
(Field corn—also called cow corn—is less sweet than the corn people eat.) You read a
report predicting that bad weather during the growing season will decrease the supply
of field corn by 3 percent. As you learned in Chapter 2, a decrease in supply will raise
the price; with this information, you can immediately forecast that the price of corn will
rise. For planning purposes, however, you need a more precise forecast: By how much
will the price of corn rise? You lack the data needed to estimate a demand curve for
corn, but estimates of the price elasticity of demand for corn are easy to obtain.
According to one such estimate, the price elasticity of demand for field corn is 0.2.5
Using this estimate, you can forecast that the percentage rise in the price of corn will
equal (3 percent decrease in quantity)>10.22 = 15 percent. You now know that you
must either prepare for a large increase in your costs or try to moderate the increase,
perhaps by signing contracts to lock in the price of corn at a lower level.

In later chapters, you will learn that you also can use the price elasticity of
demand to help you make pricing decisions (see Sections 6.2, 6.3, and 10.1). In the
meantime, it should be obvious that the price elasticity of demand is useful to man-
agers because they can use it to determine the change in the quantity demanded
with a change in price.

Using the Income Elasticity of Demand Through the
Business Cycle
The income elasticity of demand is similarly useful in making better managerial
decisions. For example, suppose that the income elasticity of demand for new auto-
mobiles is 1.9. Because it is a positive number, new automobiles are a normal good—
demand increases when the economy is expanding and people’s incomes are
growing, and demand decreases when the economy is in a business cycle recession
and people’s incomes are falling. Because the value exceeds 1, the swings in demand
for automobiles are larger than the changes in income. If you are a manager at Kia
Motors Corporation (the South Korean automotive company), when you make deci-
sions about your future production plans, you must keep in mind that rapid growth
in demand for automobiles in a growing economy might be followed by an equally
rapid decrease in demand in response to a recession.

For a contrasting example, say that you are a manager at FirstGroup plc (the
British-based owner of Greyhound Lines, which offers inter-city bus travel). The
income elasticity of demand for intercity bus travel is negative because it is an inferior
good. Your planning must take into account the decrease in demand for your product
in a growing economy and the increase in demand during a recession. The magnitude
of the income elasticity of demand will provide information about the sizes of the
changes in demand, and you can use that information to improve your decisions.

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Revisiting How Managers at the Gates Foundation Decided
to Subsidize Antimalarial Drugs

As noted at the beginning of the chapter, the manag-ers at the Bill and Melinda Gates Foundation want to
use their funds in the best way possible. Because wast-
ing their resources means that people could die unneces-
sarily, managers at the foundation want to fund the most
cost-effective programs. To achieve that goal, they must
determine the quantitative impact of the proposals pre-
sented to them.

In the case of the proposals to subsidize antimalarial
drugs in Kenya and other nations, the managers were unlikely
to have an estimated demand curve for the drugs in these
countries because of data limitations. Instead, they proba-
bly relied on estimates of the price elasticity of demand to
determine the increase in the quantity of drugs demanded.

The subsidy programs lowered the price of these
drugs between 29 percent and 78 percent (the fall in
price differed from nation to nation and from drug to
drug). Overall, the average decrease in price was roughly
50 percent. Because there are few substitutes, the demand
for pharmaceutical drugs is price inelastic. The price elas-
ticity of demand for pharmaceutical drugs for low-income
Danish consumers is estimated to be 0.31. Denmark and

Kenya differ in an important respect: Low-income consum-
ers in Kenya have much lower incomes than their coun-
terparts in Denmark. Consequently, the expenditure on
drugs in Kenya is a much larger fraction of consumers’
income, which means that the price elasticity of demand
for drugs in Kenya is larger than in Denmark. If the man-
agers at the Bill and Melinda Gates Foundation estimated
that the price elasticity of demand for drugs in Kenya
was about twice that in Denmark-—say, 0.60-—they
could then predict that lowering the price of the drugs
by 50 percent would increase the quantity demanded by
50 percent * 0.60 = 30 percent.

The Gates Foundation funded the proposals to sub-
sidize antimalarial drugs. The actual outcome was that
the quantity of the drugs demanded in the different na-
tions increased by 20 to 40 percent. The quantitative
estimate was right in line with what occurred. Using
the price elasticity of demand to estimate the impact of
the drug subsidy proposals allowed the managers at the
foundation to compare them to competing proposals
and to make decisions that saved the maximum number
of lives.

Summary: The Bottom Line
3.1 Regression: Estimating Demand
• Regression analysis is a statistical tool used to estimate

the relationships between two or more variables.
• Regression analysis assumes that the function to be es-

timated has a random element. The estimated coeffi-
cients minimize the sum of the squared residuals
between the actual values of the dependent variable
and the values predicted by the regression.

3.2 Interpreting the Results of Regression
Analysis

• The coefficients estimated by a regression change
when the data change. The statistical programs used in
regression analysis calculate confidence intervals for
each estimated coefficient. For the 95 percent confi-
dence interval, the value of the true coefficient falls
within the interval 95 percent of the time.

• The P-value indicates whether an estimated coefficient is
statistically significantly different from zero. If the P-
value is 5 percent (0.05) or less, then you can be 95 percent
confident that the true coefficient is not equal to zero.

• The R2 statistic, which measures the overall fit of the
regression, varies between 100 percent (the predicted
values capture all the variation in the actual dependent
variable) and 0 (the predicted values capture none of
the variation in the actual dependent variable).

3.3 Limitations of Regression Analysis
• Managers should examine regressions reported to

them to be certain that all the relevant variables are
included.

• Managers should determine whether a regression’s
functional form (curve or straight line) is the best fit for
the data.

3.4 Elasticity
• The price elasticity of demand measures how strongly

the quantity demanded responds to a change in the
price of a product. It equals the absolute value of the
percentage change in the quantity demanded divided
by the percentage change in the price.

Summary: The Bottom Line  123

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124  CHAPTER 3 Measuring and Using Demand

• If the price elasticity of demand exceeds 1.0, consum-
ers respond strongly to a change in price, and demand
is elastic. If the price elasticity of demand equals 1.0,
demand is unit elastic. If the price elasticity of demand
is less than 1.0, consumers respond weakly to a change
in price, and demand is inelastic.

• The more substitutes available for the product and the
larger the fraction of the consumer’s budget spent on
the product, the larger the price elasticity of demand.

• The income elasticity of demand equals the percentage
change in the quantity demanded divided by the per-
centage change in income. It is positive for normal
goods and negative for inferior goods.

• The cross-price elasticity of demand equals the per-
centage change in the quantity demanded of one good

divided by the percentage change in the price of a re-
lated good. It is positive for products that are substi-
tutes and negative for those that are complements.

3.5 Managerial Application: Regression
Analysis and Elasticity

• Regression analysis can estimate a firm’s demand
function and other important relationships. You can
use the estimated functions to make forecasts and pre-
dictions that improve your decisions.

• When there are not enough data to estimate a demand
function, you can use the price elasticity of demand,
the income elasticity of demand, and/or the cross-
price elasticity of demand to estimate or forecast the
effect of changes in market factors.

Key Terms and Concepts
Confidence interval

Critical value

Cross-price elasticity of demand

Elastic demand

Elasticity

Income elasticity of demand

Inelastic demand

Perfectly elastic demand

Perfectly inelastic demand

Price elasticity of demand

P-value

Regression analysis

R2 statistic

Significance level

t-statistic

Unit-elastic demand

Questions and Problems
All exercises are available on MyEconLab; solutions to even-numbered Questions and Problems appear in the back of
this book.

3.1 Regression: Estimating Demand
Learning Objective 3.1 Explain the basics of
regression analysis.

1.1 In the context of regression analysis, explain the
meaning of the terms dependent variable, indepen-
dent variable, explanatory variable, univariate equa-
tion, and multivariate equation.

1.2 Why does regression analysis presume the pres-
ence of a random error term?

1.3 Explain why minimizing the sum of the squared
residuals is a reasonable objective for regression
analysis.

3.2 Interpreting the Results of Regression
Analysis
Learning Objective 3.2 Interpret the results
from a regression.

2.1 Your marketing research department provides the
following estimated demand function for your

product: Qd = 500.6 – 11.4P + 0.5INCOME,
where P is the price of your product and
INCOME is average income.
a. Is your product a normal good or an inferior

good? Explain your answer.
b. The standard error for the price coefficient

is 2.0. What is its t-statistic? What can you
conclude about the coefficient’s statistical
significance?

c. The standard error for the income coeffi-
cient is 0.3. What is its t-statistic? What can
you conclude about the coefficient’s statisti-
cal significance?

2.2 What does the R2 statistic measure? Why is it
important?

2.3 The estimated coefficient for a variable in a
regression is 3.5, with a P-value of 0.12.
Given these two values, what conclusions
can you make about the estimated coefficient?

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3.3 Limitations of Regression Analysis
Learning Objective 3.3 Describe the limita-
tions of regression analysis and how they
affect its use by managers.

3.1 You are a manager at a company similar to KB
Home, one of the largest home builders in the
United States. You hired a consulting firm to
estimate the demand for your homes. The con-
sultants’ report used regression analysis to esti-
mate the demand. They assumed that the
demand for your homes depended on the
mortgage interest rate and disposable income.
The R2 of the regression they report is 0.24
(24 percent). What suggestions do you have for
the consultants?

3.2 Your research analyst informs you that “I always
estimate log-linear regressions.” Do you think
the analyst’s procedure is correct? What would
you say to the analyst?

3.3 You are an executive manager for HatsforAll, a
major producer of hats. You are studying a pre-
liminary report submitted by a research firm
you hired. The report includes a regression that
estimates the demand for your hats. The re-
search firm used 20 years of data on sales of
your hats and included two independent vari-
ables: the annual average price of your hats and
the annual average winter temperature in your
marketing areas. (The theory behind the tem-
perature variable is that consumers are more
likely to buy hats when the temperature is
colder.) The estimated coefficient for the price
variable is −5.8, with a standard error of 0.8,
and the estimated coefficient for the tempera-
ture variable is −20.8, with a standard error of
15.6. Based on the results of survey cards in-
cluded with the hats, you are confident that
higher-income people buy more hats. You are
writing a memo to the research firm regarding
the report. What additional information will
you request from the research firm, and what
changes will you recommend it make?

3.4 Elasticity
Learning Objective 3.4 Discuss different
elasticity measures and their use.

4.1 The short-run price elasticity of demand for oil
is 0.3. If new discoveries of oil increase the quan-
tity of oil by 6 percent, what will be the resulting
change in the price of oil?

4.2 Complete the following table.

Elasticity

Percentage
Change in

Price

Percentage
Change in
Quantity

Demanded

a. __ 8 percent 12 percent
b. 1.4 6 percent _____
c. 0.6 6 percent _____
d. 1.2 _____ 6 percent
e. 0.4 _____ 6 percent

4.3 The slope of a linear demand curve is −$2 per unit.
a. What is the price elasticity of demand when

the price is $300 and the quantity is 100 units?
b. What is the price elasticity of demand when

the price is $250 and the quantity is 125 units?
c. What is the price elasticity of demand when

the price is $100 and the quantity is 200 units?
d. As the price falls (causing a downward

movement along the demand curve), how
does the price elasticity of demand change?

4.4 Your marketing research department estimates
that the demand function for your product is
equal to Qd = 2,000 – 20P. What is the price
elasticity of demand when P = $60?

4.5 Your marketing research department estimates
that the demand function for your product is
equal to Qd = 2,000 – 20P. What is the price
elasticity of demand when P = $40?

4.6 Your marketing research department estimates
that the demand function for your product is
equal to ln Qd = 7.5 – 2.0ln P. What is the price
elasticity of demand when P = $60?

4.7 As a brand manager for Honey Bunches of Oats
cereal, you propose lowering the price by
4 percent. What will you tell your supervisor
about what you expect will be the impact on
sales in the short run and in the long run?
Explain your answer.

4.8 You own a small business and want to increase
the total revenue you collect from sales of your
product.
a. If the demand for your product is inelastic,

what can you do to increase total revenue?
b. If the demand for your product is elastic,

what can you do to increase total revenue?
c. If the demand for your product is unit elas-

tic, what can you do to increase total
revenue?

Questions and Problems  125

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126  CHAPTER 3 Measuring and Using Demand

4.9 You are a literary agent for an author who writes
very popular mystery novels. As the agent, you
receive 0.5 percent of the total revenue from
sales of the books. You are currently in negotia-
tions with Amazon about the price Amazon will
charge for your author’s e-books. You believe
that your author’s books are unique—no one
else writes similar stories. What implication
does this belief have for your estimate of the
price elasticity of demand for your author’s
books and for your negotiations with Amazon?

4.10 As a manager for the fresh chicken division of a
firm like Tyson Foods, Inc., you know that the
price elasticity of the total market demand for
broiler chickens is 0.5. When one of your assis-
tants suggests raising the price of your chicken by
10 percent, asserting that such a move would in-
crease revenue, how do you respond, and why?

4.11 Only the price elasticity of demand uses the
absolute value. Why don’t the other elasticities
(income elasticity of demand and cross-price
elasticity of demand) also use the absolute value?

4.12 Economists estimate that the income elasticity of
demand for clothing and footwear is 0.96. As in-
comes grow, what happens to the fraction of in-
come spent on clothing and footwear? Explain
your answer.

4.13 Say that as a manager at a company supplying
processed chicken, you are aware that a rise in
the cost of feeding steers is predicted to lead to a
15 percent rise in the price of beef. Your analysts
have estimated the cross-price elasticity between
the demand for chicken and the price of beef is
0.12. You and a customer are negotiating the
price at which you will sell them chicken for the
next year. What do you predict will be the im-
pact on the demand for chicken from the rise in
the price of beef, and how does this estimate af-
fect your negotiating position?

3.5 Managerial Application: Regression
Analysis and Elasticity
Learning Objective 3.5 Use regression
analysis and the different elasticity measures
to make better managerial decisions.

5.1 You are managing a division of a large company.
The marketing department submits a report to
you about the demand for the product you man-
age. The report includes the following estimated
demand function:

Qd = 2,910.0 – 11.3P + 0.050INCOME – 3.0Pother
(100.4) (3.2) (0.012) (1.0)

where P is the price of your product, INCOME is
average income, Pother is the price of a related
product, and the numbers in parentheses are the
standard errors of the estimated coefficients di-
rectly above them. The R2 statistic for the regres-
sion is 0.84 (84 percent).
a. What are your general comments about the

regression, such as its fit and the significance
of the coefficients? As a manager, would you
use this estimated demand function to help
you make decisions? Explain your answer.

b. Is the product a normal good? Explain your
answer.

c. Is the related product a complement or a
substitute for your product? Explain your
answer.

d. The current price of your product is $200,
average income is $50,000, and the price of
the related product is $300. What is the
quantity demanded of your product?

e. Based on the prices and income in part d,
what is the price elasticity of demand for
your product? Round your answer to one
decimal point.

f. If you raise the price of your product, what do
you predict will happen to the total revenue?

5.2 Using disposable personal income (people’s in-
come after paying taxes) as their measure of in-
come, General Motors’ economists estimate that
the income elasticity of demand for its cars is
1.9. The economists forecast that disposable per-
sonal income will grow 3.8 percent next year.
What will be the effect on the demand for
General Motors’ cars?

5.3 Your marketing research department estimates
that the log-linear demand function for your prod-
uct is ln Qd = 9.3 – 1.6ln P. The standard error
of the coefficient for ln P is 0.3, and the 95 percent
confidence interval runs from – 2.2 to – 1.0.
a. At a price of $50, what is the predicted price

elasticity of demand? Calculate the 95 percent
confidence interval for the elasticity using
the 95 percent confidence interval for the
estimated coefficient.

b. At a price of $30, what is the predicted price
elasticity of demand? Calculate the 95 percent
confidence interval for the elasticity using
the 95 percent confidence interval for the
estimated coefficient.

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5.4 Say that you work for U.S. Steel Corporation.
Energy accounts for a significant fraction of U.S.
Steel’s costs. One of its sources of energy is natu-
ral gas. Because of new methods of production,
such as hydraulic fracking, the quantity of natu-
ral gas is increasing. Suppose that forecasters
predict the quantity of natural gas will increase
by 10 percent and you know the price elasticity
of demand for natural gas is 0.4. U.S. Steel will
be very interested in how much the price of nat-
ural gas will change. What is your prediction for
the change in the price of natural gas?

5.5 You are a midlevel manager for a seafood restau-
rant. You and your supervisor discuss new regu-
lations that decrease the quantity of cod caught on
Georges Bank by 55 percent. Your restaurant fea-
tures Georges Bank cod, so your supervisor asks
you for a quick estimate of the impact of the new
regulations on its price. You know that the price
elasticity of demand for Georges Bank cod is 2.0.
a. Will the new regulations shift the demand

curve for cod? Will they shift the supply
curve? Explain your answers.

b. What will you report to your supervisor?
What managerial suggestions will you make?

5.6 The table below has data for the price of pizzas
and the quantity demanded at each price.
a. Use these data to estimate the demand curve

for pizza. You want to report and discuss the
estimated coefficients. Are they what you
expected? How well does your estimated re-
gression fit the data? Provide a figure if you
think it would be useful.

5.7 The St. Louis Cardinals’ website has data on play-
ers’ batting averages, and the Deadspin website
has data on the players’ salaries. (For example,
the 2015 batting salaries are at http://deadspin
.com/nl-central-chicago-cubs-jon-lester-20-000-
000-edwin-ja-1695058450.) Excluding pitchers,
presumably a higher batting average leads to a
higher salary.
a. Using regression, determine whether this

hypothesis is correct for players on the
opening day payroll for the St. Louis
Cardinals in 2015. Explain your regression
results.

b. It may be that a player’s salary depends on
his batting average and the number of his
home runs. Using regression, determine
whether this hypothesis is correct for the
players on the opening day payroll for the
St. Louis Cardinals in 2015. Explain your re-
gression results.

b. Your manager knows that the elasticity of
demand can help you make good decisions.
So once you have your demand curve, cal-
culate the elasticity at a price of $10, $15,
$20, $25, and $30. Carefully describe how you
calculated the elasticity. How does the elastic-
ity change along the demand curve? Using
the estimated demand curve, over what price
range is the demand elastic? At what price is
the demand unit elastic? Over what price
range is the demand inelastic?

Quantity
(pizzas per evening)

Price
(dollars)

Quantity
(pizzas per
evening)

Price
(dollars)

Quantity
(pizzas per
evening)

Price
(dollars)

69 $30 92 $18 141 $12

42 29 125 17 141 12

66 28 140 16 163 11

57 28 106 16 154 11

78 27 115 15 141 11

72 25 104 15 151 10

81 24 148 14 151 10

83 23 143 14 147 10

70 22 124 14 135 9

101 21 138 13 160 9

93 20 129 13 163 8

100 19 131 13 163 8

107 18 138 12 172 7

Accompanies problem 5.6.

Questions and Problems  127

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128  CHAPTER 3 Measuring and Using Demand

3.1 Bret’s Accounting & Tax Services is a small but
locally well-known accounting firm in Sioux
City, IA, that completes taxes for individuals.
Every year firms like Bret’s decide how much
they will charge to complete and file an individ-
ual tax return. This price determines how many
tax returns firms complete each year.
Suppose that you are an office manager for a
firm like Bret’s Accounting & Tax Services and
you are trying to determine what your firm
should charge next year for tax returns. Use the
data provided to complete the following:
a. Graph the data using a scatter plot. Using the

Insert Trendline function in Excel, determine
whether you should use linear or log-linear
regression. (Place the graph beneath the data;
be sure to label both axes.)

b. Using Excel’s Regression Analysis function, run
a regression, and answer the following ques-
tions about your output. (Place your regression
results beneath the graph from part a.)

c. What is your estimated demand function?
(Round the estimated coefficients to two
decimal places.)

d. What is the R2? (Report this as a percentage;
round to two decimal places.)

e. Based on the R2, do you think this regression
can be used for analysis?

f. How many returns do you expect to be com-
pleted if the firm charges $85 per return?

g. What is the elasticity at this point on the
demand curve?

h. At this price, are you on the elastic, inelastic, or
unit-elastic portion of your demand curve?

i. Do you recommend an increase, a decrease, or
no change in the price with this information?

3.2 Hawaiian Shaved Ice, in Newton Grove, NC,
sells shaved ice and snow cone equipment and
supplies for individual and commercial use.
Suppose that you purchased a commercial-grade
machine and supplies from a company similar to
Hawaiian Shaved Ice to open a shaved ice stand
on a beach busy with tourists. Because this is a
new business, you’ve tried a number of prices
and run a few specials to try to attract customers.
As such, you have 20 days’ worth of data to ana-
lyze and help you set a more permanent price.

a. Graph the data provided using a scatter plot.
Using the Insert Trendline function in Excel,
determine whether you should use linear or
log-linear regression. (Place the graph
beneath the data; be sure to label both axes.)

b. Using Excel’s Regression Analysis function, run
a regression, and answer the following ques-
tions about your output. (Place your regression
results beneath the graph from part a.)

c. What is your estimated demand function?
d. Discuss the fit and significance of the

regression.

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3.3 Ben and Jerry’s is a popular brand of ice cream
based in South Burlington, VT. The company is
known for its delicious and cleverly named fla-
vors and its commitment to social responsibility.
Suppose that the marketing department for a firm
like Ben and Jerry’s estimates monthly demand
for a pint of ice cream to be Q = 1000 – 150P.
a. Using the table provided and Excel func-

tions, calculate quantity demanded for each
of the prices given.

b. Using the prices provided and quantities
demanded that you calculated in part a, cal-
culate the elasticity of demand for each of
the prices in the table.

c. Comment on how elasticity changes as you
move along the demand curve.

d. Are there prices between $3 and $6 that you
are certain the company should not charge
based on the elasticities you observe? Why
or why not?

e. If the goal of this firm is to maximize reve-
nue, what price do you recommend it charge
for a pint of ice cream?

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Decision-Making Using Regression

Introduction
Upper-level managers frequently make important long-
run strategic decisions about acquisitions, mergers, plant
or store locations, pricing, financing, and marketing.
Indeed, a major focus of this book is to explain how man-
agers can use economic principles as a guide to making
these types of decisions. But even the best guidance can
fail without adequate information and data analysis.

Company analysts often use regression analysis to
help them provide quantitative information to manage-
rial decision makers. In this chapter, you learned how re-
gression analysis can help managers estimate demand
functions. But regression can be used to help managers
answer other questions, such as these: How many more
units of a product will we sell if our store stays open an
extra hour each day? Is San Diego a good location to open
a new store? How will consumers react if we change the
packaging of our product? In this case study, we explore
how regression analysis can help provide invaluable in-
formation about another important managerial issue,
whether to remodel the company’s stores and/or change
how the company prices its products.

Regression Example
Regression can help managers make the decisions faced
by companies that are debating whether to remodel their
stores and/or their operations. Companies such as restau-
rant chains continually struggle to retain their market
share by remaining fresh and relevant for consumers.
Most restaurant chains undertake constant innovation,
moving specials on and off their menus as well as tweak-
ing and refining their more permanent offerings. Occa-
sionally, however, upper-level managers decide that some
of their restaurants need renovation. Take, for example,
Olive Garden, a division of Darden with more than 800
restaurant locations. In 2013, the new president of Olive
Garden, Dave George, announced that Olive Garden
would remodel and modernize its interiors.

Suppose that you work in the research department
for a similar restaurant chain. Your chain has a new presi-
dent, and your president also is considering a new style
of remodeling for your restaurants. Remodeling is expen-
sive, so the new president asks your research team to
determine if the expense is justified by the projected
increased in the chain’s profit.

To obtain the information needed to make this type
of decision, a firm often remodels a few stores and then

130

CASE STUDY

1 This situation is similar to what Darden’s analysts faced in
2013 because Olive Garden had started remodeling its stores’ ex-
teriors and some of the interiors to present a different view of
Italy. That approach, however, was not what the incoming presi-
dent, Mr. George, envisioned. His goal was modernization, not
changing the geographic region the stores presented.

uses regression analysis to compare the profitability of the
remodeled stores to that of stores that are not remodeled.
Suppose, however, that your chain faces a more compli-
cated situation: Under the previous president, the chain
had already remodeled some locations but in a way that
differs from your new president’s vision.1 So you have
two types of restaurants—already remodeled and not
previously remodeled. The regression analysis needs to
consider this factor.

To use regression, your chain needs to remodel sev-
eral restaurants according to the new president’s vision.
Which restaurants are remodeled is unimportant because
your regression should be able to predict the profitability
regardless of location. After the remodeling, your group
must collect data over several months to measure the
profitability of all your restaurants. Ideally, you would
collect the economic profits of the restaurants. In practice,
however, their economic profit is impossible to measure,
so you will need to use their accounting profits as a proxy
for their economic profits. Your research group will use
these data as the dependent variable in the regression.

Your team of analysts needs to determine how the
new remodeling scheme affects profitability. But other
factors also affect profitability. A restaurant’s profit equals
its total revenue minus its total cost, so you and the other
analysts need to determine what variables affect total rev-
enue and total cost:

• Total revenue. The higher the demand for meals at
your restaurants, the greater the total revenue. So the
regression should include independent variables that
affect the demand for dining at your restaurants. For
example, your group might decide to include two in-
dependent variables that affect demand and thereby
total revenue: (1) the population of the county or lo-
cality in which the restaurant is located and (2) in-
come in that county or locality. When these variables
are included in the regression, the estimated coeffi-
cients for both these variables are expected to be pos-
itive—higher population and higher income both in-
crease demand and thereby increase the restaurant’s
total revenue and raise its profit.

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SUMMARY  131

• Total cost. The higher the total cost, the lower the
profit. So your team should include independent
variables in the regression that affect a restaurant’s
cost. For example, your group might settle upon two
variables: (1) the rent paid for the restaurant, which
will vary among locations, and (2) the legal mini-
mum wage employees receive, which will also vary
among locations. When these variables are included
in the regression, the estimated coefficients for both
of them are expected to be negative—a higher rent
and a higher minimum wage both increase the
restaurant’s cost and thereby reduce its profit.

In addition to the factors that affect total revenue
and total cost, the regression needs to take account of
whether the restaurant was remodeled according to the
past president’s scheme, remodeled according to the new
president’s ideas, or not remodeled at all. To do so, your
team needs to include indicator variables (colloquially
called “dummy variables”) as additional independent
variables. Indicator variables equal 1 when a condition is
met and equal 0 otherwise. For example, one indicator
variable should equal 1 if the restaurant had previously
been remodeled and 0 if it had not been remodeled. Call
this variable OLDREMODEL. For the purposes of deter-
mining the profitability of the new style of remodeling,
the crucial indicator variable measures whether the loca-
tion has been remodeled according to the new scheme.
This variable equals 1 for restaurants that are newly
remodeled and 0 for the other restaurants. Call this vari-
able NEWREMODEL. The estimated coefficient of each
indicator variable measures the effect of whatever condi-
tion is being met.2 That means that the coefficient for the
variable NEWREMODEL is key because when the variable
equals 1, the restaurant has been newly remodeled along
the lines suggested by the new president. The change in
profit for a restaurant going from no remodeling at all to
the new remodeling equals the estimated coefficient of
NEWREMODEL—call it gn—multiplied by the value of the

variable when the location is newly remodeled, which is 1,
or gn * 1 = gn.3

There are other factors you and your group could in-
clude that affect the total revenue and total cost, but let’s
limit the discussion to what we have discussed. Using
these variables, to predict the profitability of a restaurant
in your chain, your team would estimate the regression as

PROFIT = a + 1b * POPULATION2 + 1c * INCOME2
– 1d * RENT2 – 1e * MINIMUMWAGE2
+ 1 f * OLDREMODEL2+1g * NEWREMODEL2

in which a, b, c, d, e, f, and g are the coefficients the regres-
sion will estimate.

Once your team has estimated the regression, you
can use what you have learned in Chapter 3 to judge the
adequacy of the regression: Are the estimated coefficients
statistically different from zero? Is the fit of the regression
high? Or do you and your group need to either add or re-
move some variables? Once you are satisfied with the re-
gression, you can use it to determine the profitability of
the proposed new remodeling. In particular, the estimated
gn coefficient measures the change in profit from the new
remodeling. If this estimated coefficient is positive and
significantly different from zero, you can present it to
your new president as an estimate of the profit from re-
modeling a previously unremodeled store according to
the new style and allow the president to use it when de-
ciding whether to proceed with the new remodeling.

Your Decisions
Regression analysis can be used in any industry, not just
the restaurant industry. Take, for example, the retail
industry. In November 2011, Ron Johnson was hired to be
the new CEO of JCPenney. Less than two months later,
Mr. Johnson announced the following sweeping changes:

1. JCPenney’s pricing had relied on heavy discounting
and extensive use of coupons; Mr. Johnson immedi-
ately changed the pricing policy to adopt “full-but-
fair prices” with no discounts or coupons.

2. JCPenney had offered a large selection of middle-of-
the-road store brands; Mr. Johnson discontinued the
store brands in favor of selling more “trendy,”
high-fashion brands.

2 For technical reasons, when a set of conditions taken together
equals the entire set of observations, it is not possible to use an
indicator variable for each type of condition; one type must not
have an indicator variable. For example, in the analysis discussed
above, you cannot use an indicator variable that equals 1 if the
location had been previously remodeled, another indicator vari-
able that equals 1 if the location is newly remodeled, and yet a
third indicator variable that equals 1 if the location has not been
remodeled. You cannot use all three of these indicator variables
because taken together these three conditions equal the entire set
of observations. Consequently, in the regression discussed in the
example, there is no indicator variable for the stores that have not
been remodeled.

3 More specifically, the NEWREMODEL indicator variable’s coeffi-
cient, gn, measures the profit from the new remodeling relative to
whichever condition has not been given an indicator variable. In
the example at hand, gn measures the restaurant’s change in profit
from being newly remodeled compared to not being remodeled
at all.

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132  CHAPTER 3 Measuring and Using Demand

3. JCPenney’s customer base was generally older and
middle to lower income; Mr. Johnson moved to es-
tablish smaller “stores within a store” with more
expensive merchandise to target younger, higher-
income customers.

Mr. Johnson immediately started to implement his
new policies without any testing. Unfortunately for both
him and the company, customers rejected his changes:
JCPenney’s sales dropped about 30 percent, its profit
turned to billions of dollars of losses, and in April 2013,
the board of directors fired Mr. Johnson as CEO.

Suppose you work in the research department of a
retail department store chain that is considering three
similar changes—ending discounts, offering trendy
brands, and creating stores within the store. Your chain,
however, decides to test these ideas before rolling them
out chain-wide. So your supervisor asks you to write a
proposal that will allow your company’s executives to
determine the profitability of these possible changes. You
will use regression analysis to decide on the profitability
of the changes.

Prepare a proposal that answers the following
questions:

1. The changes can be implemented separately, all to-
gether, or in combinations of two, so how do you
want to test the three changes? Be sure to explain
why you made your decision.

2. If you want to compare the profitability of stores in
different locations, explain what variables you expect
to use. Be certain to mention variables other than
those discussed above in the restaurant example that
might affect the stores’ profitability. Carefully explain
what effect you expect from each variable you in-
clude. For each variable, do you expect that the esti-
mated coefficient will be positive or negative?
Mention the source from which you plan to obtain
the data you will use.

3. Will you use any indicator variables? If so, what will
they be?

4. Is there any feature (or features) about the specifica-
tion or functional form of the regression that needs
additional explanation?

5. After you estimate the regression, how do you plan
to decide whether the estimated regression is ade-
quate? How might the regression results be inade-
quate? What do you plan to do if the results are
inadequate?

6. Once you have an acceptable regression, explain how
you plan to use the results to determine the profit-
ability of the changes.

Sources: Steve Denning, “J.C. Penney: Was Ron Johnson Wrong?”
Forbes.com, April 9, 2013, http://www.forbes.com/sites/
stevedenning/2013/04/09/j-c-penney-was-ron-johnsons-
strategy-wrong/#32427add283c; James Surowiecki, “The
Turnaround Trap,” New Yorker, March 25, 2013.

132  CHAPTER 3 CASE STUDY Decision-Making Using Regression

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A. Regression Analysis and Elasticity  133

CHAPTER 3 APPENDIX

The Calculus of Elasticity

Many of the elasticity results discussed in this chapter, including the elasticity formulas for
linear and log-linear demand functions and the total revenue test, can be derived using calcu-
lus. Indeed, we can start by giving the definition of the price elasticity of demand 1e2 from
Equation 3.2 (Section 3.4),

e = ∞
a ∆Q

d

Qd
b

a ∆P
P

b

a precise calculus interpretation:

e = ∞
a dQ

d

Qd
b

a dP
P

b
∞ A3.1

where the discrete Δ changes are now differential d changes.

A. Price Elasticity of Demand for a Linear and a Log-Linear
Demand Function
Some algebra using the definition of the price elasticity of demand in Equation A3.1 gives
another measure of elasticity:

e = ∞

dQd

Qd

dP
P

∞ = ` a dQ
d

Qd
b * a P

dP
b ` = ` dQ

d * P
Qd * dP

` = ` dQ
d * P

dP * Qd
` = ` a dQ

d

dP
b * a P

Qd
b ` A3.2

If you use a general specification of the demand function, Qd = f1P2, then dQ
d

dP
= f′1P2,

where f′1P2 is the derivative of the demand function with respect to the price. Substituting
f′1P2 into Equation A3.2 shows that the price elasticity of demand equals

e = ` a dQ
d

dP
b * a P

Qd
b ` = ` f′1P2 * a P

Qd
b ` A3.3

Equation A3.3 has the following interpretation: At any price and for any demand function, the
price elasticity of demand equals the derivative of the demand function at that price multiplied
by the price divided by the quantity demanded at that price.

We can use Equation A3.3 to determine the equations for the price elasticity of demand
for two common demand functions, a linear demand function and a log-linear demand func-
tion. For a linear demand function—say, Qd = a – 1b * P2, where a and b are coefficients—
the derivative of the quantity with respect to the price is

dQd

dP = – b. Using Equation A3.3, for
a linear demand function the price elasticity of demand equals

e = ` b * a P
Qd

b `

133

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134  CHAPTER 3 APPENDIX The Calculus of Elasticity

which is shown as Equation 3.4 in the chapter (see Section 3.4). For a log-linear demand
function—say,

ln Qd = a – 1b * ln P2 A3.4
where ln represents the natural logarithm—the derivative of the quantity with respect to the
price is1

dQd

dP
= – b * a Q

d

P
b

Accordingly, using Equation A3.3 once again shows that, for a log-linear demand function, the
price elasticity of demand equals

e = ` a – b * a Q
d

P
b b * a P

Qd
b ` = b

precisely as stated in the chapter. In other words, for a log-linear demand function, the price
elasticity of demand is the same for all prices and equals b, the coefficient multiplying the
logarithm of the price in Equation A3.4.

B. Total Revenue Test
Calculus also helps prove the total revenue test presented in the chapter (see Section 3.4). Recall
that the total revenue test shows how the total revenue changes when the price changes; that is,
it measures dTR>dP. The total revenue test includes three assertions: Demand is elastic when e
is greater than 1, unit-elastic when e equals 1, and inelastic when e is less than one.

1. Elastic demand 1E + 12 :
• If the price rises, the total revenue decreases, which means that dTR>dP is negative.
• Conversely, if the price falls, the total revenue increases, which (again) means that

dTR>dP is negative.
2. Unit-elastic demand 1E = 12 :

• If the price rises or falls, the total revenue does not change, which means that dTR>dP is
equal to zero.

3. Inelastic demand 1E * 12 :
• If the price rises, the total revenue increases, which means that dTR>dP is positive.
• Conversely, if the price falls, the total revenue decreases, which (again) means that

dTR>dP is positive.
Total revenue equals the price of the product (P) multiplied by the quantity sold (Q), and

the quantity sold equals the quantity demanded by consumers (Qd):

TR = P * Qd

The quantity demanded is given by Qd = f1P2, so total revenue equals
TR = P * f1P2 A3.5

Taking the derivative of total revenue in Equation A3.5 with respect to the price by using
the product rule gives

dTR
dP

= 3P * f′1P24 + f1P2 A3.6

1 Taking the total derivative of ln Qd = a – 1b * ln P2 gives 11>Qd) * dQd = – b * 11>P2 * dP.
Multiplying both sides of the equality by Qd and dividing both sides by dP yields dQd>dP = – b * 1Qd>P2.

M03_BLAI8235_01_SE_C03_pp86-137.indd 134 23/08/17 9:53 AM

CHAPTER 3 APPENDIX The Calculus of Elasticity  135

In Equation A3.6, f1P2 = Qd. Using this equality and rearranging the terms in the right
side of Equation A3.6 yields

dTR
dP

= Qd + 3f′1P2 * P4 A3.7

Next, multiply the second term (the term in Equation 3.7 in the brackets) on the right side

of Equation 3.7 by 1 in the form of a Q
d

Qd
b:

dTR
dP

= 3Qd4 + c a Q
d

Qd
b * 1f′1P2 * P2 d

Finally, factor Qd out of both terms, and then rearrange the terms to give

dTR
dP

= Qd * e 314 + c a 1
Qd

b * 1f’1P2 * P2 d f = Qd * e 314+c af′1P2 * P
Qd

b d f A3.8

The term c f′1P2 * P
Qd

d is the same as the price elasticity of demand in Equation A3.3
except that there is no absolute value sign. Recall that we use the absolute value sign because
otherwise the price elasticity of demand would be negative, since the law of demand means

that f′1P2, which equals dQ
d

dP
, is negative. Consequently, the c f′1P2 * P

Qd
d term in

Equation A3.8 has the same numeric value as the price elasticity of demand but is negative, so

c f′1P2 * P
Qd

d = -e. Using this equality, we can rewrite Equation A3.8 as

dTR
dP

= Qd * 31 – e4 A3.9

Equation A3.9 shows how the total revenue changes when the price changes. In it, the

quantity demanded, Qd, is always positive, so the sign of
dTR
dP

depends on the 31 – e4 term.
Using this result, we can now prove the total revenue test:

1. Elastic demand 1E + 12 :
• If e 7 1, then 1 – e is negative, so from Equation A3.9, dTR>dP is negative.

2. Unit-elastic demand 1E = 12 :
• If e = 1, then 1 – e equals 0, so from Equation A3.9, dTR>dP is equal to zero.

3. Inelastic demand 1E * 12 :
• If e 6 1, then 1 – e is positive, so from Equation A3.9, dTR>dP is positive.

C. Income Elasticity of Demand and Cross-Price
Elasticity of Demand
It is probably no surprise that both the income and the cross-price elasticities of
demand can be defined using calculus. If the demand function is Qd = f1P, INCOME, Pj2,
where P is the price of the good, INCOME is consumers’ average income, and Pj is the
price of a substitute or complement, then the income and cross-price elasticities of
demand are

M03_BLAI8235_01_SE_C03_pp86-137.indd 135 23/08/17 9:53 AM

In both of the definitions, we take a partial derivative because the demand function is
multivariate; that is, the demand function has more than one independent variable. Even so,
as Table A3.1 shows, the meanings of the signs of the income and cross-price elasticities do
not change from what was explained in the chapter.

Table A3.1 Signs of Income Elasticity and Cross-Price Elasticity of Demand

Income elasticity of demand

• If ∂Qd>∂INCOME is positive then eINC is positive, and the product is a normal good.
• If ∂Qd>∂INCOME is negative then eINC is negative, and the product is an inferior good.
Cross-price elasticity of demand

• If ∂Qd>∂Pj is positive then eCROSS is positive, and the products are substitutes.
• If ∂Qd>∂Pj is negative then eCROSS is negative, and the products are complements.

Calculus Questions and Problems
All exercises are available on MyEconLab; solutions to even-numbered Questions and Problems appear in the back of
this book.

A3.1 The hourly demand for music downloads is given by

Qd = 500 – 100P

where Qd is the number of songs demanded per
hour and P is the price of downloading a song.
a. Suppose that P = $3. At this price, what does

the price elasticity of demand equal? What is
the total revenue?

b. At what price does e = 1? What is the total rev-
enue when the price is $2.50?

c. Explain whether your results to parts a and b
are consistent with the total revenue test.

A3.2 The weekly demand for sandwiches at a local sand-
wich shop is given by

Qd = 2,000 – 5P + 2Pj – 0.01INCOME

where Qd is the number of sandwiches demanded
per week, P is the price of a sandwich, Pj is the price
of a related product, and INCOME is the average
monthly income of consumers.

a. Suppose that P = $10, Pj = $50, and
INCOME = $5,000. What is the value of the
cross-price elasticity of demand? Is the related
product a substitute or a complement?

b. Suppose that P = $10, Pj = $50, and
INCOME = $5,000. What is the value of the
income elasticity of demand? Are sandwiches a
normal good or an inferior good?

A3.3 The hourly demand for corndogs at the local state
fair is estimated to be

Qd = 360P-2

where Qd is the number of corndogs demanded per
hour and P is the price of a corndog.
a. Using the estimated demand function for corn-

dogs, calculate the price elasticity of demand as
a function of the price of a corndog.

b. Using the demand function for corndogs, the
quantity demanded is 90 corndogs when the

136  CHAPTER 3 APPENDIX The Calculus of Elasticity

eINC =

a 0Q
d

Qd
b

a 0INCOME
INCOME

b
= a 0Q

d

0INCOME
b * a INCOME

Qd
b

eCROSS =

a 0Q
d

Qd
b

a
0Pj
Pj

b
= a 0Q

d

0Pj
b * a

Pj

Qd
b

M03_BLAI8235_01_SE_C03_pp86-137.indd 136 23/08/17 9:53 AM

price is $2 per corndog, and the quantity
demanded is 40 corndogs when the price is $3
per corndog. Does the total revenue from sell-
ing corndogs rise or fall as the number of corn-
dogs sold increases?

c. Is your answer to part b consistent with the
total revenue test? Explain.

A3.4 The monthly demand for bus rides in Miami, Flor-
ida, depends on the price of a train ride, the price of
a bus ride, and the average monthly income of rid-
ers. Some consumers might choose to ride the train
instead of the bus, while other riders might use
both forms of transportation to get to their final
destination. The demand function for bus rides is

Qd = 9,750 – 500P + 250Pj + 5INCOME

where Qd is the number of bus rides demanded per
month, P is the price of a bus ride, Pj is the price of a
train ride, and INCOME is the average monthly
income of riders.
a. Suppose that P = $1.50, Pj = $4.00, and

INCOME = $3,000. What is the monthly quan-
tity of bus rides demanded?

b. Suppose that P = $1.50, Pj = $4.00, and
INCOME = $3,000. What is the value of the
cross-price elasticity of demand? Based on your
answer, are train rides and bus rides substitutes
or complements?

c. Suppose that P = $1.50, Pj = $4.00, and
INCOME = $3,000. What is the value of the in-
come elasticity of demand? Based on your an-
swer, are train rides an inferior or a normal good?

A3.5 The monthly demand for personal pizzas depends
on the price of a personal pizza and the price of a
separate related good. The demand function for
personal pizzas is

Qd = 480 – 5P + 10Pj

where Qd is the number of personal pizzas
demanded per month, P is the price of a personal
pizza, and Pj is the price of the related good.
a. Suppose that P = $6 and Pj = $9. What does

the cross-price elasticity of demand equal?
b. Based on the answer to part a, is the related

good a substitute or a complement to pizza?

CHAPTER 3 APPENDIX The Calculus of Elasticity  137

M03_BLAI8235_01_SE_C03_pp86-137.indd 137 23/08/17 9:53 AM

138

4

Pizza Hut Managers Learn That Size Matters

In 2014, Pizza Hut had about 6,300 restaurants in the United States. Although this number is impressive, exec-
utive managers at Pizza Hut realized that they had a prob-
lem. Most of the existing locations featured both delivery
and dine-in services, so they were large restaurants with
correspondingly high costs. Potential franchisees became
unwilling to open new restaurants because their high
costs made them unprofitable. From 2001 to 2014, the
number of Pizza Hut restaurants in the United States actu-
ally decreased from 7,700 to 6,300 because franchisees
closed more restaurants than they opened.

After crunching some data, Pizza Hut’s research
department calculated that the fraction of their pizza sales

involving home delivery had fallen. Delivery is the most
popular way for consumers to buy pizza, so Pizza Hut’s
executive managers needed to boost delivery sales. They
also recognized a cost problem: Conventional Pizza Hut
restaurants were too large to make focusing primarily on
home delivery profitable. What could Pizza Hut’s manag-
ers do to increase the number of their stores, and thereby
their profit, in the face of these challenges?

This chapter explains the relationship between the
costs of inputs, such as labor and capital, and the amount
of output. At the end of the chapter, you will learn how
Pizza Hut’s executives could have evaluated these factors
in creating a plan to improve their company’s operation.

Sources: Annie Gasparro, “Pizza Hut Scales Down to Boost Delivery,” Wall Street Journal, October 2, 2012; Annie
Gasparro, “Yum Pizza Hut Pares Outlet size; Delivery Is Focus,” Marketwatch, October 3, 2012; Rick Hynum, “The
2015 Pizza Power Report,” PMQ Pizza Magazine, December 2014; A World of Yum! (2005 YUM Annual Report).

Production and Costs

Learning Objectives
After studying this chapter, you will be able to:

4.1 Explain the relationship between a firm’s inputs and its output as well as calculate the
marginal product of an input.

4.2 Use the cost-minimization rule to choose the combination of inputs that produces a
given quantity of output at the lowest cost.

4.3 Distinguish between fixed cost and variable cost and calculate average total cost,
average variable cost, average fixed cost, and marginal cost.

4.4 Derive the long-run average cost curve and explain its shape.
4.5 Apply production and cost theory to make better managerial decisions.

C
H

A
P

T
E

R

Introduction
Successful businesses must respond to consumers’ demands for goods and services.
The amount of a good or service a firm produces depends on the demand for that good
or service and the opportunity costs of producing it.1 The costs depend on four factors:

1. The quantity of inputs, such as labor and capital, utilized
2. The cost of each input

1 For the sake of brevity, we usually drop the modifier opportunity in front of the word cost, but keep in
mind that as a manager you must always be concerned with opportunity cost rather than accounting cost.

M04_BLAI8235_01_SE_C04_pp138-185.indd 138 23/08/17 10:07 AM

4.1 Production  139

3. The production technology utilized
4. The managers’ efforts to minimize the cost of production

The chapter begins with an analysis of the firm’s production function, which
is the relationship between the firm’s inputs and its output. For simplicity, the
discussion assumes that managers know their firm’s production function. Unfortu-
nately, managers often begin with only a vague idea. Discovering the best way to
organize inputs to produce a good or service can be a challenging trial-and-
error process. This chapter can help you develop a strategy to work through this
trial-and-error process and make the managerial decisions that lead to the most
efficient production.

Next, you will learn about costs by deriving and illustrating a firm’s cost curves.
Because the firm incurs costs for its use of inputs, the cost curves are closely related
to the firm’s production technology and the productivity of the inputs. The cost
curves are the foundation for the next several chapters, which provide valuable
insights into managers’ profit-maximizing decisions about the amount of output to
produce and the price to charge.

To help you understand the important concepts of production and costs,
Chapter 4 includes five sections:

• Section 4.1 explores the production function, the difference between the short run and
the long run, and the definitions of the marginal product of labor and capital.

• Section 4.2 describes how to determine the combination of inputs that produces the
desired quantity of output at the minimum cost.

• Section 4.3 explains how costs change in the short run when production changes.
• Section 4.4 examines how costs change in the long run when production changes.
• Section 4.5 discusses how you can apply production and cost theory to make better man-

agerial decisions.

4.1 Production
Learning Objective 4.1 Explain the relationship between a firm’s inputs and
its output as well as calculate the marginal product of an input.

Suppose that you are a general manager of an Italian restaurant, like Olive Garden,
and you report to a district manager. One of your goals is to produce your output
(Italian dinners) as efficiently as possible, which generally means producing the
dinners at the lowest possible cost. If you minimize the cost of producing the out-
put, you will be well on your way to maximizing the profit of your restaurant. To
make the best decisions about costs, you must understand some basic elements of
production.

Production Function
When a firm produces a good or service, it combines inputs, called factors of produc-
tion, according to a precise procedure or “recipe,” called a production function. At
your Italian restaurant, inputs consist of

• The workers you hire, such as chefs and servers
• Raw materials, such as lettuce and chicken
• Capital equipment, such as grills and ovens
• Intermediate goods, such as olive oil and flour

M04_BLAI8235_01_SE_C04_pp138-185.indd 139 15/09/17 2:48 PM

140  CHAPTER 4 Production and Costs

The production function is the relationship between different amounts of a
firm’s inputs and the maximum quantity of output it can produce with those inputs.
Mathematically, the production function is written as Q = f1X1, X2, c, Xn2, where

• Q is the quantity of output
• Xs are the inputs
• f is the function, or “recipe,” that converts the inputs into output

The function, f, incorporates the current state of technology. Changes in technol-
ogy change the production function and generally enable firms to produce more
output using the same or even smaller quantities of inputs.

A production function that uses many inputs can be complex. For simplicity,
let’s focus on a simple firm that uses only two inputs, labor and capital equipment.
This firm’s two-input production function can be written as Q = f1L, K2, where Q is
the quantity of output, f is the production function, L is the quantity of the labor
input, and K is the quantity of the capital input. This simplified two-input produc-
tion function will provide lessons and insights that you can apply to real-world pro-
duction decisions involving many more than two inputs.

Short Run and Long Run
Within a given period of time, it is more difficult for a firm to obtain and use addi-
tional units of some inputs than others. For instance, at your Italian restaurant, it
would be very expensive, if not impossible, to increase the size of the dining area by
20 percent in the space of a week. During that same week, however, you could easily
hire an additional server. On the other hand, if you had a year to make changes, it
would be easy to both increase the size of your dining area and hire another server.
Economists define two periods of time that reflect these differences: the short run
and the long run. The short run is the period of time during which at least one input
is fixed, so that a firm cannot vary the quantity of that input. Using the two-input
production function with capital and labor as the only inputs, in the short run capital
is the fixed input and labor is the variable input. For a restaurant, the size of the dining
room (capital) is a fixed input in the short run. The long run is a period of time long
enough that no input is fixed, allowing a firm to vary the quantity of all the inputs it
uses. Because managers can change the amounts used, in the long run both capital
(expansion of the dining area) and labor (the addition of a server) are variable
inputs.

The long run varies widely among firms. It might take a firm like Darden, the
parent company of Olive Garden, two years to obtain the permits and construct a
new Olive Garden restaurant. By comparison, it might take as long as six years for a
computer chip–producing company like Intel to obtain permits, construct a new
manufacturing facility, and then certify it.

Long-run decisions are often more difficult or more costly to reverse—the cost of
building an unnecessary factory dwarfs the cost of hiring an unnecessary worker. So
decisions about the long run are more strategic in nature. Generally, upper-level
management or executives make long-run decisions. Short-run decisions are often
more tactical, however, and can be made by midlevel managers.

With more than two inputs, the complexity of the production function increases
because it takes different amounts of time for different inputs to become variable.
For example, at your restaurant, it is possible to change the number of servers within
a week, but it could take two months to hire a new skilled chef, three months to add
a new oven, and two years to remodel the entire restaurant. As this example shows,

Production function The
relationship between
different amounts of a
firm’s inputs and the
maximum quantity of
output it can produce with
those inputs.

Short run The period of
time during which at least
one input is fixed, so that a
firm cannot vary the
quantity of that input.

Long run A period of time
long enough that no input
is fixed, allowing a firm to
vary the quantity of all the
inputs it uses.

M04_BLAI8235_01_SE_C04_pp138-185.indd 140 23/08/17 10:07 AM

4.1 Production  141

you can make more profound changes as time passes, which is reflected in differ-
ences in the short-run production function and the long-run production function.

Short-Run Production Function
The previous section pointed out that firms can vary the quantity of labor (number
of servers) more quickly than capital (expansion of the dining area), which for the
short run makes capital a fixed input and labor a variable input. So the short-run pro-
duction function, when there is at least one fixed input, is

Q = f1L, K2
where the bar over K signifies that the quantity of capital is fixed.

You can get a feeling for this short-run production function for your Italian
restaurant by examining the hypothetical data and graph in Figure 4.1. Figure 4.1(a)
assumes that the restaurant’s capital—the size of the dining room, number of ovens,
and number of booths—is fixed and equal to 5 units of capital. The curve labeled PF
in Figure 4.1(b) is the short-run production function for 5 units of capital, plotted
from the data in Figure 4.1(a). The PF curve illustrates the relationship between the
quantity of labor (the number of workers) on the horizontal axis and quantity of out-
put (the number of dinners per day) on the vertical axis.

To derive the data and then the graph in Figure 4.1, you need to determine the
relationship between the number of dinners produced and the number of employ-
ees. Conceptually, you could experiment by starting with one employee per shift and
then adding extra workers, while keeping track of the quantity of dinners served.
The production data in Figure 4.1 represent these hypothetical findings. As you can

Output (dinners per day)

Labor (workers)

350

50

100

121110987654321

150

200

250

300

0

PF

Capital, K
(units of
capital)

Labor, L
(workers)

Output, Q
(dinners per

day)

5 0 0

5 1 10

5 2 30

5 3 60

5 4 110

5 5 170

5 6 220

5 7 260

5 8 290

5 9 310

5 10 320

5 11 310

Figure 4.1 The Short-Run Production Function

The data represent the short-run production
function for 5 units of capital.

The figure graphs the data from part a and shows the short-
run production function, PF.

(a) Production Data (b) Short-Run Production Function

M04_BLAI8235_01_SE_C04_pp138-185.indd 141 11/09/17 11:29 AM

142  CHAPTER 4 Production and Costs

see from the data and curve in Figure 4.1, the output begins to decrease with the 11th
worker. No manager would add more workers when doing so decreases output, so
there is no need to include data beyond 11 workers.

For small quantities of labor, output responds dramatically to changes in labor.
Why? Suppose you start with a single worker. This worker would need to seat the
customers, take the orders, cook the food, serve the food, collect the payment, and
bus the tables. As you add more workers, they waste less time scurrying around from
one place to another, allowing them to be more efficient and produce more output
(dinners) and thereby serve more customers. In addition, greater specialization of
labor is possible. Some workers specialize in cooking, others in serving the custom-
ers, and still others in busing the tables. Specialization also increases the output (the
dinners). Both the more efficient use of labor and the increase in specialization mean
that as the managers hire more labor, each additional worker increases the firm’s out-
put by more than the previous worker. As more labor is used, however, eventually
output increases more slowly in response to increases in the number of workers
because the opportunity for additional gains diminishes. Finally, as the managers
add more and more workers, the congestion of workers becomes so severe that the
restaurant reaches its maximum output. In Figure 4.1, the maximum output is 320
dinners per day. Any further additions to the workforce—say, going from 10 to 11
workers per shift—actually decrease the quantity of output.

Marginal Product
The production function highlights a crucial decision for managers: determining the
optimal quantity of an input to employ. This decision depends on the input’s pro-
ductivity and its cost compared to other inputs’ productivities and costs. The rele-
vant measure of productivity is the input’s marginal product, which is the change in
total output that results from changing the input by one unit while keeping the other
inputs constant.

Using this definition, the marginal product of labor (MPL) is the change in total
output that results from changing labor by one unit while keeping the other inputs
constant. It equals

MPL =
1Change in output2
1Change in labor2 =

1∆Q2
1∆L2

In this equation, the delta symbol (Δ) means “change in,” Q is output, and L is
labor.

Figure 4.2(a) shows the marginal product of labor from the same data
included in Figure 4.1(a). To calculate the marginal product of labor, divide the
change in the number of dinners by the change in the number of workers. For
example, the marginal product of labor of increasing the number of workers
from 6 to 7 equals

1260 dinners – 220 dinners2
17 workers – 6 workers2 = 40 dinners per worker

which means that increasing the number of workers from 6 to 7 enables your Italian
restaurant to produce an additional 40 dinners per day. In Figure 4.2(a), this mar-
ginal product is located between 6 and 7 workers. The remaining results in the third
column of Figure 4.2(a) are calculated in the same way.

Figure 4.2(b) shows the behavior of the MPL curve: As the number of workers
increases, the marginal product of labor starts small, rises, hits a maximum, and then
decreases. This is a graphic example of the economics of the situation. When only a

Marginal product The
change in total output that
results from changing an
input by one unit while
keeping the other inputs
constant.

Marginal product of labor
The change in total output
that results from changing
labor by one unit while
keeping the other inputs
constant.

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4.1 Production  143

Labor, L
(workers)

Output, Q
(dinners per day)

Marginal Product
of Labor

(dinners per
worker)

MPL

Marginal product (dinners per worker)

Labor (workers)

70

0

10

20

121110987654321

30

40

50

60

210

0 0
10

20

30

50

60

50

40

30

20

10

– 10

1 10

2 30

3 60

4 110

5 170

6 220

7 260

8 290

9 310

10 320

11 310

Figure 4.2 The Marginal Product of Labor

The marginal product of labor equals
1Change in Q2
(Change in L) .

The third column shows the marginal product of
labor obtained by dividing the change in output
(column 2) by the change in labor (column 1).
For example, the marginal product of labor of
increasing employment from 4 to 5 workers equals
1170 dinners – 110 dinners2
15 workers – 4 workers2 = 60 dinners per worker.

The figure plots the marginal product of labor (MPL) for
each worker using the data from part a.

(a) Marginal Product of Labor Data (b) Marginal Product of Labor Curve

few workers are employed, hiring another worker results in increased specialization
and increases the efficiency of all of the workers, leading to a large increase in out-
put—that is, a large MPL. Eventually, the marginal product of labor hits its maxi-
mum, which occurs at 4½ workers in Figure 4.2(b). Then as managers hire more
workers, congestion sets in, and there is a smaller increase in output from hiring
another worker. Of course, the number of workers and the numerical value of the
maximum marginal product of labor differ from company to company, but the gen-
eral appearance of the curve is similar to the one shown in Figure 4.2(b).

Figure 4.3 shows the relationship between the production function and the mar-
ginal product of labor curve by illustrating both in the same diagram. As labor
increases from 1 worker to 4½ workers, the production function rises and becomes
steeper—each additional worker increases output by more than the previous
worker—so the marginal product of labor increases in this range. The range over
which the marginal product of labor increases is defined as the range with increasing
marginal returns to labor.

For the range of workers between 4½ and 10, the production function still rises,
but it becomes less steep—each additional worker increases output by less than the
previous worker—so the marginal product of labor decreases in this range. The
range over which the marginal product of labor decreases but remains positive is
defined as the range with decreasing marginal returns to labor.

Increasing marginal
returns to labor The range
of labor input over which
the marginal product of
labor increases.

Decreasing marginal
returns to labor The range
of labor input over which
the marginal product of
labor decreases but
remains positive.

M04_BLAI8235_01_SE_C04_pp138-185.indd 143 23/08/17 10:07 AM

144  CHAPTER 4 Production and Costs

Finally, for all workers beyond 10, the production function falls—each addi-
tional worker decreases output. Consequently, the marginal product of labor is nega-
tive in this range. The range over which the marginal product of labor is negative is
defined as the range with negative marginal returns to labor.

The concept of marginal product applies to other inputs besides labor. Each
input has its own marginal product, equal to the change in output that results from
changing that input by one unit while keeping all the other inputs constant. For
example, in the long run, managers can change the quantity of capital, so at that
point the marginal product of capital (MPK) is equal to

MPK =
∆Q
∆K

More realistic production functions include more than two inputs, but the mar-
ginal products for all other inputs are calculated in the same way. The inputs will
have the same three ranges described above: initially increasing marginal returns
followed by decreasing marginal returns and ending with negative marginal
returns.

The marginal product for each input is important knowledge for managers
because it helps determine the cost-minimizing combination of inputs. Unfortu-
nately, as a manager, you will never know the precise production function or the
precise marginal product of your inputs. You can estimate approximate values using
records of changes in output resulting from changes in the use of an input, perhaps
by using regression analysis as explained in Chapter 3 (see Section 3.1). Alternatively,
you might use your best managerial judgment to estimate the marginal product.
Regardless of how you obtain your estimate, as you will learn in Section 4.2, know-
ing the marginal product is essential to accomplishing the goal of minimizing your
firm’s costs.

Negative marginal returns
to labor The range of labor
input over which the
marginal product of labor
is negative.

Figure 4.3 Increasing,
Decreasing, and Negative
Marginal Returns to Labor

The range over which the
marginal product of labor
increases, from 0 to
4½ workers in the figure,
has increasing marginal
returns to labor. The range
over which the marginal
product of labor decreases
but is positive, 4½ to
10 workers in the figure,
has decreasing marginal
returns to labor. The range
over which the marginal
product of labor decreases
and is negative, more than
10 workers in the figure,
has negative marginal
returns to labor.

Output and marginal product

Labor (workers)

350

50

250

100

121110987654321

150

200

250

300

0

MPL

Increasing
marginal returns

to labor

Negative
marginal
returns
to labor

Decreasing marginal
returns to labor

PF

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4.1 Production  145

The Impact of Changes in Technology
A change in technology shifts the production function. Typically, advances in tech-
nology allow the firm to produce more output from the same quantity of inputs. For
example, suppose that a new convection oven technology doubles the number of
dinners your Italian restaurant can produce at each quantity of workers. As illus-
trated in Figure 4.4(a), the technological advance shifts the production function
upward. Technological advances also generally increase the marginal product of
labor. The technological advance that doubles the number of dinners shifts the mar-
ginal product of labor curve upward, as shown in Figure 4.4(b).

Long-Run Production Function
In the long run, all inputs are variable, so managers can change the quantity of all of the
inputs. For a two-input production process, you can write the long-run production func-
tion, when all inputs are variable, as Q = f1L, K2, where both labor, L, and capital, K,
can be changed. The long-run production function is more difficult to illustrate in a
figure because even with just two inputs the figure needs to be three-dimensional to
take account of the two inputs and one output. Instead of trying to illustrate a long-run
production function, Table 4.1 presents a portion of the long-run production function
using data from the Italian restaurant example.

Output (dinners per day)

Labor (workers)

700

100

200

121110987654321

300

400

500

600

0

PF1

PF0

Marginal product (dinners per worker)

Labor (workers)

140

20

220

40

121110987654321

60

80

100

120

0

MP1
MP0

Figure 4.4 The Effects of a Technological Advance

(a) The Effect of a Technological Advance on the
Production Function

(b) The Effect of a Technological Advance on the
Marginal Product of Labor Curve

An improvement to technology shifts the production
function upward, from PF0 to PF1.

An improvement to technology shifts the marginal
product of labor curve upward, in the figure from MP0
to MP1, though in general the unit of labor with the
maximum marginal product will change.

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146  CHAPTER 4 Production and Costs

For any given amount of capital, such as the 4 units shown in Table 4.1, the mar-
ginal product of labor follows the same pattern described earlier: It rises to a maxi-
mum during a range with increasing marginal returns and then falls during a range
with decreasing marginal returns. Although there are not enough data in the table to
show its entire pattern, the marginal product of capital follows the same behavior: It
rises to a maximum during a range with increasing marginal returns and then falls
during a range with decreasing marginal returns. For example, holding employment
constant at 5 workers, the marginal product of capital when capital is increased from
4 to 5 units is

1170 dinners – 130 dinners2
15 units of capital – 4 units of capital2 = 40 dinners per unit of capital

Then the marginal product of capital when capital is increased from 5 to 6 units is

1230 dinners – 170 dinners2
16 units of capital – 5 units of capital2 = 60 dinners per unit of capital

These two marginal products of capital fall within the increasing marginal returns
range, but if you continued to calculate the marginal product of capital for larger and
larger amounts of capital, eventually it would hit a maximum and then begin to
decrease.

Using the marginal product along with the prices of the different inputs enables
you to make decisions that minimize the cost of producing your firm’s product. The
next section explains how to make these decisions.

Table 4.1 The Long-Run Production Function

These data represent the long-run production function.

Production Data

Capital,
K

(units of
capital)

Labor,
L

(workers)

Output,
Q

(dinners
per day)

Capital,
K (units of

capital)

Labor,
L

(workers)

Output,
Q

(dinners
per day)

Capital,
K

(units of
capital)

Labor,
L

(workers)

Output,
Q

(dinners
per day)

4 0 0 5 0 0 6 0 0

4 1 8 5 1 10 6 1 12

4 2 26 5 2 30 6 2 34

4 3 50 5 3 60 6 3 72

4 4 85 5 4 110 6 4 140

4 5 130 5 5 170 6 5 230

4 6 170 5 6 220 6 6 300

4 7 205 5 7 260 6 7 350

4 8 235 5 8 290 6 8 390

4 9 250 5 9 310 6 9 420

4 10 240 5 10 320 6 10 440

4 11 230 5 11 310 6 11 450

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4.2 Cost Minimization  147

4.2 Cost Minimization
Learning Objective 4.2 Use the cost-minimization rule to choose the combination
of inputs that produces a given quantity of output at the lowest cost.

When a firm uses an input, it incurs a cost. Regardless of whether you are managing
a for-profit firm, a not-for-profit organization, a government agency, or an NGO,
your goal should be to use the mix of inputs that minimizes the cost of producing
the desired quantity of the good or service. You will constantly face decisions about
the amount of each input to use when producing your product. For instance, if you
are a general manager at a restaurant, should you hire another server and let a table
busser go, or should you purchase another dish-washing machine and fire a dish-
washer? If you are a manager at a nonprofit like the American Red Cross, should
you buy another emergency response vehicle and fire five disaster workers and two
CPR trainers? As the choices faced by these managers demonstrate, all the different
types of organizations use multiple inputs. For simplicity, however, the text discus-
sion continues to use the two-input production function, Q = f1L, K2. Learning how
to minimize cost with only two inputs will help you understand the process for the
real-world case of many inputs.

As you have already learned, some inputs are fixed in the short run. You cannot
change the quantity of fixed inputs, so you must focus on minimizing the cost of the
variable inputs to optimize production and minimize the total cost. To demonstrate
how to choose the quantities of variable inputs to minimize costs, assume that you
are dealing with the long run so that both inputs (labor and capital) are variable.
Although the demonstration uses labor and capital, the results apply to any combi-
nation of variable inputs.

Marginal Product of Labor at a Bicycle Courier Service

You are a manager at a firm like Snap Delivery, a bicycle courier service in New York City.
You estimate that if you hire 10 couriers, you can deliver 180 packages a day and if you
hire 11 couriers, you can deliver 198 packages a day. You also estimate that the price you
can charge for the delivery of each package will be $25. What is the marginal product of
labor for the 11th courier? What is the effect of the price on the marginal product of labor?

Answer

The marginal product of labor is equal to the change in the output divided by the
change in labor, or

MP L =
∆Q
∆L

The total output using 11 couriers is 198 packages, and the total output using 10 couriers
is 180 packages. So the change in output, ∆Q, that occurs by adding the 11th courier
is 198 packages – 180 packages, or 18 packages. The change in employment, ∆L, is
1 worker, so the marginal product of the 11th courier is 118 packages2>11 worker2, or
18 packages. The price of the delivery plays no role in determining the marginal product
because the marginal product is based solely on the change in output and the change
in input.

SOLVED
PROBLEM

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148  CHAPTER 4 Production and Costs

The decision to use an additional unit of an input—say, hire a worker—has two
immediate effects:

1. The firm’s output increases. Recall that the marginal product of labor is the
amount by which production increases, so hiring another worker increases the
firm’s output by MPL units.

2. The firm’s total cost increases. Assume that the cost of hiring a worker is the
wage rate (W), the amount that the worker must be paid. In reality, firms must
also pay taxes, unemployment insurance, and possibly fringe benefits. More-
over, merely employing another worker usually does not increase production on
its own because additional raw materials must often be purchased. For example,
when you hire another cook for your restaurant, you might also need to pur-
chase more flour to enable that worker to boost production of pasta and bread.
For simplicity, consider all of these costs (taxes, fringe benefits, unemployment
insurance, and price of other necessary materials) as part of the wage rate, W.

Cost-Minimization Rule
To derive the cost-minimization rule, start by combining the marginal product of
labor and the wage rate into one term,

MPL
W . This term measures the change in output

that results from a $1 change in the quantity of labor employed. For example, if the
wage of a restaurant worker is $100 and the marginal product of the worker is 20
dinners, then

MPL
W

=
20 dinners

$100
= 0.2 dinners per dollar

In other words, as the restaurant’s general manager, for each additional dollar spent
on labor you gain 0.2 dinners. Alternatively, for each decrease of a dollar spent on
labor you lose 0.2 dinners.

Similar calculations hold for any input. For example, if R is the cost of using an
additional unit of capital equipment,2 then

MPK
R is the change in production from a $1

change in the quantity of capital used.
Using both of these fractions, you arrive at the cost-minimization rule: To mini-

mize cost, a firm should use the combination of labor and capital that produces the
desired amount of output and is such that

MPL
W =

MPK
R .

To minimize cost, a firm should use the combination of labor and capital that produces

the desired amount of output and is such that
MP L
W =

MP K
R .

COST-MINIMIZATION RULE

2 Both the services from and the expenditures for a piece of capital equipment typically accrue for many
periods. This fact complicates the proper measurement of the cost of capital. Chapter 16 covers these issues
in detail. This chapter sidesteps this difficulty by assuming that both MPK and R are measured correctly.

Why does this equality minimize cost? It minimizes cost because if the two terms
are not equal, a manager can adjust the quantity of inputs used and lower the cost
without changing the total quantity produced. Let’s see how these adjustments work:

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4.2 Cost Minimization  149

• If
MPL
W 7

MPK
R , the quantity of inputs can be changed to lower the firm’s cost.

For example, suppose that
MPL
W = 6 units per dollar and

MPK
R = 2 units per dollar.

At these values, reducing the amount spent on capital by $3 decreases produc-
tion by 6 units 12 units * $32, and increasing the amount spent on labor by $1
increases production by 6 units. Combining these changes leaves the quantity

produced unchanged but lowers the cost by $2 1$3 – $12. More generally,
whenever

MPL
W 7

MPK
R , you can lower the total cost by increasing the amount of

labor used and decreasing the amount of capital used. As you make these
changes, the increase in the quantity of labor decreases the marginal product of
labor, and the decrease in the quantity of capital increases the marginal product

of capital, thereby driving the inequality
MPL
W 7

MPK
R toward the cost-minimizing

equality,
MPL
W =

MPK
R . But as long as

MPL
W exceeds

MPK
R , increasing the amount of

labor used and decreasing the amount of capital used lowers the total cost.

• If
MPK

R 7
MPL
W , the cost can once again be reduced by adjusting the quantity of

inputs employed. In this case, however, you would increase the quantity of capital
and decrease the quantity of labor. Suppose that

MPK
R = 8 units per dollar and

MPL
W = 1 unit per dollar. At these values, reducing the amount spent on labor by

$8 decreases production by 8 units 11 unit * $82, and increasing the amount spent
on capital by $1 increases production by 8 units. Combining these changes again
leaves the quantity produced unchanged but lowers the cost, this time by $7
1$8 – $1). As you make this change, the increase in the quantity of capital decreases
the marginal product of capital, and the decrease in the quantity of labor increases

the marginal product of labor, driving the inequality
MPK

R 7
MPL
W toward the cost-

minimizing equality,
MPL
W =

MPK
R . As long as

MPK
R exceeds

MPL
W , increasing the amount

of capital used and decreasing the amount of labor used lowers the total cost.

The cost-minimizing lesson from these examples is straightforward: Increase
spending on the input with the larger output per dollar, and reduce spending on the
input with the lower output per dollar.

Generalizing the Cost-Minimization Rule
The cost-minimization rule generalizes beyond the example of two inputs. To mini-
mize the cost of producing the desired quantity of output with more than two inputs
requires that

MP1
P1

=
MP2
P2

=
MP3
P3

= c
MPn
Pn

4.1

In Equation 4.1, MP1 is the marginal product of the first input and P1 is the price of
the first input, MP2 is the marginal product of the second input and P2 is the price of
the second input, and so on. For example, if the first input is labor, then MP1 is the
marginal product of labor, MPL, and P1 is the wage rate, W.

The intuition behind Equation 4.1 and that behind the two-input cost-minimization
rule are identical. When MPi is the marginal product of input i and Pi is its price, then
the term

MPi
Pi

equals the change in output from changing spending on input i by $1.
According to the cost-minimization rule, these terms must be equal for all inputs, so
the change in output from changing spending by $1 on any input must be equal for
all inputs. If these quantities are not equal, the manager can lower costs by buying

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150  CHAPTER 4 Production and Costs

4.3 Short-Run Cost
Learning Objective 4.3 Distinguish between fixed cost and variable cost and
calculate average total cost, average variable cost, average fixed cost, and
marginal cost.

Effective managers make decisions based on understanding how their firm’s costs
change when the production of output changes. This section begins by examining

Cost Minimization at a Construction Firm

As a construction manager for a firm like KB Home, you employ carpenters and carpen-
ter assistants. You pay your carpenters $800 per week and your carpenter assistants
$500 per week. The marginal product of a carpenter is construction of 2 rooms per
week, and the marginal product of a carpenter assistant is construction of 1 room per
week. Are you minimizing your costs? Explain your answer.

Answer

Cost minimization requires that

MP CARPENTER
WCARPENTER

=
MPASS‘T CARPENTER
WASS‘T CARPENTER

But using the data in the problem shows that

2 rooms per week
$800 per week


1 room per week

$500 per week

so you are not minimizing your costs. Spending an additional dollar on a carpenter
increases your construction of rooms by more than spending that dollar on a carpenter
assistant, so increasing the number of carpenters and decreasing the number of carpenter
assistants will decrease your cost. You can verify this conclusion by noticing that hiring an
additional carpenter for ½ of a week enables you to construct 1 room at a cost of $400, while
laying off a carpenter assistant for a week decreases your construction by 1 room but saves
you $500 in cost. Combining these changes leaves the number of rooms you construct the

same, but your costs fall by $100. As long as the
MP CARPENTER
WCARPENTER

and
MPASS‘T CARPENTER
WASS‘T CARPENTER

terms are not

equal, you can decrease your cost by using more of the input with the larger change in
production per dollar and less of the input with the smaller change in production per dollar.

SOLVED
PROBLEM

more of the inputs that give the manager more output (those with high MPP ) and buying
fewer of the inputs that give the manager less output (those with low MPP ). No matter
how many inputs managers use in the production process, whenever the change in
output from spending $1 on one input differs from that for another input, managers
can lower the total cost by using more of the input with the larger change in output
and less of the input with the smaller change.

Successful managers make decisions that minimize the cost of producing a given
quantity of output. They also know how costs change when the quantity of output
changes. You will begin to learn about this important topic in the next section on
short-run changes in cost.

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4.3 Short-Run Cost  151

short-run costs. As you learned in Section 4.1, the short run is the time period during
which at least one input is fixed. To capture this difference between inputs, again use
the two-input short-run production function, Q = f1L, K2. Recall that the bar over K
signifies that the quantity of capital is fixed. This two-input short-run production
function means that managers can change the quantity produced only by changing
the quantity of the variable input, labor. In reality, managers can change the quantity
produced by adjusting the amount(s) of any of a larger number of variable inputs.
But as usual, once you understand the two-input production function, you can apply
this simplified approach to more realistic situations.

Fixed Cost, Variable Cost, and Total Cost
Regardless of the number of inputs, all the inputs can be sorted into one of two cate-
gories: fixed or variable. The sum of the costs paid for all fixed inputs is called the
fixed cost (FC). Fixed cost does not change with changes in output because the quan-
tity of fixed inputs cannot be changed. The sum of the costs paid for all variable
inputs is called the variable cost (VC). Variable cost changes with changes in output
because managers must change the quantity of variable inputs in order to change
output. Since every input falls into one of the two groups (fixed inputs or variable
inputs), the total cost (TC) of the inputs equals the sum of the fixed costs (for the fixed
inputs) and the variable costs (for the variable inputs), or

TC = FC + VC

Table 4.2 relates a firm’s production function to its costs. The first three col-
umns of Table 4.2 are from the production function shown in Table 4.1 when your
Italian restaurant uses 6 units of capital (K). The fixed input is capital, so the cost
of the capital is the fixed cost. Suppose that the cost of each unit of capital, which
might represent rental payments on the building, interest payments due on the
capital equipment, or the economic depreciation of the capital, is $83.33. The
fixed cost (FC) for all 6 units is $500, 6 units of capital multiplied by $83.33 per
unit of capital. The variable input is labor, so the cost of the labor is the variable
cost. Suppose that the cost of each unit of labor (the sum of the wage rate plus
other costs of hiring a worker) is $100. In the first row of Table 4.2, when no work-
ers are hired, the variable cost is $0. In the second row, when one worker is hired,
the variable cost is $100. In the third row, when two workers are hired, the variable
cost is $200.

Table 4.2 illustrates a fundamental difference between fixed cost and variable
cost: The fixed cost remains constant when output changes, but the variable cost
changes with a change in output. This difference reflects the distinction between a
fixed input and a variable input. In the short run, a firm cannot change the amount
of its fixed input(s), so the fixed cost remains constant—fixed—when output
changes. But to change its output, the firm must change the amount of its variable
input(s), so when output changes, so does the variable cost.

Table 4.2 shows two other significant aspects of total cost:

1. Even when output is zero—that is, even when the firm is closed—the firm still
incurs a cost. In particular, the firm still must pay its fixed costs. Although the
variable costs are zero when the firm is closed, the total cost is not zero.

2. When output changes, the total cost changes. When output increases, the total
cost increases. When output decreases, the total cost decreases. This relationship
is due entirely to the changes in the variable costs when output changes.

Fixed cost The sum of the
costs paid for all fixed
inputs; fixed cost does not
change when output
changes.

Variable cost The sum of
the costs paid for all
variable inputs; variable
cost changes when output
changes.

Total cost The sum of the
fixed cost and the variable
cost; TC = FC + VC .

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152  CHAPTER 4 Production and Costs

Sunk Cost Versus Fixed Cost
In Chapter 1 you learned about sunk costs, costs that you cannot recover because they
have been paid or incurred in the past. Costs that have already been paid do not change
when output changes. Consequently, all sunk costs are fixed costs, but not all fixed
costs are sunk costs. For example, your restaurant might have a month-to-month rental
agreement that specifies rent on the site of $200 per day. The rent is a fixed cost because
it pays for a fixed input and does not change with the number of dinners produced. But
the rent is not a sunk cost because the restaurant pays it month by month.

Average Fixed Cost, Average Variable Cost, and
Average Total Cost
The next three columns of Table 4.2 have data related to three more cost concepts:
average fixed cost, average variable cost, and average total cost. The definitions of
these three cost concepts are similar. Average fixed cost (AFC) is the fixed cost (FC)
divided by the amount of output (Q), or, in algebraic terms, AFC = FCQ . The average
variable cost (AVC) is the variable cost (VC) divided by the amount of output, or
AVC = VCQ . Finally, the average total cost (ATC) is the total cost (TC) divided by the

amount of output, or ATC = TCQ .
Average total cost also equals the sum of the average fixed cost and the average

variable cost: ATC = AFC + AVC. This alternative expression is derived from the
definition of total cost: TC = FC + VC. Divide both sides of the total cost definition
by the quantity (Q), and the result is

TC
Q

=
FC
Q

+
VC
Q

1 ATC = AFC + AVC

Average fixed cost Fixed
cost divided by the amount
of output; AFC = FCQ .

Average variable cost
Variable cost divided by
the amount of output;
AVC = VCQ .

Average total cost Total
cost divided by the amount
of output; ATC = TCQ .

Table 4.2 Short-Run Production Function and Cost Data

The table presents a short-run production function and the resulting costs. The cost of a unit of labor is $100,
and the cost of a unit of capital is $83.33. Because marginal cost is calculated for a change in output, each MC is
placed midway between two rows, indicating that it applies to the change in output between the rows.

Capital,
K

Labor,
L

Output,
Q

Fixed
Cost, FC

Variable
Cost, VC

Total
Cost, TC

Average
Fixed
Cost,
AFC

Average
Variable

Cost,
AVC

Average
Total
Cost,
ATC

Marginal
Cost,
MC

6 0 0 $500 $0 $500 X X X
$8.33

4.55

2.63

1.47

1.11

1.43

2.00

2.50

3.33

5.00

10.00

6 1 12 500 100 600 $41.67 $8.33 $50.00

6 2 34 500 200 700 14.71 5.88 20.59

6 3 72 500 300 800 6.94 4.17 11.11

6 4 140 500 400 900 3.57 2.86 6.43

6 5 230 500 500 1,000 2.17 2.17 4.35

6 6 300 500 600 1,100 1.67 2.00 3.67

6 7 350 500 700 1,200 1.43 2.00 3.43

6 8 390 500 800 1,300 1.28 2.05 3.33

6 9 420 500 900 1,400 1.19 2.14 3.33

6 10 440 500 1,000 1,500 1.14 2.27 3.41

6 11 450 500 1,100 1,600 1.11 2.44 3.56

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4.3 Short-Run Cost  153

Figure 4.5 shows how the average fixed cost, average variable cost, and average
total cost change when quantity increases or decreases. The behavior of the AFC
curve is unique: The average fixed cost constantly falls as the quantity increases.3 In
Figure 4.5, the average fixed cost (the blue curve) falls from $14.71 when 34 dinners
are produced to $1.11 when 450 dinners are produced. As additional dinners beyond
450 are produced, the average fixed cost continues to fall.

The shapes of the AVC curve and the ATC curve are more complicated. As
Table 4.2 and Figure 4.5 show, both of these costs start out large, decrease until
they hit a minimum, and then increase. The U shape is typical of the AVC curve (in
red) and the ATC curve (in green) for any type of firm, not just a restaurant. Of
course, different firms reach the minimum points on the curves at different
amounts of production.

The explanation of the U shape must wait until the next section, which covers mar-
ginal cost. For now, note that in Figure 4.5 the vertical distance between the two curves
becomes smaller as output increases. The equation ATC = AFC + AVC shows why.
Rearranging it to ATC – AVC = AFC shows that the difference between the average
total cost and the average variable cost is the average fixed cost. As you just learned,
the average fixed cost becomes smaller as output increases. With average fixed cost
becoming smaller, the difference between the average total cost and average variable
cost becomes smaller, which means that the AVC curve approaches the ATC curve.

Marginal Cost
As a manager, knowing your average total cost and average variable cost can be
helpful in making decisions, but knowing yet another cost, the marginal cost, is sig-
nificantly more important. Like all marginal concepts, the marginal cost focuses on
changes. The marginal cost (MC) is the change in the total cost brought about by a

Marginal cost (MC ) The
change in total cost (TC )
divided by the change in
output (Q ); MC = ∆TC∆Q .

3 As output increases, fixed cost does not change. Consequently, for the average fixed cost, as output
increases the numerator does not change and the denominator increases, so the fraction falls in value.

Cost (dollars per dinner)

Output (dinners per day)

$2.00

$4.00

$6.00

$8.00

$10.00

$12.00

$14.00

$16.00

$18.00

$20.00

47542537532527522517512575250

ATC
AVC

AFC

Figure 4.5 AFC, AVC,
and ATC Curves

The three cost curves
are derived from the
data in Table 4.4. Both
the AVC and the ATC
curves are U-shaped.
The vertical distance
between the AVC and
ATC curves becomes
smaller as the
quantity increases.

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154  CHAPTER 4 Production and Costs

The marginal cost shows the change in total cost when output changes. Because the
fixed cost does not change when output changes, it has no effect on the marginal cost.

The last column in Table 4.2 shows the marginal cost for your Italian restaurant.
Because marginal cost is calculated for a change in output, each MC listing in the table is
placed midway between two rows, indicating that it applies to the change in output
between the rows. For example, when output increases from 300 to 350 units, the total
cost increases from $1,100 to $1,200, so the marginal cost equals $10050 = $2.00 per dinner.

Figure 4.6 shows the MC curve calculated from the data in Table 4.2, along with the
AVC curve and the ATC curve. In Figure 4.6, the marginal cost values are plotted midway
between the relevant quantities, indicating that the marginal cost applies to the change in
output between these quantities. For example, the marginal cost of increasing production
from 34 to 72 dinners, $2.63, is plotted at 53 dinners, midway between 34 and 72 dinners.

Figure 4.6 shows that the marginal cost initially falls and then rises as the quan-
tity increases. The general U shape of the MC curve is common to all firms. In fact,
the U shape of the MC curve is the consequence of how the marginal product of the
variable inputs changes as output changes.

Suppose that labor is the only variable input. The cost of hiring an additional
worker is W, and the increase in output is MPL. Consequently, the cost of producing
one more unit of output—the marginal cost—by hiring an additional worker is equal
to WMPL. For example, using the data in Table 4.2, hiring the first restaurant worker
increases the production of dinners from 0 dinners to 12 dinners, so the marginal
product of this worker is 12 dinners. At a wage rate of $100, the marginal cost of

Fat Tire Tours is a Paris-based company selling “skip-the-line” tours to the Eiffel Tower
and other Paris landmarks. Suppose that you manage a similar company and each
year your company sells tours to 60,000 sightseers, with a marginal cost of $47 per
tour. In addition, suppose that last year the monthly insurance premium you paid to
insure against accidents was $6,000. This year the insurance company increases the
premium to $9,000. How would this change affect your company’s marginal cost?

Answer
It may surprise you that the change in the insurance premium has no effect on
the marginal cost. In other words, the marginal cost does not change. The
marginal cost measures how the total cost changes when output changes (when
the number of tours changes). The insurance premium is a fixed cost. The premium
does not change when your company sells more or fewer tours. Accordingly,
the (fixed) insurance premium has no effect on the marginal cost.

DECISION
SNAPSHOT

Input Price Changes and Changes in the
Marginal Cost of an Eiffel Tower Tour

change in output and is defined as MC = ∆TC∆Q , where, as usual, the symbol delta (Δ)
means “change in.” Marginal cost is most meaningful when calculated for small changes
in output. When output increases by a single unit, the marginal cost is the additional cost
incurred to produce the additional unit. Conversely, when output decreases by a single
unit, the marginal cost is the decrease in cost from not producing the unit. You will see
throughout this text that the marginal cost plays a vital role in decision making.

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4.3 Short-Run Cost  155

producing one more dinner between 0 and 12 dinners is $10012 dinners = $8.33 per dinner.
The marginal product of the second worker is 22 dinners, so the marginal cost of

producing one more dinner between 12 and 34 dinners is $10022 dinners = $4.55 per dinner.
The larger the marginal product, the smaller the marginal cost. Over the range of
output with increasing marginal returns to labor, the marginal product increases, so
the marginal cost decreases and the MC curve slopes downward. Eventually, as
more workers are hired, the range with decreasing marginal returns to labor is
reached, and the marginal product starts to decrease. For example, the 11th worker
has a marginal product of only 10 dinners, so the marginal cost of producing one

more dinner here is $10010 dinners = $10.00 per dinner, much larger than the marginal cost
when hiring the first or second worker. Once the marginal product starts to decrease,
the marginal cost of an additional dinner increases, so over this range of output the
MC curve slopes upward.

The following box summarizes the general relationship between the marginal
product of labor and marginal cost.

• Over the range of output where the marginal product of labor increases, the
marginal cost decreases.

• At the level of output where the marginal product of labor is at its maximum,
the marginal cost is at its minimum.

• Over the range of output where the marginal product of labor decreases, the
marginal cost increases.

RELATIONSHIP BETWEEN THE MARGINAL PRODUCT OF LABOR
AND MARGINAL COST

Cost (dollars per dinner)

Output (dinners per day)

$1.00

$2.00

$3.00

$4.00

$5.00

$6.00

$7.00

$8.00

$9.00

$10.00

$11.00

47542537532527522517512575250

ATC

AVC

MCThe MC curve intersects
the ATC and AVC curves
at their minimum points.

Figure 4.6 MC, ATC,
and AVC Curves

The figure shows
three cost curves
from Table 4.2. The
values for the MC
curve are plotted
midway between the
relevant quantities.
The MC curve
intersects the AVC
curve and the ATC
curve at their
minimums.

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156  CHAPTER 4 Production and Costs

Marginal/Average Relationship
Figure 4.6 illustrates another notable result: The MC curve intersects the AVC curve
and the ATC curve at their minimum points, an example of a more general relation-
ship called the marginal/average relationship. The marginal/average relationship has
two parts:

• If the marginal ________ is greater than the average ________, then the average
________ increases.

• If the marginal ________ is less than the average ________, then the average
________ decreases.

As the blanks imply, this relationship applies anytime a marginal and an aver-
age are involved. For example, every student is familiar with this general relation-
ship: If the grade you receive in an additional class (a marginal class) exceeds your
grade point average (GPA), then your GPA will rise. Conversely, if the grade you
receive in an additional class is less than your GPA, then your GPA will fall. What is
true for grades is also true for costs: If the marginal cost of another unit is greater
than the average cost, then the average cost will rise. If the marginal cost of another
unit is less than the average cost, then the average cost will fall.

These results mean that the MC curve must intersect the AVC curve and the
ATC curve at their minimums. In Figure 4.6, examine the relationship between
average variable cost and marginal cost when your Italian restaurant produces less
than 325 dinners. Over this range of production, the marginal cost of another dinner
is less than the average variable cost, so producing an additional dinner means a
decrease in the average variable cost. As the figure shows, the AVC curve slopes
downward.

Now look at this same relationship when the production exceeds 325 dinners.
Over this range of output, the marginal cost of another dinner is greater than the
average variable cost, so producing another dinner increases the average variable
cost. As Figure 4.6 shows, the AVC curve slopes upward. Combining these two
results demonstrates that the AVC curve slopes downward until it reaches 325 din-
ners, after which it slopes upward. Therefore, average variable cost must equal its
minimum at 325 dinners, the quantity where it intersects the MC curve. The same
reasoning leads to the conclusion that the MC curve intersects the ATC curve at its
minimum.4

In Figure 4.6, the AVC curve is flat at its minimum value, between 300 and 350
dinners. If Table 4.2 had a finer division for the labor input—for instance, increasing
the numbers of workers fractionally by hiring part-time labor—then the curves
might not have long, straight sections. Even with hiring fractional numbers of work-
ers, however, some firms’ production techniques are such that their average cost
curves still have long flat sections at their minimums.

Competitive Return
This section has developed cost theory with the assumption that a firm uses only
two inputs. Realistically, of course, any firm will use many more inputs. When
considering costs such as the average total cost or marginal cost, it is essential
that you include the opportunity costs of all of the inputs. As you learned in
Chapter 1, one key input is the assets made available by the firm’s owners, such

4 We formally prove this result using calculus in Section 4.C of the Appendix at the end of this chapter.

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4.3 Short-Run Cost  157

as the funds supplied to a large corporation by its investors. The opportunity cost
of the owners’ resources is the return these resources would earn if invested in the
next best alternative use (the competitive return). As an opportunity cost of the
business, the competitive return is included among all the other costs, such as
wages and rent, when calculating the average total cost, average variable cost,
and marginal cost.

Shifts in Cost Curves
Understanding how cost changes when output changes will help you make optimal
managerial decisions. The cost curves just presented provide a good framework for
organizing your thoughts. But you must also understand the factors that change
costs and shift the cost curves because shifts in cost curves can change business deci-
sions. Three factors shift the cost curves: (1) changes in the prices of the inputs,
(2) changes in technology that alter the production function, and (3) economies and
diseconomies of scope.

The Effect of Changes in Input Prices on the Cost Curves
Costs change and cost curves shift if the price of an input changes. The curves that
shift depend on the type of input that changes in price. For example:

• If the price of a fixed input (such as the rent on a firm’s store or factory) rises,
then the fixed cost increases, and the FC curve shifts upward. Because the fixed
cost is part of the total cost, the average total cost increases, and the ATC curve
also shifts upward. Neither the AVC nor the MC curve shifts, because the fixed
cost does not affect the variable or marginal costs. Figure 4.7 shows the effect an
increase in the fixed cost has on the ATC, AVC, and MC curves for your Italian
restaurant.

Cost (dollars per dinner)

Output (dinners per day)

$1.00

$2.00

$3.00

$4.00

$5.00

$6.00

$7.00

$8.00

$9.00

$10.00

$11.00

47542537532527522517512575250

ATC0

ATC1

AVC

MC

Figure 4.7 Effect of
an Increase in Fixed
Cost

An increase in the
fixed cost shifts the
ATC curve upward. It
does not shift the
AVC and MC curves.

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158  CHAPTER 4 Production and Costs

• If the price of a variable input (such as the wage rate) rises, then the variable cost
increases, and the AVC and ATC curves both shift upward. The MC curve also
shifts upward. Figure 4.8 shows the effect of an increase in the variable cost for
your restaurant.

The Effect of Changes in Technology on the Cost Curves
Changes in technology shift both the production function and the cost curves. Some-
times technological change means that fewer inputs are necessary to produce the
same quantity of output. For example, Toyota has redesigned its assembly lines from
a straight line to a U shape. The U shape allows the workers to accomplish more
work in the same time on each vehicle, decreasing the number of workers that Toy-
ota must use to produce a car. Airbus provides another example: The company used
to install overhead bins directly part-by-part in the plane. It now assembles the bins
outside of the plane and then installs them in one piece. This change has decreased
the time and labor spent installing bins. These types of technological changes reduce
the cost for each unit of output produced and shift the AVC, ATC, and MC curves
downward.

Learning-by-doing is an important source of technological change. Learning-
by-doing refers to the idea that as a firm produces more of a particular product, its
workers become better at the production process, thereby lowering costs. Com-
puter chips are a prime example. Computer chip–manufacturing firms like Intel
produce computer chips on large wafers, approximately 12 inches in diameter. Each
wafer has many chips etched into it, but minuscule errors result in some of the
chips malfunctioning. As a firm produces the same wafer week after week and
month after month, its technicians learn how to increase the yield of good chips.
The knowledge gained from learning-by-doing is a technological change that shifts
the cost curves downward.

Cost (dollars per dinner)

Output (dinners per day)

$1.00

$2.00

$3.00

$4.00

$5.00

$6.00

$7.00

$8.00

$9.00

$10.00

$11.00

47542537532527522517512575250

ATC 0

ATC1

AVC 0

AVC 1

MC 0

MC 1

Figure 4.8 Effect of an
Increase in Variable
Cost

An increase in the
variable cost shifts the
ATC, AVC, and MC
curves upward.

M04_BLAI8235_01_SE_C04_pp138-185.indd 158 23/08/17 10:07 AM

4.3 Short-Run Cost  159

A firm like Intel can use its learning curve, a curve that shows how the average
total cost of a chip falls as the firm produces more wafers, to help predict its average
total cost of a particular chip. Figure 4.9 shows such a learning curve. After the firm
has produced 100,000 wafers, the average total cost of this chip is $70, but the aver-
age total cost falls to $50 and then $30 after 200,000 and then 500,000 wafers have
been produced.

The flip side of learning-by-doing is forgetting-by-not-doing. Forgetting-
by-not-doing refers to a situation in which workers forget the most efficient way of

Suppose that you are an executive at a steel mill owned by Shagang Group, one
of China’s top five steel producers. Heating iron and other ores to high tempera-
tures is one of the first steps in steel making. The heat to melt the ores often
comes from burning coal. How does an increase in the price of iron affect your
average total cost and marginal cost? How does an increase in the price of coal
affect your average total cost and marginal cost? Finally, how does an increase in
the wage paid your employees affect your average total cost and marginal cost?

Answer
Increases in the prices of all three inputs increase your average total cost. All
three inputs—iron, coal, and workers—are variable inputs. More iron, more coal,
and more workers are necessary to produce more steel. Increases in any of these
three prices increase your marginal cost.

DECISION
SNAPSHOT

Changes in Input Prices and Cost
Changes at Shagang Group

Average cost of a computer
chip (dollars per chip)

Cumulative quantity of wafers (wafers)

$10

$20

$30

$40

$50

$60

$70

$80

$90

$100

6005004003002001000

Figure 4.9 A Learning
Curve for a Computer Chip

The learning curve shows
how the average total cost
of a chip falls as the firm
reaps learning-by-doing
economies from producing
more wafers.

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160  CHAPTER 4 Production and Costs

doing an activity because of a decrease in production, causing the company’s cost
curves to shift upward. There is evidence that learning-by-doing can be important in
many industries and for many firms. There is less evidence supporting the perils of
forgetting-by-not-doing, though in recent years NASA had to spend significant sums
of money to rediscover how to produce huge rockets, such as the Saturn V rocket
(the rocket that sent astronauts to the moon). Because no one had made such huge
rockets for decades, NASA engineers had effectively forgotten how to produce them.

Often technological changes are embedded in capital. In other words, new capi-
tal is required to implement technological change. For example, JCPenney, a mid-
level U.S. retailer, and Burberry, a high-end U.K. retailer, have recently changed the
procedure by which customers use credit and debit cards to purchase their products.
Previously, customers lined up at fixed cash registers, but these companies decided
to equip their associates with mobile iPod and iPad checkout devices. This techno-
logical change altered the type and the quantity of capital required at their stores.

The Effect of Economies and Diseconomies of Scope
on the Cost Curves
Firms that produce more than one good are called multiproduct firms. Producing
multiple goods can have varied effects on a firm’s costs. We discuss two: economies
of scope and diseconomies of scope. The first lowers the firm’s costs and shifts its
cost curves downward, and the second raises the firm’s costs and shifts its cost
curves upward.

1. Economies of scope occur when the total cost of producing two or more goods
is lower if they are produced within one firm than if they are produced sepa-
rately by two different firms. For example, Intel and other chip-manufacturing
firms produce computer chips and spend billions of dollars researching methods
of shrinking the transistors used on each chip. When Intel started to produce
chips for wireless communication, it used the same research to shrink the tran-
sistors on these chips. Spreading the cost of the research across the different
types of chips means Intel’s total cost is lower when compared to the total costs
of two independent firms, each one specializing in the production of one type of
chip and separately performing the research to shrink transistors.

Cost complementarities are a special case of economies of scope. Cost comple-
mentarities occur when the production of one good makes the marginal cost of
producing another good at the same firm lower compared to the marginal cost
of a firm that produces only the second good. For example, refineries produce
kerosene by heating petroleum until it evaporates and then allowing it to cool.
They collect the kerosene as it condenses from the petroleum vapor at tempera-
tures between 600°F and 350°F. Refineries also produce gasoline, in this case by
simply letting the vapor cool some more and collecting the gasoline when it
condenses at temperatures between 210°F and 140°F. By producing kerosene
and gasoline, the petroleum is heated only once to a very high temperature to
collect the kerosene, so there is no need to incur a separate cost of heating the
petroleum to collect gasoline, thereby making the marginal cost of producing
gasoline lower than it would be at a firm that refined petroleum and produced
only gasoline.

2. Diseconomies of scope occur when the total cost of producing two goods is
higher if they are produced within one firm than if they are produced sepa-
rately by two different firms. In this case, the total cost of producing any of the
goods increases as the firm produces more types of goods. For example,

Economies of scope The
total cost of producing two
goods is lower if they are
produced within one firm
than if they are produced
separately by two different
firms.

Diseconomies of
scope The total cost of
producing two goods is
higher if they are produced
within one firm than if they
are produced separately
by two different firms.

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4.3 Short-Run Cost  161

Calculating Different Costs at a Caribbean Restaurant

The following table includes the various costs involved in operating a restaurant like
Bahama Breeze, an American restaurant chain that serves Caribbean-inspired dishes.
Supposing all the workers are paid the same wage, fill in the missing numbers.

SOLVED
PROBLEM

Capital,
K

Labor,
L

Output,
Q

Fixed
Cost,

FC

Variable
Cost,
VC

Total
Cost,

TC

Average
Fixed Cost,

AFC

Average
Variable Cost,

AVC

Average Total
Cost,
ATC

Marginal
Cost,
MC

2 0 0 X X X
$20.00

2 1 10 200 $35.00
2 2 40 18.75
2 3 90
2 4 150 5.33
2 5 220
2 6 300 1.17
2 7 350 5.00
2 8 390

5.00

2 9 420
2 10 440 4.54
2 11 450 350 20.00

Answer

The completed table is on the next page. The fixed cost is the same for all quantities, so
it is $350 for all the rows. The second row in the table shows that the variable cost is $200
per worker, so the variable cost equals $200 per worker multiplied by the number of
workers. The total cost is equal to the sum of the fixed cost and the variable cost. The
average fixed cost equals the fixed cost divided by the output, the average variable
cost equals the variable cost divided by the output, and the average total cost equals the
total cost divided by the output. Finally, the marginal cost equals the change in the total
cost divided by the change in the output.

McDonald’s executive managers apparently determined that McDonald’s was
suffering from diseconomies of scope because the firm had allowed its menu to
get too large. The managers decided to simplify the menu by reducing the
number of different items McDonald’s sells. The reduction in the number of
menu items decreased McDonald’s total cost of producing the products they
continued to sell.

So far, you have learned how short-run costs change when output changes. As a
manager, you must also be concerned with the impact of your decisions in the long
run. As you learned earlier in this chapter, you can make more profound changes in
the operation of your business in the long run, such as remodeling to increase the
size of the dining area or the kitchen in your Italian restaurant. Such changes are
costly and not easily reversed, both of which are excellent reasons to learn about
long-run cost curves, the topic of the next section.

(Continues )

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162  CHAPTER 4 Production and Costs

4.4 Long-Run Cost
Learning Objective 4.4 Derive the long-run average cost curve and explain its
shape.

The long run is important for planning purposes because in the long run managers
can adjust the scale of the firm’s operations by changing not only the amount of
labor employed but also the amount of capital (and all other inputs). Managers’
long-run decisions about the scale of their operations are very important. For exam-
ple, if Darden’s regional managers were to approve a remodeling plan that makes
some Olive Garden restaurants too large for the most profitable operation, the firm
would need to live with this mistake for years.

Long-Run Average Cost
In the long run, managers can adjust the scale of production by changing some or all
inputs. For simplicity, assume once again that the firm uses only two inputs, capital
(K) and labor (L), to produce its output (Q). With this assumption, the long-run pro-
duction function is Q = f1L, K2. In the long run, managers can change the quantities
of both inputs. Efficient managers select the amounts of capital and labor that mini-
mize the average cost of its output.

Table 4.3 presents some more production data for your Italian restaurant. In this long-
run case, all inputs are variable. So unlike Table 4.1(a), which examined the short run
and therefore had only one quantity of capital, included in Table 4.3 are three different
quantities of capital. From these data, you can calculate three sets of average total costs—
one for 4 units of capital, one for 6 units of capital, and one for 8 units of capital. Assum-
ing again that one unit of capital costs $83.33 and one unit of labor costs $100, Table 4.4
shows the average total costs in the short run for the three different amounts of capital.
The columns in the tables are shaded to help you to see the linkage between the tables.

The Long-Run Average Cost Curve
Part of a manager ’s job is to determine the combination of inputs that minimizes
the average total cost of its output. As a manager, you will make day-to-day deci-
sions that minimize your short-run average cost, but the long-run decision about

Capital,
K

Labor,
L

Output,
Q

Fixed
Cost,

FC

Variable
Cost,
VC

Total
Cost,

TC

Average
Fixed Cost,

AFC

Average
Variable

Cost, AVC

Average
Total

Cost, ATC

Marginal
Cost,
MC

2 0 0 $350 $0 $350 X X X
$20.00

6.67
4.00

3.33
2.86
2.50
4.00
5.00
6.67

10.00

20.00

2 1 10 350 200 550 $35.00 $20.00 $55.00
2 2 40 350 400 750 8.75 10.00 18.75
2 3 90 350 600 950 3.89 6.67 10.56
2 4 150 350 800 1,150 2.33 5.33 7.66
2 5 220 350 1,000 1,350 1.59 4.55 6.14
2 6 300 350 1,200 1,550 1.17 4.00 5.17
2 7 350 350 1,400 1,750 1.00 4.00 5.00
2 8 390 350 1,600 1,950 0.90 4.10 5.00
2 9 420 350 1,800 2,150 0.83 4.29 5.12
2 10 440 350 2,000 2,350 0.80 4.54 5.34
2 11 450 350 2,200 2,550 0.78 4.89 5.67

SOLVED PROBLEM (continued )

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4.4 Long-Run Cost  163

Table 4.3 The Long-Run Production Function

All inputs are variable in the long-run production function.

Capital,
K

(units of
capital)

Labor,
L

(workers)

Output,
Q

(dinners
per day)

Capital,
K

(units of
capital)

Labor,
L

(workers)

Output,
Q

(dinners
per day)

Capital,
K

(units of
capital)

Labor,
L

(workers)

Output,
Q

(dinners
per day)

4 0 0 6 0 0 8 0 0

4 1 8 6 1 12 8 1 14

4 2 26 6 2 34 8 2 40

4 3 50 6 3 72 8 3 90

4 4 85 6 4 140 8 4 170

4 5 130 6 5 230 8 5 290

4 6 170 6 6 300 8 6 370

4 7 205 6 7 350 8 7 440

4 8 235 6 8 390 8 8 500

4 9 250 6 9 420 8 9 550

4 10 240 6 10 440 8 10 580

4 11 230 6 11 450 8 11 600

Table 4.4 Short-Run Average Total Costs

The table shows the average total costs for different amounts of capital.

4 Units of Capital 6 Units of Capital 8 Units of Capital

Output,
Q

Average
Total

Cost, ATC

Output,
Q

Average
Total

Cost, ATC

Output,
Q

Average
Total

Cost, ATC

0 X 0 X 0 X

8 $54.17 12 $50.00 14 47.62

26 20.51 34 20.59 40 21.67

50 12.67 72 11.11 90 10.74

90 8.63 140 6.43 170 6.27

130 6.41 230 4.35 290 4.02

170 5.49 300 3.67 370 3.42

210 5.04 350 3.43 440 3.11

240 4.82 390 3.33 500 2.93

250 4.93 420 3.33 550 2.85

240 5.56 440 3.41 580 2.87

230 6.23 450 3.56 600 2.94

the quantity of capital to use determines what choices are available on any given
day. Figure 4.10 illustrates the three sets of short-run average total cost data from
Table 4.4. The figure shows that the amount of capital that minimizes the average
cost depends on the scale of output—that is, quantity of dinners produced. For
example, if you project that your Italian restaurant will serve 80 dinners per day,
using 4 units of capital will have the lowest average total cost, approximately $9 per

M04_BLAI8235_01_SE_C04_pp138-185.indd 163 08/09/17 12:25 PM

164  CHAPTER 4 Production and Costs

Cost (dollars per dinner)

Output (dinners per day)

$1.00

$2.00

$3.00

$4.00

$5.00

$6.00

$7.00

$8.00

$9.00

$10.00

$11.00

560480400320240160800

ATC8
ATC6

ATC4

A

B

Figure 4.10 Using
Short-Run Average
Total Cost Curves to
Create a Long-Run
Average Cost Curve

The three short-run
average total cost
curves have been
created using data
from Table 4.4. The
subscript of each
curve denotes the
amount of capital
used. The LAC curve
will run along the
ATC4 curve until point
A, then along the
ATC6 curve until point
B, and then along the
ATC8 curve.

dinner. If instead you forecast that the restaurant will serve 240 dinners per day,
6 units of capital minimizes the average total cost, and 8 units of capital is optimal
at 440 dinners per day.

You can use this type of analysis to determine the minimum average total cost of
producing any quantity of output. The long-run average cost is defined as the mini-
mum average total cost of producing any given quantity of output when all inputs
can be changed.

The long-run average cost (LAC) curve shows how the long-run average cost
depends on the level of output. In Figure 4.10, if the only quantities of capital that
can be used are 4, 6, and 8 units, the LAC curve runs along the ATC4 curve to point A,
then along the ATC6 curve to point B, and finally along the ATC8 curve.

Figure 4.10 shows the long-run average cost with only three possible amounts of
capital for your Italian restaurant. In contrast, Figure 4.11 shows a more general case,
in which the managers can use many possible amounts of capital (and other fixed
inputs), thereby creating many short-run ATC curves. Only a few of the many possi-
ble curves are illustrated in the figure. The point on each short-run ATC curve that is
the minimum average total cost of producing an amount of output becomes a point
on the LAC curve. In other words, in Figure 4.11 the short-run blue ATC curves are
combined to trace the red LAC curve.

Note that it is only on the horizontal section of the LAC curve that the actual
minimum points of the individual (short-run) ATC curves fall on the LAC curve. For
example, take point B on ATC1. To produce 200 units, the managers could produce at
point B, which is the minimum-cost point on ATC1. If they do so, the average cost is
$12.00. However, the managers could use more capital and produce at point C on
ATC2, for an average cost of $9.00. Even though the firm is not producing at the min-
imum point on ATC2, its average cost is still lower than at the minimum point on
ATC1, which is why point C is on the LAC curve and point B is not.

The quantity at which the long-run average cost first reaches its minimum is called
the minimum efficient scale. In Figure 4.11, the minimum efficient scale is 300 units per day.

Long-run average cost
The minimum average total
cost of producing any
given quantity of output
when all inputs can be
changed.

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4.4 Long-Run Cost  165

Figure 4.11 illustrates the importance of your decision about the quantity of capital
(and other fixed inputs) to utilize. If you use too much capital (for your restaurant,
increasing your dining area too much) or too little capital (not expanding your kitchen
when you increase the size of the dining area), your firm faces higher costs for an extended
period of time until you can correct your mistake. Because the stakes are high, long-run
decisions about the quantity of capital are usually made by higher-level executives.

The LAC curve also contains some insight about your optimal response to a perma-
nent change in the quantity produced. Suppose that your firm initially produces 75 units
and you had made short-run decisions that minimized costs, so production occurred at
minimum cost at point A on the long-run average cost curve in Figure 4.11. If the firm’s
sales expand to 200 units, in the short run you can increase the quantity of the variable
inputs so the firm moves down along short-run average total cost curve ATC1 to point B,
decreasing the firm’s average cost to $12.00. In the long run, you can lower the average
cost still more by changing inputs that are fixed in the short run. You can increase the
firm’s capital, move along the LAC curve to point C (which is on short-run average total
cost curve ATC2), and lower the firm’s average cost from $12.00 to $9.00.

This same result—increasing the quantity of capital in the long run—can be
obtained using the cost-minimization analysis presented in Section 4.2. At point A in
Figure 4.11, the managers are minimizing the firm’s costs by producing 75 units of
output, so at this point

MPL
W =

MPK
R . Moving from point A to point B requires the firm to

hire more variable inputs, such as labor. Using more labor decreases the marginal
product of labor, MPL. The fall in the marginal product of labor means that at point B
the cost-minimization equality has changed to an inequality,

MPL
W 6

MPK
R . As you

learned in Section 4.2, this inequality indicates that you can lower the total cost by
increasing the quantity of capital and moving to average total cost curve ATC2,
though, of course, this change cannot be made until the long run.

Long-Run Marginal Cost
To determine the cost of each additional unit of output in the long run, you must use
the long-run marginal cost. The long-run marginal cost (LMC) is the cost of produc-
ing an additional unit of output when all inputs are variable. The long-run marginal
cost corresponds to the least costly of all the possible ways to increase output.

Long-run marginal cost
The cost of producing an
additional unit of output
when all inputs are
variable.

Cost (dollars per unit)

Output (units per day)

$2.00

$4.00

$6.00

$8.00

$10.00

$12.00

$14.00

$16.00

$18.00

1,0009008007006005004003002001000

ATC1

ATC2
ATC3

ATC4 ATC5

ATC6

A

B

C

LAC

Figure 4.11 Long-Run
Average Cost Curve

The long-run average
cost curve, the red
curve labeled LAC,
shows the minimum
average total cost to
produce different
quantities of output. The
LAC curve is comprised
of the points on the
short-run ATC curves
that are the minimum
average total cost for
each different amount
of output.

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166  CHAPTER 4 Production and Costs

The relationship between the long-run marginal cost and the long-run average
cost is the same as the relationship between the short-run marginal cost and the
short-run average total cost. As Figure 4.12 shows, when the long-run marginal cost
is less than the long-run average cost, the LAC curve slopes downward. When the
long-run marginal cost is greater than the long-run average cost, the LAC curve
slopes upward. When the long-run marginal cost equals the long-run average cost,
the long-run average cost is at its minimum. In Figure 4.12, along the horizontal sec-
tion of the LAC curve, the range where the long-run average cost is at its minimum,
the long-range marginal cost lies directly on the LAC curve. Indeed, whenever the
LAC curve is horizontal—which occurs if the long-range average cost is constant
when changing production—it is always equal to the long-range marginal cost.

Economies of Scale, Constant Returns to Scale,
and Diseconomies of Scale
A firm’s LAC curve typically has three segments: one with economies of scale, one
with constant returns to scale, and one with diseconomies of scale. Figure 4.13 iden-
tifies the segments for a bakery like Texas Star Bakery, which manufactures delicious
loaves of bread. These different returns to scale reflect features of the firm’s
technology.

The region with economies of scale is one in which the long-run average cost
falls when output increases, so the LAC curve is downward sloping. In this range,
when a firm increases all of its inputs by the same percentage, the firm’s production
process is such that its output increases by an even larger percentage. Economists
say the firm has increasing returns to scale. Increasing returns to scale lead to econo-
mies of scale. For example, if a firm increases its use of all inputs by 10 percent at the
same time, its cost rises by 10 percent. If the firm’s output increases by more than
10 percent, however, then the average cost falls.

The range with constant returns to scale is one in which the long-run average
cost does not change when output increases, so the LAC curve is horizontal. In this
case, when a firm increases all of its inputs by the same percentage, the technology is
such that its output increases by the same percentage. Therefore, a 10 percent

Economies of scale The
long-run average cost falls
when output increases; the
downward-sloping
segment of the long-run
average cost curve.

Constant returns to
scale The long-run
average cost does not
change when output
increases; the horizontal
segment of the long-run
average cost curve.

Cost (dollars per unit)

Output (units per day)

$2.00

$4.00

$6.00

$8.00

$10.00

$12.00

$14.00

$16.00

$18.00

1,0009008007006005004003002001000

LACLMC

Figure 4.12 Long-Run
Average Cost and Long-
Run Marginal Cost
Curves

The LMC curve shows
the marginal cost of
producing an additional
unit of output when all
inputs are variable. When
the LMC curve lies below
the LAC curve, the LAC
curve slopes downward;
when it lies on top of the
LAC curve, the LAC curve
is horizontal; and when it
lies above the LAC curve,
the LAC curve slopes
upward.

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4.4 Long-Run Cost  167

increase in all inputs results in a 10 percent increase in the firm’s cost and in its out-
put, so the firm’s average cost does not change.

Finally, the segment with diseconomies of scale is one in which the long-run
average cost rises when output increases, so the LAC curve is upward sloping. Over
this range of the LAC curve, when a firm increases all of its inputs by the same per-
centage, its output increases by a smaller percentage. The firm has decreasing returns
to scale. Decreasing returns to scale lead to diseconomies of scale: If the firm increases
all of its inputs by 10 percent, again raising its cost by 10 percent, its output
increases by less than 10 percent, so the average cost rises.

The Challenges of Economies of Scale
Economies of scale are often the result of increased specialization. As a firm’s pro-
duction expands, it buys more specialized equipment. For instance, consider again
the humble loaf of bread. A bakery starting out with a small scale of production,
such as at point A in Figure 4.13, makes the loaves by hand. A chef measures and
combines all ingredients, kneads the dough, lets it rise, shapes it into a loaf, bakes
the loaf in the oven, wraps it, and moves it to the front of the store, where a clerk
sells it. The average cost of producing a loaf is high. In the long run, as the bakery
expands in size and increases the scale of its production, ultimately the bread is
made almost exclusively by machine. Workers pour flour, water, yeast, and other
ingredients into enormous vats, where large mixers combine the ingredients and
knead the dough. Workers then wheel the vats of dough to huge machines that do
the rest: proof the dough (let it rise), shape it into loaves, bake the loaves, slice them,
wrap them, and then deliver them to workers who place the loaves in boxes ready to
be shipped nationwide. The scale of production is immensely larger than that of the
small bakery, and with the increased capital in the form of specialized machinery, the
firm has moved along its LAC curve and gained economies of scale.

Executives managing firms in which economies of scale are important must
always be alert to the growth of competitors. If competitors increase their scale of

Diseconomies of
scale The long-run
average cost rises when
output increases; the
upward-sloping segment of
the long-run average cost
curve.

Cost (dollars per loaf of bread)

Output (loaves of bread per day)

$0.25

$0.50

$0.75

$1.00

$1.25

$1.50

$1.75

$2.50

$2.25

$2.00

1,0009008007006005004003002001000

LAC

C

B

A

Economies
of scale

Diseconomies
of scale

Constant
returns
to scale

Figure 4.13 Regions of
the Long-Run Average
Cost Curve

The three segments of
the LAC curve are
• Economies of scale:

The long-run average
cost falls when output
increases

• Constant returns to
scale: The long-run
average cost does not
change when output
increases

• Diseconomies of scale:
The long-run average
cost rises when output
increases

M04_BLAI8235_01_SE_C04_pp138-185.indd 167 23/08/17 10:07 AM

168  CHAPTER 4 Production and Costs

operations, they gain the advantage of lower costs. If your firm lags behind the com-
petition and your rivals use their cost advantage to lower their prices, your outlook
can quickly become dire. In addition, if the source of economies of scale lies in the
utilization of specialized equipment, as a manager you must make certain that your
firm is using the specialized equipment appropriate to its scale of production.

Constant Returns to Scale
Eventually, economies of scale taper off and reach a region of the LAC curve with
constant returns to scale, such as at point B in Figure 4.13. For firms in many indus-
tries, the region with constant returns to scale is quite large. Some firms’ LAC curves
are effectively L-shaped: One segment has economies of scale and a second has per-
sisting constant returns to scale. Regression results for firms in a large variety of
industries show that their LAC curves have constant returns to scale. Paper mills,
insurance companies, and producers of glass containers, construction equipment,
and men’s footwear seem to have little in common, but their LAC curves all display
extended regions with constant returns to scale.

Managers of firms in industries producing in the region of constant returns to
scale need not fear that competitors will gain a cost advantage by increasing the
scale of their operations. They cannot relax completely, however, because they must
constantly be on the alert in order to minimize cost.

The Challenges of Diseconomies of Scale
With increases in scale come increases in complexity, bureaucracy, and the size of a
firm’s labor force. All of these factors may eventually cause the average cost to
increase when a firm increases production. As the firm becomes large and complex,
decision making suffers because information must be filtered through layers of man-
agement before a decision can be made and then communicated back through the
same channels before any action can be taken. As the bureaucracy builds and the
labor force increases in size, managers and workers have increasing opportunities to
focus on their own self-interest and office politics, rather than spending their time
advancing the firm’s interest. In the largest organizations, wasteful duplication of
effort can easily occur, with one group of managers and/or workers hard at work,
blissfully unaware that another group elsewhere in the firm is diligently working on
the same task. The slowdown and loss of quality in decisions, the pursuit of advance-
ment by engaging in office politics, and the growing likelihood of duplication of
effort all mean that as the firm increases its scale of production, its average cost rises.

Executives managing a firm that suffers from diseconomies of scale, such as a
firm at point C in Figure 4.13, face difficult decisions. To lower the firm’s costs, the
managers must decrease the scale of operations, creating a movement down along
its LAC curve to a scale of production with lower average cost. Decreasing produc-
tion means decreasing the amount of inputs. In the popular vernacular, the manag-
ers must downsize the firm. Downsizing is never easy because of the human cost
inflicted on the downsized workers, but at times, these decisions are necessary. In
some cases, the only way to assure the firm’s survival is to reduce its costs. Of
course, when decreasing inputs, the managers must be careful to follow the rules
you have learned about cost minimization.

Changes in the Long-Run Average Costs
In Section 4.3, you learned that a fall in the price of an input, a technological change,
and learning-by-doing lower a firm’s average total costs and thereby shift its short-
run ATC curve downward. Anything that shifts the short-run ATC curve also shifts

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4.4 Long-Run Cost  169

the LAC curve. For example, a fall in the price of an input decreases the short-run
average total cost and shifts the short-run ATC curves downward. It also decreases
the long-run average cost and shifts the LAC curve downward.

Changes in the price of inputs and changes in technology are likely to affect all
competitors’ costs more or less equally. Learning-by-doing, however, may result in
an important competitive advantage. As a manager, you must realize that accepting
an apparently unprofitable contract might actually wind up being profitable if it
enables your workers to learn by doing. Such a contract could lower your long-run
production costs below those of your competitors.

Long-Run Average Cost

In the table below, identify points on the firm’s LAC curve. Then graph the LAC curve.
Over what ranges of output are there economies of scale? Constant returns to scale?
Diseconomies of scale?

SOLVED
PROBLEM

2 Units of Capital 4 Units of Capital 6 Units of Capital 8 Units of Capital

Output,
Q

Average
Total Cost,

ATC

Output,
Q

Average
Total Cost,

ATC

Output,
Q

Average
Total Cost,

ATC

Output,
Q

Average
Total Cost,

ATC

5 $40 5 $60 5 $80 5 $100

10 20 10 30 10 50 10 70

15 15 15 10 15 25 15 50

20 20 20 15 20 9 20 30

25 40 25 35 25 5 25 15

30 70 30 60 30 20 30 5

35 110 35 90 35 40 35 15

40 160 40 130 40 80 40 30

Answer

2 Units of Capital 4 Units of Capital 6 Units of Capital 8 Units of Capital

Output, Q
Average

Total Cost,
ATC

Output,
Q

Average
Total Cost,

ATC

Output,
Q

Average
Total Cost,

ATC

Output,
Q

Average
Total Cost,

ATC

5 $40 5 $60 5 $80 5 $100

10 20 10 30 10 50 10 70

15 15 15 10 15 25 15 50

20 20 20 15 20 9 20 30

25 40 25 35 25 5 25 15

30 70 30 60 30 20 30 5

35 110 35 90 35 40 35 15

40 160 40 130 40 80 40 30

(Continues)

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170  CHAPTER 4 Production and Costs

Cost (dollars per unit)

Quantity (units)

$5

$10

$15

$20

$25

$30

$35

$40

$45

$50

5 10 15 20 25 30 35 40

LAC

450

The points on the LAC curve are in red in the table and are graphed in the figure, which
shows the LAC curve. For each quantity, these points have the lowest average total
cost. From 5 units to 25 units, there are economies of scale because the long-run aver-
age cost falls between these levels of output. There are constant returns to scale
between 25 units and 30 units because the long-run average cost is constant between
these levels of output. There are decreasing returns to scale after 30 units because the
long-run average cost rises after this quantity.

4.5 Using Production and Cost Theory
Learning Objective 4.5 Apply production and cost theory to make better
managerial decisions.

Costs serve as a fundamental factor in virtually every business decision you will
encounter in your career. Consequently, the material in this chapter serves as the
foundation for the economic models presented in many of the later chapters. Even
before you proceed to those chapters, some noteworthy lessons emerge that can be
extremely helpful in making decisions.

Effects of a Change in the Price of an Input
Suppose that you are a manager at a firm like Sticky’s Finger Joint, a fast-food
restaurant in New York specializing in unique, delicious chicken fingers. As an alert
manager, one of your goals is to minimize the impact of a change in input price on

MANAGERIAL
APPLICATION

SOLVED PROBLEM (continued)

M04_BLAI8235_01_SE_C04_pp138-185.indd 170 23/08/17 10:07 AM

4.5 Managerial Application: Using Production and Cost Theory  171

the cost of producing a given output. Recall the cost-minimization equation for two
inputs:

MPL
W =

MPK
R . The City of New York has passed regulations that will require the

minimum wage you pay your workers to rise, eventually reaching $15 per hour on
July 1, 2021. Suppose that the wage rate will rise from its current level—say, W—to a

higher level—say, W

. The increase in the wage rate changes the equality to
MPL
W
∼ 6

MPK
R .

Section 4.2 showed that with this inequality your restaurant can lower costs by using
less labor and more capital. More generally, according to the cost-minimization
equation, the marginal products of all inputs divided by their costs should be equal,
not just capital and labor. So when the cost of any variable input rises, cost-minimizing
managers decrease the quantity of that input and increase the quantities of the other
variable inputs to maintain the equality.

Of course, in the short run, it might be impossible for you to change the quantity
of capital, but in the long run, you can do so. Accordingly, you might decide to
decrease your order staff by creating self-order kiosks, where customers can use tab-
lets to order and pay for their items. Or you might cut back on the number of cooks
by purchasing fryers that automate more of the cooking process.

This general conclusion—that managers should decrease use of an input that
rises in cost and increase use of other inputs—probably does not come as a sur-
prise. The issue is determining the magnitude of the changes. Unfortunately, there
is no easy, cut-and-dried method to determine precisely how much to change the
inputs, but keep in mind the intuition behind the cost-minimization rule. In partic-
ular, you learned in Section 4.2 that cost minimization requires that the change in out-
put from spending one more dollar on one input must equal the changes in output
from spending one more dollar on the other inputs. When the price of an input
changes, ask yourself, “How much more output would I obtain if I spent one more
dollar on that input?” Then ask yourself the same question for another input.
Comparing the two answers will guide you to lower the total cost by using less of
the input that produces less output and more of the other input. If you continue to
make changes until your answers are all the same, you will have responded cor-
rectly to the change in the price of an input. Of course, the difficult part of this
procedure is determining the marginal products of the inputs. As a manager, you
may be forced to come up with educated estimates of the marginal products.
Thinking about how output changes when spending an additional dollar on an
input can help you refine your estimates. If you are working for a company with
research analysts, you may be able to call on them to use regression analysis
(explained in Section 3.1) to provide you with estimates of the marginal products.

Economies and Diseconomies of Scale
Suppose that you are an executive at a firm like Groupon, an online deal company
that offers to sell consumers discount coupons for different products if enough con-
sumers sign up for the deal. There is no simple, instantaneous way to determine
where on its LAC curve your firm is producing. However, you can infer whether it is
operating on the LAC curve where there are economies of scale or diseconomies of
scale by thinking about the short-run average total cost:

• Economies of scale. If your firm is producing at a point such as point A in
Figure 4.14, where the firm can lower the short-run average total cost by
increasing the scale of production—say, from 50,000 deals per year to
100,000—then you can infer that it is producing at a point on the LAC curve
with economies of scale.

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172  CHAPTER 4 Production and Costs

• Diseconomies of scale. If your firm is producing at a point such as point C in
Figure 4.14, where the short-run average total cost can be lowered by decreasing
the scale of production—say, from 450,000 deals per year to 400,000—you can
conclude that it is producing at a point on the LAC curve with diseconomies of
scale.

• Constant returns to scale. If your firm is producing at a point such as point B in
Figure 4.14, where you cannot decrease your short-run average total cost by
either increasing or decreasing the scale of production, you can deduce that the
firm is producing at a point with constant returns to scale.

Once you know the segment of the LAC curve on which your firm is operat-
ing—economies of scale, constant returns to scale, or diseconomies of scale—you
can make much better decisions than managers who either lack this information or
choose to ignore it. For example, if your firm is producing 450,000 deals per year at
point C on its LAC curve, you know that decisions designed to expand output
might fail. Because your firm is producing at a point with diseconomies of scale,
the expansion will raise its long-run average costs. Indeed, you may want to con-
tract your scale of business in order to lower your long-run average costs. If
instead your firm is producing 50,000 deals per year at point A, you should be
more inclined to make decisions that increase the scale of output. Because the firm
is producing at a point with economies of scale, the increase in production will
lower its long-run average costs. As it happens, initially Groupon was producing
at a point such as A because it expanded rapidly. But apparently its managers
expanded too much. Groupon wound up offering approximately 450,000 deals per
year, but Groupon’s executives then announced that they planned to reduce its
scale of operations and would cease operating in 12 countries, offering deals in
15 countries instead of 27.

Cost (dollars per deal o�ered)

Output (thousands of deals
o�ered per year)

$2.50

$5.00

$7.50

$10.00

$12.50

$15.00

$17.50

$25.00

$22.50

$20.00

500450400350300250200150100500

LAC

C

B

A

Economies
of scale

Diseconomies
of scale

Constant
returns
to scale

ATC4

ATC1
ATC7

Figure 4.14 Determining the Returns to Scale

A manager can determine if the firm is
producing at a point on its LAC curve with
economies of scale, constant returns to scale, or
diseconomies of scale by considering the effect
of a change in production on the short-run
average total cost.
• If increasing production lowers the short-run

average total cost (point A), then the firm is
producing at a point with economies of scale.

• If decreasing production lowers the short-run
average total cost (point C), then the firm is
producing at a point with diseconomies of
scale.

• If increasing or decreasing production does
not change the short-run average total cost
(point B), then the firm is producing at a point
with constant returns to scale.

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Revisiting How Pizza Hut Managers Learned That Size Matters  173

Revisiting How Pizza Hut Managers Learned That
Size Matters

At the beginning of the chapter, you read about a challenge facing managers at Pizza Hut: How could
they increase the number of stores and thereby boost
their profit? You can now apply the concepts of this
chapter to explain how those managers answered
that question.

The hypothetical data in Figure 4.15 show Pizza
Hut’s problem. Pizza Hut’s standard restaurants were
large and designed to feature both dine-in and delivery
services. In Figure 4.15, the average total cost curve
of these large stores is ATC0. For simplicity, assume
that ATC0 means Pizza Hut is operating where it has
constant returns to scale, but note that the results
would be the same if Pizza Hut was operating where
it had economies or diseconomies of scale. In
Figure 4.15, the lowest average total cost ($3 per
pizza) occurs at production of 700 pizzas per day on
ATC0. A delivery-only restaurant, however, sells fewer
pizzas—say, 350 per day. As the black dot on ATC0 at
the quantity of 350 pizzas shows, the average total
cost for a large restaurant that sells only 350 pizzas
per day is $8 per pizza, which is much too high to be
profitable.

Pizza Hut’s executive managers realized that they
needed to develop a new concept: a restaurant that
would have lower average total cost when producing
350 pizzas per day and would concentrate on home
delivery. Pizza Hut’s managers designed a smaller
store for delivery only, with no dine-in services. The
smaller store used less capital, less land, and fewer
other inputs. The new design was appropriate for a
smaller scale of production because the designers
planned a restaurant that would have lower average
total costs when producing fewer pizzas per day. The
smaller restaurant’s average total cost curve is ATC1
in Figure 4.15. Its average total cost when producing
350 pizzas per day is only $3 per pizza, a cost that
would enable franchisees to make a profit selling

350 pizzas. After Pizza Hut began offering this new concept,
the franchisees gobbled them up: The number of Pizza Hut
restaurants stopped decreasing and started to increase,
thereby increasing Pizza Hut’s profit.

Cost (dollars per pizza)

Output (pizzas per day)

$1.00

$2.00

$3.00

$4.00

$5.00

$6.00

$7.00

$8.00

$9.00

$10.00

1,0009008007006005004003002001000

ATC1 ATC0

LAC

Figure 4.15 Determining the Returns to Scale for Pizza Hut

Pizza Hut designs its large restaurants to support both home
delivery and dine-in services, which requires producing and
selling 700 pizzas per day. The average total cost curve for a
large restaurant is ATC0, so the average total cost of 700
pizzas is $3.00. A restaurant that provides delivery only sells
a smaller number of pizzas—say, 350 per day. Along ATC0,
the average total cost of producing 350 pizzas per day is
$8.00. Pizza Hut’s managers designed a smaller restaurant
optimized to sell only 350 pizzas. The smaller restaurant has
average total cost curve ATC1 and an average total cost of
only $3.00 for 350 pizzas.

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174  CHAPTER 4 Production and Costs

Summary: The Bottom Line
4.1 Production
• The production function is the relationship between

different amounts of a firm’s inputs and the maximum
quantity of output it can produce with those inputs.

• The short run is the period of time during which at
least one input is fixed, so that a firm cannot vary the
amount of that input. The long run is a period of time
long enough that no input is fixed, allowing a firm to
vary the amounts of all the inputs it uses.

• The marginal product of an input is the change in out-
put that results from changing the input by one unit
while keeping other inputs constant.

4.2 Cost Minimization
• The cost-minimization rule shows that costs are mini-

mized when managers use the combination of inputs
that produces the desired quantity of output and for

which
MP1
P1

=
MP2
P2

=
MP3
P3

= c .

4.3 Short-Run Cost
• The total cost (TC) is equal to the fixed cost (FC) plus

the variable cost (VC): TC = FC + VC.
• The average fixed cost (AFC) equals the fixed cost divided

by the output (Q): AFC = FC>Q. The average variable
cost (AVC) equals the variable cost divided by the out-
put: AVC = VC>Q. The average total cost (ATC) equals
the total cost divided by the output: ATC = TC>Q.

• The marginal cost (MC) equals the change in total cost
divided by the change in output: MC = ∆TC>∆Q.

• Both the ATC curve and the AVC curve are U-shaped.
The MC curve intersects the minimum points on the
AVC and ATC curves.

• Changes in the prices of inputs and changes in tech-
nology alter the costs and shift the cost curves.

4.4 Long-Run Cost
• The long-run average cost (LAC) is the minimum aver-

age cost of producing any given quantity of output
when all inputs can be changed. The LAC curve is
U-shaped.

• If increasing output lowers a firm’s LAC, the firm has
economies of scale, and the LAC curve is downward
sloping. If the firm’s long-run average cost does not
change as output increases, the firm has constant returns
to scale, and its LAC curve is horizontal. If increasing
output raises a firm’s LAC, the firm has diseconomies of
scale, and the LAC curve is upward sloping.

4.5 Managerial Application: Using
Production and Cost Theory

• If the price of an input changes, you can use the
cost-minimization rule to adjust the quantity of inputs
and lower your costs.

• If you are producing at a point on the LAC and an
increase in output lowers short-run average total cost,
your firm is operating in a region with economies of
scale. If you are producing at a point on the LAC and a
decrease in output lowers short-run average total cost,
your firm is operating in a region with diseconomies of
scale. If you are producing at a point on your LAC and
your firm cannot lower its average total cost by either
increasing or decreasing its production, it is operating
in a region with constant returns to scale.

• If your firm is operating on its LAC curve in a region
with increasing returns to scale, you can decrease its
average cost by increasing production.

• If your firm is operating on its LAC curve in a region
with decreasing returns to scale, you can decrease its
average cost by decreasing production.

Key Terms and Concepts
Average fixed cost

Average total cost

Average variable cost

Constant returns to scale

Decreasing marginal returns to labor

Diseconomies of scale

Diseconomies of scope

Economies of scale

Economies of scope

Fixed cost

Increasing marginal returns to labor

Long run

Long-run average cost

Long-run marginal cost

Marginal cost

Marginal product

Marginal product of labor

Negative marginal returns to labor

Production function

Short run

Total cost

Variable cost

M04_BLAI8235_01_SE_C04_pp138-185.indd 174 23/08/17 10:07 AM

Questions and Problems

4.1 Production
Learning Objective 4.1 Explain the relation-
ship between a firm’s inputs and its output
as well as calculate the marginal product of
an input.

1.1 What is the difference between the short run and
the long run? As a manager producing 3,000
units of output, if you can lower your cost, will
you be able to lower it more in the short run or
the long run? Explain your answer.

1.2 As a manager, how would you expect the mar-
ginal product of labor to change as you hire
more workers?

1.3 “A firm will never find it optimal to employ so
much of an input that its marginal product is
negative.” Is this statement true or false? Explain
your answer.

1.4 A technological change increases the amount of
output that a firm can produce from a given
quantity of inputs. It increases the marginal
product of labor for each quantity of labor and
shifts the marginal product of labor curve
upward. How does this technological change
affect the marginal product of capital?

4.2 Cost Minimization
Learning Objective 4.2 Use the cost-
minimization rule to choose the combination
of inputs that produces a given quantity
of output at the lowest cost.

2.1 The production of ABC, Inc.’s output requires
only two inputs. Its manager says, “Because the
two input prices are equal, to minimize cost I
employ equal quantities of the two inputs.” Is
the manager correct? Explain your answer.

2.2 The wage rate of high-skilled labor is $40 per
hour, and the wage rate of low-skilled labor is
$15 per hour. The marginal product of high-
skilled labor is 60 units per hour, and the mar-
ginal product of low-skilled labor is 15 units per
day. Is a firm operating under these conditions
minimizing its cost? If not, what should the firm
do? Explain your answers.

2.3 As a production manager, your job depends on
your ability to minimize the cost of production.
You hire a consulting firm, and its report sug-
gests that you have plenty to worry about: The

cost of capital is $200 per hour, the wage paid
to your workers is $16 per hour, the marginal
product of capital is 10 units per hour, and the
marginal product of labor is 32 units per hour.
What is the consulting firm going to recom-
mend, and why?

2.4 You are an executive for a firm like VCA Antech,
which operates over 600 animal hospitals in the
United States. Each hospital is treating the desired
number of cases per day. At each hospital, you
estimate that hiring another veterinarian enables
the location to treat 20 additional cases per day
and firing one decreases the number of cases
treated by 20 per day. Hiring another veterinary
assistant enables the location to treat 10 more cases
per day, and firing one decreases the number of
cases treated by 10 per day. Finally, hiring another
veterinary technician enables the location to treat
15 more cases per day, and firing one decreases the
number of cases treated by 15 per day. A veterinar-
ian is paid $300 per day, a veterinary assistant is
paid $100 per day, and a veterinary technician is
paid $150 per day. Are your hospitals minimizing
the cost of treatment? If so, explain why. If not,
identify the change(s) that you should make.

2.5 As a manager for a nonprofit like Doctors With-
out Borders, you are charged with determining
what supplies to send to South Sudan. You can
send different boxes of medicine. The marginal
product is the number of lives saved. Suppose
that the cost of a box of medicine to treat cere-
bral malaria is $40 and will save 10 lives. The
cost of a box of medicine to treat diarrhea is $60
and will save 20 lives. Which box will you ship
first? Explain your answer.

2.6 Suppose that your manufacturing firm has the
following production function with three inputs:

Q = F1X1, X2, X32
where X1, X2, and X3 are the three inputs. As

a manager, how will you determine the cost-
minimizing quantities of X1 and X2 if the quantity
of X3 is fixed?

4.3 Short-Run Cost
Learning Objective 4.3 Distinguish between
fixed cost and variable cost and calculate
average total cost, average variable cost,
average fixed cost, and marginal cost.

Questions and Problems  175

M04_BLAI8235_01_SE_C04_pp138-185.indd 175 23/08/17 10:07 AM

176  CHAPTER 4 Production and Costs

3.2 Why is a firm’s short-run average total cost
curve typically U-shaped?

3.3 How does marginal cost differ from average
total cost?

3.4 As a manager, you know that as your firm uses
more of a variable input, the marginal product
of the input decreases. What conclusion can you
draw about the behavior of the marginal cost
curve?

3.5 What is the competitive return for the resources
the owners provide? Why is it included as part
of a firm’s costs?

3.6 Quick-service restaurants like Burger King (also
called fast-food restaurants) typically employ
many minimum wage workers. If the govern-
ment raises the minimum wage, what happens
to a Burger King’s cost curves?

3.7 Clerical workers form a union that successfully
raises its members’ wages. What happens to the
short-run average total cost curve and long-run
average cost curve of a firm that hires clerical
workers? What happens to the firm’s marginal
costs?

3.8 Energizer Holdings initially produced only its
namesake batteries. Over the years, it acquired

other divisions that produced personal care
products such as razors (Schick) and sunscreen
(Hawaiian Tropic and Banana Boat). The execu-
tives at Energizer Holdings decided that they
would split the company into two independent
firms, one producing batteries and the other the
personal care products, because they thought
the split would lower the two firms’ costs.
Using the concepts presented in this chapter,
explain the executives’ reasoning.

3.9 Apple Inc.’s research and development for its
iPhone eventually helped the firm develop its
first iPad. How did Apple’s production of iPads
affect its costs?

4.4 Long-Run Cost
Learning Objective 4.4 Derive the long-run
average cost curve and explain its shape.

4.1 Explain the relationship between the short-run
average total cost and the long-run average cost.
Include a figure in your answer.

4.2 The table shows production data for three
quantities of capital. Suppose that each unit
of capital costs $1,000 and each unit of labor
costs $200.

3.1 Assuming that all units of labor are paid the
same wage rate, complete the table below.

Labor, L Capital, K Output, Q
Average

Total
Cost, ATC

Capital, K Output, Q
Average

Total Cost
ATC,

Capital, K Output, Q
Average

Total
Cost, ATC

0 2 0 X 3 0 X 4 0 X

1 2 100 3 160 4 210

2 2 800 3 1,200 4 1,350

3 2 1,300 3 1,800 4 2,200

4 2 1,475 3 2,100 4 2,600

5 2 1,500 3 2,200 4 2,700

6 2 1,510 3 2,220 4 2,710

Capital, K Labor, L Output, Q
Fixed

Cost, FC
Variable
Cost, VC

Total
Cost, TC

Average
Fixed

Cost, AFC

Average
Variable

Cost, AVC

Average
total cost,

ATC

Marginal
Cost, MC

2 0 0 $400 X X X

2 1 100 $400

2 2 800

2 3 1,200

2 4 1,500

2 5 1,700

2 6 1,800

M04_BLAI8235_01_SE_C04_pp138-185.indd 176 23/08/17 10:07 AM

a. Complete the table.
b. If you estimate that your production will be

1,300 units, how much capital do you want
to use?

c. If you estimate that your production will be
2,100 units, how much capital do you want
to use?

d. Over what approximate range of production
would you use 2 units of capital? Explain
your answer.

4.3 If doubling all inputs increases output by 70 per-
cent, what can you conclude about the shape of
the long-run average cost curve?

4.4 Your company has a long-run average cost curve
that has a range of output with economies of scale,
followed by a range with constant returns to scale,
and then followed by a range with diseconomies
of scale. You know that you are producing at a
point where you have constant returns to scale.
You want to lower your average cost. Can you do
so by increasing your output by using more labor?
By using more capital? By using more labor and
more capital? Explain your answers.

4.5 Suppose that the only inputs your company
uses are labor and capital.
a. Explain how it is possible to simultaneously

have negative marginal returns to labor and
increasing returns to scale.

b. As a manager in this situation, what changes
would you make to minimize your average
total cost in the short run?

c. What changes would you make to minimize
your average total cost in the long run?

4.5 Managerial Application: Using
Production and Cost Theory
Learning Objective 4.5 Apply production
and cost theory to make better managerial
decisions.

5.1 A firm uses only labor (L) and capital (K) as
inputs and is minimizing the cost of producing
Q1 units of output by using L1 worth of labor
and K1 worth of capital. How should the firm
respond to an increase in the price of capital? Be
sure to explain your answers for both the short
run and the long run.

5.2 A large architectural firm has just landed a con-
tract to build a hospital. Eight architects currently
work 40 hours per week in this firm, and all are
available to work full-time on this project. The
managers estimate that they need 400 archi-
tect-hours per week for 20 weeks to complete this
project. Architects earn $500 per 40-hour week.
Suppose that there is a fixed cost of hiring an
architect of $2,000. (This cost reflects the advertis-
ing costs, interviewing costs, and so forth.)
a. The firm’s current architects are willing to

work overtime to complete this project if
they receive 1.5 times their usual wage rate
for any hours in excess of 40 hours per week.
How much would the managers pay in
overtime wages for the project?

b. Alternatively, the firm can handle this proj-
ect by hiring new workers (for 20 weeks
only) and having all architects work 40 hours
per week. How many new architects would
the firm need to hire?

c. Should the managers hire new architects or
ask the firm’s current architects to work
overtime? Explain your answer.

5.3 Suppose that the government offers to pay a
firm that hires low-skilled labor a subsidy. In
particular, for each low-skilled worker hired, the
government will pay a part of the wage rate.
How would this program affect the firm’s hiring
decisions?

5.4 The Monroe County Public Defender’s Office in
New York has a budget of approximately $8 mil-
lion and employs nearly 70 attorneys and 25 staff
people. The courts have imposed new require-
ments for representation: Indigent people must
now be represented at their first hearing. The
Public Defender has given you the task of deter-
mining how many new attorneys to hire while
simultaneously minimizing the cost. Suppose
that you can hire Special Assistant Public
Defenders at a salary of $12,000 per month,
Senior Assistant Public Defenders at a salary of
$10,000 per month, and Assistant Public Defend-
ers at a salary of $6,000 per month. You know
that you will need to provide representation for
700 new cases per month. The precceding table
shows how many cases each class of attorney can

Questions and Problems  177

Special Assistant
Public Defender

Additional Cases
Handled

(per month)

Senior Assistant
Public Defender

Additional Cases
Handled

(per month)

Assistant Public
Defender

Additional Cases
Handled

(per month)

1 240 1 200 1 140

2 200 2 160 2 120

3 160 3 110 3 60

Accompanies problem 5.4.

M04_BLAI8235_01_SE_C04_pp138-185.indd 177 23/08/17 10:07 AM

178  CHAPTER 4 Production and Costs

handle. How many Special Assistant, Senior
Assistant, and Assistant Public Defenders will
you hire? Explain your answer.

long-term, fixed-price contract for your product
that would significantly increase the size of your
firm. If you sign the contract and do not expect the
prices of your inputs to change, do you think your
profit will be larger in the short run or the long run?

MyLab Economics Auto-Graded Excel Projects
4.1 Cakes by Monica (a bakery under the umbrella

of the Café Brulé restaurant) in Vermillion, SD,
makes cupcakes for customers to purchase both
in the store and in bulk orders for birthday par-
ties and weddings.
Suppose that in the short run Cakes by Monica
has a fixed amount of capital but can easily hire
college students from the University of South
Dakota to increase production as needed. A pro-
duction schedule is provided for you where Q is
dozens of cupcakes.
a. Using the schedule provided, calculate the

marginal product of labor when K = 3.
b. Using your calculations, for which workers

are there increasing, decreasing, and nega-
tive marginal returns to labor?

c. Suppose Cakes by Monica decides to add
another unit of capital in the long run. Find
the marginal product of the 4th unit of capi-
tal and the marginal product of labor when
K = 4.

d. Create a graph of the marginal product of
labor for K = 3 and K = 4.

e. Using your graph and the data, how does
the addition of another unit of capital affect
the productivity of labor?

4.2 Sugar Plum Oak is a company based in Norfolk,
NE, that produces handmade Amish furniture.
One of its signature items is handmade rocking
chairs. The table provides weekly cost data for
handmade rocking chairs.
a. Using the total cost schedule provided, calcu-

late total and average fixed cost and variable
cost, average total cost, and marginal cost.

b. Use Excel to graph the ATC, AVC, and MC
curves. What does the distance between the
ATC and AVC curves represent?

c. Using the same graph, where does the MC
curve intersect the ATC curve? What does this
point mean to the firm from a cost perspective?

Accompanies problem 4.1.

5.5 Your company is producing at a point on its long-
run average cost curve with economies of scale. As
a manager, you have the opportunity to sign a

M04_BLAI8235_01_SE_C04_pp138-185.indd 178 23/08/17 10:07 AM

179

CHAPTER 4 APPENDIX

Demonstrating some of the production and cost results discussed in the chapter using calculus
can help reinforce your understanding. We start with the definition of marginal product.

A. Marginal Product
You have learned that the marginal product of an input is the change in total output that
results from changing the input by one unit while keeping other inputs constant. As you will
see in many of these appendices, all “marginal” concepts have calculus interpretations that
revolve around “changes,” and marginal product is no exception. If a firm’s production func-
tion is Q = f1L, K2, where Q is the quantity produced, L is labor input, K is capital input, and
f is the function that relates the inputs to the output, then the marginal product of labor is
equal to

MPL =
0f1L, K2

0L
A4.1

and the marginal product of capital is equal to

MPK =
0f1L, K2

0K
A4.2

In both cases, we take the partial derivative because the production function depends on more
than one variable and the concept of marginal product studies the change in output that
results from changing one input while keeping the others constant. In this case, the variables
are the inputs labor and capital.

Equations A4.1 and A4.2 use a general specification for the production function. Often
economists use a specific production function—in, particular, Q = ALaKb. This production
function is called a Cobb–Douglas production function after the first two researchers to use it.
In it, A, a, and b are parameters that determine some of the properties of the production func-
tion. A is a scale parameter because it has a direct effect on the quantity produced. a and b are
both less than one and influence the relative importance of labor and capital in production.
Using the power rule to take the partial derivative of the Cobb–Douglas production function
with respect to labor, the marginal product of labor equals

MPL = aAL
a – 1Kb

and taking the partial derivative with respect to capital, the marginal product of capital is
equal to

MPK = bAL
aKb-1

To explore the Cobb–Douglas production function in more detail, we can specify some
values for the A, a, and b parameters and then observe how the marginal product of labor
changes when labor changes and when capital changes. Figure A4.1 shows two MPL curves
for A = 50, a = 0.7, and b = 0.3 for two levels of capital: K = 4 and K = 6. These curves
show that the Cobb–Douglas production function misses the region with increasing mar-
ginal returns to labor because the MPL curves always slope downward. They also, however,
demonstrate that when the quantity of capital increases, the MPL curve shifts upward,
which means that for any quantity of labor, the marginal product of labor is larger with
more capital.

The Calculus of Cost

M04_BLAI8235_01_SE_C04_pp138-185.indd 179 23/08/17 10:07 AM

You can check that the MPK curves are similar: They always slope downward as capital
increases, and they shift up when labor increases.

B. Cost Minimization
The marginal products of labor and capital play an important role in minimizing the total cost
of producing a given quantity of output. Suppose that the firm produces a fixed amount
of output, Q. The production function, Q = f1L, K2, shows that any number of combinations of
labor and capital can be used to produce this quantity of output. The firm’s managers, of
course, want to use the combination of labor and capital that minimizes the firm’s cost. Sup-
pose that the cost of employing a worker is W and the cost of using a unit of capital is R. Then
the firm’s total cost is TC = 1W * L2 + 1R * K2. Formally, the firm’s managers face this
problem:

Min TC = 1W * L2 + 1R * K2 subject to Q = f1L, K2
This constrained minimization problem can be solved using calculus and a Lagrange

multiplier. Alternatively, we can also solve the problem using a figure. To use a figure, let’s
start by determining the different combinations of labor and capital that produce Q—that is,
the different combinations of L and K such that f1L, K2 = Q. For production to stay at Q, an
increase in one input must be offset by a decrease in the other. For example, using the Cobb–
Douglas production function with the parameters featured in Figure A4.1, when L = 2 work-
ers and K = 4 units, output is 123.1 Then if labor increases to 3 workers, to keep output equal
to 123 capital must decrease to 1.55 units. Economists call the curve showing the combinations
of inputs, labor and capital, that keep output at a fixed amount an isoquant.

Labor, L
(workers)

MPL, for K = 4 MPL, for K = 6

1 53 60

2 43 49

3 38 43

4 35 40

5 33 37

Figure A4.1 The Marginal Product of Labor for a Cobb–Douglas Production Function

The marginal products of labor are from the Cobb–Douglas production function, Q = 50L0.7K 0.3. The first
column of marginal products has K = 4, and the second has K = 6. As labor increases, the marginal product of
labor decreases. And as capital increases, the MPL curve shifts upward.

Marginal product of labor
(units per worker)

Labor (number of workers)
6531 42

$30

$40

$50

$60

$70

$80

0

MP L (K 5 6)

MP L (K 5 4)

1 The output rounds to 123; more precisely, it is 123.11.

180  CHAPTER 4 APPENDIX The Calculus of Cost

M04_BLAI8235_01_SE_C04_pp138-185.indd 180 15/09/17 2:49 PM

Figure A4.2 illustrates an isoquant for a general production function, not necessarily
Cobb–Douglas. This isoquant shows the combinations of labor, L, and capital, K, that produce
20 units of output, f1L, K2 = 20. Though the figure shows only the isoquant for producing 20
units of output, there are isoquants for each possible level of production.

We can calculate the slope of an isoquant, dK>dL, by taking the total differential of
f1L, K2 = 20:

a
0f
0L

* dLb + a
0f
0K

* dKb = 0 A4.3

In Equation A4.3,
0f
0L

is the marginal product of labor, MPL, and
0f
0K

is the marginal product of

capital, MPK. Using these definitions in Equation A4.3 gives

1MPL * dL2 + 1MPK * dK2 = 0 A4.4
We can rearrange Equation A4.4 to give

dK
dL

= –
MPL
MPK

A4.5

Equation A4.5 shows that the magnitude of the slope of the isoquant equals the marginal
product of labor divided by the marginal product of capital. This result explains the convex
shape of the isoquant in Figure A4.2. Moving down the isoquant, the quantity of labor
increases and the quantity of capital decreases, so that the marginal product of labor decreases
and the marginal product of capital increases. Equation A4.5 shows that these changes in the
marginal products decrease the magnitude of the isoquant’s slope, so that the isoquant
becomes flatter as labor increases and capital decreases.

The isoquant in Figure A4.2 shows the combinations of labor and capital that produce 20
units of output. To find the least costly combination, we need to introduce the cost function,
TC = 1W * L2 + 1R * K2. Economists call the line showing the combinations of labor and
capital that keep the cost at a fixed amount an isocost. For example, if W = $30, R = $20, and
TC = $90, then L = 1 worker and K = 3 units and also L = 2 workers and K = 1.5 units
both have a total cost of $90. Consequently, these two combinations of labor and capital fall on
the isocost line for W = $30, R = $20, and TC = $90. Figure A4.3 illustrates this isocost line
and two others for the same labor and capital cost but total costs of $120 and $150.

Capital (units)

Labor (number of workers)
6531 42

1

2

3

4

5

6

7

8

0

Q 5 20

Figure A4.2 An Isoquant

The isoquant in the figure shows
the different combinations of
capital and labor that produce
20 units of output. The magnitude
of the slope of the isoquant equals
the marginal product of labor
divided by the marginal product
of capital, or MPL /MPK.

CHAPTER 4 APPENDIX The Calculus of Cost  181

M04_BLAI8235_01_SE_C04_pp138-185.indd 181 23/08/17 10:07 AM

The isocosts in the figure are straight lines. We can check this result by calculating the
slope of an isocost, dK/dL. Take the total differential of TC = 1W * L2 + 1R * K2:

dTC = 1W * dL2 + 1R * dK2
Because the total cost is constant, dTC = 0. So, solving for the slope of the isocost, dK>dL,
gives

dK
dL

= –
W
R

This equation shows that the magnitude of the slope of an isocost line is equal to the wage rate
divided by the cost of a unit of capital. Because the slope equals – W>R, it is the same at every
point on the isocost line, which means that the isocost is a straight line. This value for the
slope also shows that the isocost line will rotate and change its slope if the wage rate or cost of
capital changes. If the total cost rises—say, from $90 to $120 to $150—then, as illustrated in
Figure A4.3, the isocost line shifts outward, and its slope does not change.

Suppose that the managers’ goal is to produce 20 units of output using the minimum-cost
combination of labor and capital. Further assume that the isoquant in Figure A4.2 is the rele-
vant isoquant and that W = $30 and R = $20, so the isocost lines in Figure A4.3 are relevant.
Then Figure A4.4 shows that the cost-minimizing combination of labor and capital is 2 work-
ers and 3 units of capital. This combination of labor and capital is on the isoquant for 20 units
of output and is on the lowest isocost line that touches the isoquant. Isocost lines with lower
total costs, such as Isocost$90, do not touch the isoquant because they do not buy enough
inputs to produce the 20 units of output. Isocost lines with higher total costs, such as
Isocost$120, cross the isoquant at two points and so buy enough inputs to produce 20 units of
output, but because the goal is to minimize total costs, they are not optimal.

Figure A4.4 shows that at the cost-minimizing combination of inputs, the isoquant is tan-
gent to the isocost, so their slopes are equal. In terms of an equation, this result means that at
the cost-minimizing combination of inputs


MPL
MPK

= –
W
R

A4.6

Capital (units)

Labor (number of workers)

6531 42

1

2

3

4

5

6

7

8

0

Isocost$120

Isocost$150

Isocost $90

Figure A4.3 Isocost Lines

Isocost$90 shows the different
combinations of capital and labor
that have a total cost of $90 when
the wage rate is $30 and the cost
of a unit of capital is $20.
Isocost$120 shows the different
combinations of capital and labor
that have a total cost of $120
with the same costs per unit as
before for labor and capital. The
magnitude of the slope of the
isocost equals the wage rate
divided by the cost of capital, or
W/R.

182  CHAPTER 4 APPENDIX The Calculus of Cost

M04_BLAI8235_01_SE_C04_pp138-185.indd 182 23/08/17 10:07 AM

In Equation 4.6, multiply both sides by −1 (to remove the annoying negative sign from the
equality), and then divide both sides by W and multiply by MPK. So doing gives the cost-
minimizing condition as

MPL
W

=
MPK

R

which is exactly the same result as the cost-minimization rule presented in the chapter. More
generally, just as demonstrated in Equation 4.1 in the chapter, to minimize the cost of produc-
tion managers must employ the quantity of inputs such that

MP1
P1

=
MP2
P2

=
MP3
P3

= …
MPn
Pn

where MP1 is the marginal product of the first input and P1 is the price of the first input, MP2
is the marginal product of the second input and P2 is the price of the second input, and so on.

Because the cost-minimization conditions are the same in the chapter and here, so, too,
are the implications. For example, as the price of an input rises, to minimize costs managers
should decrease their use of the higher-cost input and use more of the relatively lower-cost
input(s).

C. Marginal Cost and the Marginal/Average Relationship
Chapter 4 has one last, very important marginal concept: marginal cost. Once managers have
selected the cost-minimizing combination of inputs, the firm’s total cost then becomes a func-
tion of the quantity produced–that is, TC(Q). The firm’s marginal cost then equals the deriva-
tive with respect to the quantity, or

MC =
dTC
dQ

A4.7

We can use the definition of the marginal cost to demonstrate that when the average total
cost is at its minimum, the marginal cost equals the average total cost. Start with the definition

ATC = TCQ . Then average total cost is at its minimum when
dATC

dQ equals zero. Accordingly,

applying the quotient rule for differentiation,

Capital (units)

Labor (number of workers)

6531 42

1

2

3

4

5

6

7

8

0

Isocost$120

Isocost$150

Isocost $90
Q 5 20

Figure A4.4 Cost-Minimizing
Combination of Inputs

To produce 20 units of output,
the cost-minimizing combination
of labor and capital is 2 workers
and 3 units of capital because
this combination is on the lowest
isocost that touches the isoquant
for 20 units of output.

CHAPTER 4 APPENDIX The Calculus of Cost  183

M04_BLAI8235_01_SE_C04_pp138-185.indd 183 23/08/17 10:07 AM

dATC

dQ
=

da TC
Q

b
dQ

=
aQ * dTC

dQ
b – 1TC2

Q2
= 0 A4.8

The term after the second equal sign follows by taking the derivative of the fraction TCQ . When
taking this derivative, recall that total cost is a function of the quantity, TC1Q2.

For Equation A4.8 to equal zero, the numerator of the fraction, 1Q * dTCdQ 2 – 1TC2, must
equal zero, which means

aQ * dTC
dQ

b – 1TC2 = 0 A4.9

In Equation A4.9, divide both terms by Q and recall that dTCdQ = MC to obtain

MC – a TC
Q

b = 0 A4.10

Finally, use the definition of ATC as TC>Q to get
MC – ATC = 0 1 MC = ATC

This last equation shows the desired result: When the derivative of the average total cost
equals zero, so that the average total cost is at its minimum, the marginal cost equals the aver-
age total cost; that is, MC = ATC.

Calculus Questions and Problems
A4.1 Suppose that blueberries are produced using land

and labor according to the following production
function:

Q = L1 + 0.5L
0.5
2

where Q is the number of tons of blueberries har-
vested, L1 is the number of acres of blueberry fields,
and L2 is the number of labor-hours hired.
a. What is the marginal product of land, MP1?

What is the marginal product of labor, MP2?
b. What is the slope of the isoquant curve,

dL2>dL1?
c. Suppose that the price of using an acre of land

is W1 = $144 and the price of an hour of labor
is W2 = $9. What is the slope of the isocost line,
dL2>dL1?

d. If the price of using an acre of land is W1 = $144
and the price of an hour of labor is W2 = $9,
what is the cheapest combination of land and
labor that a firm could employ to produce 5
tons of blueberries?

e. Suppose that the price of land changes so that
the price of using an acre of land is W1 = $216
and the price of an hour of labor is W2 = $9.
What is the slope of the isocost line?

f. If the new price of land is W1 = $216 and the
price of an hour of labor is W2 = $9, what is
the cheapest combination of land and labor
that a firm could employ to produce 5 tons of
blueberries?

A4.2 Suppose that the total cost of producing a business
law handbook is

TC1Q2 = 10,000 + 25Q2 – 10Q
where Q is the total number of handbooks

produced.
a. What is the equation for the average total cost

of producing handbooks as a function of the
quantity of handbooks produced?

b. At what quantity, Q*, is the average total cost of
producing a handbook minimized? What is the
value of the average total cost at Q*?

c. At the quantity Q* that you identified in part b,
what is the marginal cost of an additional
handbook?

A4.3 Train locomotives are produced using labor and capi-
tal. The quantities of these inputs that a firm employs
determine the number of locomotives that the firm
can produce. Thomas’s Trains produces locomotives
according to the following production function:

Q = ln1L2 + 2ln1K2
where ln is the natural logarithm, Q is the quantity

of locomotives produced, and L and K are the quan-
tities of labor and capital employed, respectively.
The price of one unit of labor is wL = $10, and the
price of one unit of capital is rK = $60.
a. Using the production function given above,

what is the slope of the isoquant curve, dK>dL?

184  CHAPTER 4 APPENDIX The Calculus of Cost

M04_BLAI8235_01_SE_C04_pp138-185.indd 184 23/08/17 10:07 AM

b. What is the slope of the isocost line, dK>dL?
c. The specific production function above means

that Thomas’s Trains will always use a specific
capital-to-labor ratio, K>L. Based on your
answers to parts a and b, what is the value of
this capital-to-labor ratio?

A4.4 Rose’s Roses is a local flower shop specializing in
rose bouquets for weddings. Rose can produce her
magnificent bouquets using roses imported from
Colombia or roses imported from Ecuador. Due to
altitude and Ecuador’s location on the equator, the
Ecuadorean roses are slightly larger, meaning Rose
needs fewer of them to produce each bouquet. Rose
produces her bouquets according to the following
production function:

Q = 0.1RC + 0.125RE

where Q is the quantity of bouquets produced and
RC and RE are the quantities of Colombian roses
and Ecuadorian roses used, respectively. The price
of a Colombian rose is PC = $0.45, and the price of
an Ecuadorian rose is PE = $0.45.
a. Referring to the production function given

above, what is the slope of the isoquant line,
dRE>dRC?

b. What is the slope of the isocost line, dRE>dRC?
c. Based on your answers to parts a and b, how

many Colombian roses and how many Ecua-
dorian roses will Rose use in each of her mag-
nificent bouquets?

A4.5 Victoria Vineyards is an American wine producer,
specializing in premium red blends (red wines that
use multiple different varieties of grapes). Victoria
Vineyards’ total cost of producing its famous red
blend is

TC1Q2 = 200,000 + 5Q2 − 100Q
where Q is the quantity of cases Victoria Vineyards

produces.
a. What is Victoria Vineyards’ marginal cost equa-

tion, MC, of producing one case of its premium
red blend?

b. What is Victoria Vineyards’ average total cost
equation, ATC, of producing one case of its pre-
mium red blend?

c. Identify the range of quantities over which
MC 6 ATC.

d. Identify the quantity range over which the
slope of ATC is negative; that is, dATCdQ 6 0.

CHAPTER 4 APPENDIX The Calculus of Cost  185

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5

186

Burger King Managers Decide to Let Chickens Have It Their Way

Executives at the nation’s major restaurants realize that American consumers are clamoring for more natural
food, such as cage-free eggs. Caged chickens live in small
spaces that prevent them from standing or stretching their
wings. Cage-free chickens, on the other hand, are free to
roam the barn and engage in roosting, foraging, and nest-
ing. However, only about 10 percent of hens raised in the
United States are cage-free.

Farmers who raise cage-free chickens are part of a per-
fectly competitive industry. One farmer’s cage-free egg is a
perfect substitute for any other farmer’s cage-free egg, and
entry into the industry is cheap. The increased consumer
demand for cage-free eggs, however, is a relatively recent
change. Consequently, the farms producing cage-free eggs
are small compared to the farms producing eggs from

caged hens. Eggs produced by cage-free chickens are more
expensive than eggs produced by caged chickens due to
differences in costs. For example, raising cage-free chickens
requires farmers to employ more labor, and the mortality of
cage-free chickens is approximately twice that of caged birds.

The executives at Restaurant Brands International’s
Burger King division have been paying attention to con-
sumers’ changing preferences. In 2016, these executives
announced that Burger King would immediately start using
some cage-free eggs and would switch to 100 percent cage-
free by 2025. Why did Burger King’s managers decide to give
themselves nine years to make this switch? Why didn’t they
announce a more rapid changeover? This chapter explains
how the adjustments that occur in perfectly competitive mar-
kets shaped the decision made by Burger King’s managers.

Sources: Gregory Barber, “Are Cage-Free Eggs All They’re Cracked Up to Be?” Mother Jones, February 10, 2016,
http://www.motherjones.com/blue-marble/2016/02/corporations-are-going-cage-free-whats-next-hens; Jennifer
Chaussee, “The Insanely Complicated Logistics of Cage-Free Eggs for All,” Wired, January 25, 2016, http://www
.wired.com/2016/01/the-insanely-complicated-logistics-of-cage-free-eggs-for-all/.

Perfect Competition

Learning Objectives
After studying this chapter, you will be able to:

5.1 Summarize the conditions that make a market perfectly competitive.
5.2 Use marginal analysis to determine the profit-maximizing quantity that a perfectly

competitive firm produces in the short run.
5.3 Describe the long-run adjustments that managers in perfectly competitive markets make

to maximize profit.
5.4 Apply the theory of perfectly competitive firms and markets to help make better

managerial decisions.

C
H

A
P

T
E

R

Introduction
In Chapter 4, you learned how managers minimize costs when producing the desired
quantity of output. The profit-maximizing quantity of a good or service depends on
the extent of competition the firm faces. The amount of competition varies in different
markets. Happy Jack’s Maple Syrup is one of several thousand maple syrup producers
in North America. In contrast, PepsiCo is one of only two dominant soda producers in
the world. This chapter and the next three describe five market structures that differ
in the extent of competition. Table 5.1 outlines defining characteristics of each.

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5.1 Characteristics of Competitive Markets  187

This chapter tackles perfect competition by extending the analysis of competitive
markets (first introduced in Chapter 2) to study the profit-maximizing decisions of
managers of individual firms in this market. Managers of firms in competitive markets
make fewer pricing decisions than managers of firms that face few or no competitors.
Nonetheless, the decisions they do make affect their firms’ profitability.

The amount of competition a firm faces and the specific product it produces
influence managerial decisions. Common threads will emerge, however, that can
help you manage any firm producing any product. To assist your optimal decision
making, Chapter 5 includes four sections:

• Section 5.1 explains the conditions that define perfectly competitive markets.
• Section 5.2 examines how managers of a perfectly competitive firm can use marginal

analysis to determine the quantity that maximizes profit. The section also examines deci-
sions about when to close a company and how to respond to a change in price.

• Section 5.3 discusses long-run adjustments to the scale of production.
• Section 5.4 applies the concepts of the chapter to managerial decisions in a perfectly

competitive market and includes a cautionary tale for managers of competitive firms.

5.1 Characteristics of Competitive Markets
Learning Objective 5.1 Summarize the conditions that make a market
perfectly competitive.

In economics, the term competition refers to a market structure and the behavior of
buyers and sellers in that market. Popular usage of the word generally conjures up
images of intense personal rivalry, such as that among players on the football field,

Table 5.1 Different Market Structures

Level of Competition
High Low

Perfect
Competition
(Chapter 5)

Monopolistic
Competition
(Chapter 6)

Oligopoly
(Chapters 7

and 8)

Dominant Firm
(Chapter 6)

Monopoly
(Chapter 6)

Number of firms
in the industry

Many Many A few Few or many One

Barriers to entry
by new firms

None None
High to
medium

Medium High

Type of product Identical Differentiated
Identical or

differentiated
Identical Unique

Control over price
None; price

taker
Some; price

setter
Some; price

setter
Some; price

setter
Price setter

Long-run
economic profit

Zero Zero Possible Possible Possible

Strategic behavior No No Yes No No

Example
Maple syrup

producer
Apple PepsiCo Frito-Lay

Roche Holding’s
drug Avastin

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188  CHAPTER 5 Perfect Competition

opponents on the tennis court, or contestants on reality television shows. In contrast,
economic competition is highly impersonal. There is no active rivalry among indi-
vidual market participants. In fact, competitors might even be friends: Two neigh-
boring dairy farmers might be best friends and help each other out even as they are
competing in the dairy market.

Defining Characteristics of Perfect Competition
Five characteristics define a perfectly competitive market:

1. There are many buyers and sellers
2. There are no barriers to entry.
3. Products are homogeneous.
4. Buyers and sellers have perfect information about the price and product

characteristics.
5. There are no transaction costs.

Let’s examine each of these characteristics in turn.

Many Buyers and Sellers
There are many buyers and many sellers in a competitive market. How many? The
number of buyers must be large enough that no one buyer can influence the price.
Similarly, the number of sellers must be large enough that no single seller can influ-
ence the price. In most markets, the number of buyers is so large that an individual
consumer’s purchases are minuscule relative to the total market sales. For example,
no matter how many soft drinks, tomatoes, shares of Microsoft, or legal pads you
buy, you know that your purchases are a minute fraction of the total number pur-
chased and have no impact on the price. Similarly, if a firm accounts for a very small
share of the total market output, its managers know they cannot affect the price of
the product. Each seller has no market power—that is, no control over the price that
is set. More formally, the sellers are price takers, with no ability to change the price
of the good or service being bought and sold. Firms in an industry with a large num-
ber of sellers of similar size are more likely to be price takers than firms in an indus-
try with only a few sellers.

No Barriers to Entry
Why are there many firms in the market? There are many firms because a perfectly
competitive market has no barriers to entry. A barrier to entry is any factor that
makes it difficult for new firms to enter a market. Some barriers to entry are legal
barriers, such as a patent or copyright. Others are cost based, as when an existing
firm has a substantial cost advantage over a new entrant into the market.

Perfectly competitive markets have free entry, which means that new firms
are free to enter the market. Free entry is the reason that a perfectly competitive
market includes many firms. Free entry, however, does not mean that entry is
costless. For example, to enter the restaurant business, an entrepreneur needs
enough capital to buy or rent a building as well as the necessary equipment,
which might cost several hundred thousand or even millions of dollars. Entry
into this market is still said to be free because there are no artificial barriers to
surmount: The entrepreneur is not legally prevented from opening, and once the
business has opened, it is not at a cost disadvantage relative to the previously
existing restaurants.

Perfectly competitive
market A market with the
following five
characteristics: many
buyers and sellers, no
barriers to entry, a
homogeneous product,
perfect information, and no
transaction costs.

Price takers Market
participants (buyers and
sellers) who individually
have no ability to change
the price of the good or
service being bought and
sold.

Barrier to entry Any factor
that makes it difficult for
new firms to enter a
market.

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5.1 Characteristics of Competitive Markets  189

Homogeneous Products
The products sold in perfectly competitive markets are homogeneous, or essentially
identical. For example, all Yukon gold potatoes are virtually the same, so potato buy-
ers do not care from which farmer they buy. Similarly, manufacturers who want
sheet metal of a particular specification are indifferent to its source because all pro-
ducers provide the same product. One seller’s product is a perfect substitute for any
other seller’s product.

Perfect Information
The economic model of perfect competition assumes that all buyers and sellers
have perfect information about all prices and product characteristics. In reality, no
one can have perfect information. But frequently buyers and sellers have enough
information that their market functions as if it were perfectly competitive. For
example, even if the managers of an egg producer in Georgia do not know the price
of eggs in Oregon, they will still operate their company as if it was in a perfectly
competitive market because they know the prices of all relevant competitors.

No Transaction Costs
Transaction costs are the costs of using a market, not the price of the good or service
itself. For example, the cost of driving to the local farmers’ market and then the time
and effort you spend examining the produce before you buy it are examples of
transaction costs. If transaction costs are too high, then goods that otherwise would
be identical are not: Egg consumers in Georgia don’t think eggs in Oregon are iden-
tical to eggs in Georgia. For simplicity, the theoretical model of perfect competition
assumes that there are no transaction costs. Reality, of course, is different. But as
long as transaction costs are not so large as to create many small, separate markets
for the product, transaction costs are low enough for the market to be perfectly
competitive.

Perfectly Competitive Markets
When all of the conditions just described are satisfied, the market is perfectly com-
petitive, and the firms within the market are perfectly competitive firms. Many mar-
kets approximate the theoretical model closely enough that it is fair to analyze them
as perfectly competitive. For example:

• There are over 2,500 textile mills in the United States, and one mill’s product is
very close to being a perfect substitute for any other mill’s product.

• Lumber (and sawdust!) produced by any one of the 2,729 sawmills in the
United States is a virtually perfect substitute for that produced by any of the
others.

• Financial markets, such as stock markets, are often close to perfectly competi-
tive, as is the market for banking services.

The classic examples of perfectly competitive markets, however, are agricultural,
such as the markets for eggs, wheat, cotton, and maple syrup. Consider the market
for maple syrup. The product is homogeneous because one company’s Grade A,
light amber maple syrup is identical to any other company’s similarly graded syrup.
Clearly, there are a large number of buyers and, with 8,000 producers in the United
States, a large number of sellers. There are no barriers to entry—if entrepreneurs
want to enter the market, all they must do is buy a stand of sugar maple trees.

Transaction costs The
costs of using a market.

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190  CHAPTER 5 Perfect Competition

Information is close to perfect because it is easy to learn the prices different firms
charge. Transaction costs are low—discovering different producers is simple, and it
is not difficult to buy or sell maple syrup.

Buyers and sellers in the maple syrup market are price takers. A buyer’s pur-
chase of an additional bottle or even a case of maple syrup does not change its price,
which demonstrates the effect of competition on the buying side: The price per unit
is unaffected by the quantity purchased. There is also competition on the selling
side: The managers of a single producer—say, once again, Happy Jack’s Maple
Syrup—know that producing an extra 100 gallons has no discernible effect on the
price of maple syrup.

As you learned in Chapter 2, market demand and supply determine the price in
perfectly competitive markets. Although managers within such firms cannot control
the price of their products, they must accomplish many other tasks. As a manager,
you must pay close attention to details such as productive efficiency and mainte-
nance of product and service quality. More importantly, however, you must deter-
mine the amount to produce that will maximize the firm’s profit. We turn to this
decision in the next section.

The Markets for Fencing and Cell Phones

The Affordable Fence Company is one of approximately 50 fencing companies in Pittsburgh,
Pennsylvania. U.S. Cellular is one of four cell phone companies in Bangor, Maine.

a. Is the Affordable Fence Company competing in a perfectly competitive market? Is it
a price taker? Explain your answers.

b. Is U.S. Cellular competing in a perfectly competitive market? Is it a price taker?
Explain your answers.

Answer
To determine if these companies compete in perfectly competitive markets, you need to
decide how closely the market meets the five criteria of a perfectly competitive market.

a. A fence built by the Affordable Fence Company is virtually identical to a fence of
the same style built by any other company, so the products are close to homoge-
neous. There are a large number of buyers and sellers. Because any entrepreneur
can open a fencing company and not face a cost disadvantage compared to the
existing companies, there are no barriers to entry into this market. Buyers and
sellers can easily determine the prices different fencing companies charge, so infor-
mation is nearly perfect. Additionally, the transaction costs of buying a fence are not
large, so there is effectively only one market for fences in Pittsburgh. Consequently,
the Affordable Fence Company operates in a market that is very close to perfectly
competitive. Because the company competes in a perfectly competitive market, it is
a price taker.

b. U.S. Cellular does not compete in a perfectly competitive market. One of the charac-
teristics of perfectly competitive markets is a large number of buyers and sellers.
While there are a large number of buyers in this market, with only four sellers the
market is not perfectly competitive. So U.S. Cellular is not a price taker.

SOLVED
PROBLEM

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5.2 Short-Run Profit Maximization
in Competitive Markets

Learning Objective 5.2 Use marginal analysis to determine the profit-maximizing
quantity that a perfectly competitive firm produces in the short run.

Continue to assume that the objective of all managers, including managers of per-
fectly competitive firms, is profit maximization. Total profit is equal to the difference
between the total revenue (TR) and the total opportunity cost (TC) of producing and
selling the product:

Total profit = TR – TC

To maximize profit, a manager must select the quantity of output that maxi-
mizes the difference between total revenue and total cost.

Marginal Analysis
As you learned in Chapter 1, marginal analysis compares the marginal benefit of an
action to its marginal cost (see Section 1.4). In this and other chapters, you will see
more specifically how managers can use marginal analysis as an extremely import-
ant decision-making tool in many different circumstances. In this chapter, it helps
determine the profit-maximizing quantity to produce.

How does the marginal analysis rule help you determine how much output to pro-
duce? First, recall that the word marginal means “additional.” Marginal analysis focuses
on the additional benefit and additional cost from an action, not the total benefit or total cost
from all of the actions. In this case, the action is to produce another unit of output. The
marginal benefit is the change in total revenue from selling the additional unit because
that is the additional benefit. The change in the total revenue from selling an additional
unit is the marginal revenue. The marginal cost is the change in total cost from producing
the additional unit because that is the additional cost of the unit. The first step in applying
marginal analysis to profit maximization is to determine the demand for the firm’s prod-
uct because demand dictates the change in total revenue from an additional unit.

Market Demand and Firm Demand in a Competitive Market
When analyzing a perfectly competitive market, you must distinguish between mar-
ket demand and an individual firm’s demand. Figure 5.1 illustrates the difference
between the market demand curve and an individual firm’s demand curve in
the competitive market for maple syrup. Figure 5.1(a) shows the market demand
curve (D) and the market supply curve (S) for maple syrup. Figure 5.1(b) shows the
demand curve (d) for one individual firm—say, Happy Tree Maple Syrup, which is
one of thousands of firms producing maple syrup. The equilibrium price and the
equilibrium quantity are determined in the market as a whole from the intersection
of the market supply curve and the market demand curve, so in Figure 5.1(a)
the equilibrium price and quantity are $30 per gallon and 12 million gallons. As the
arrow extending from Figure 5.1(a) to Figure 5.1(b) indicates, Happy Tree has no
control over the price and takes the equilibrium price as given. It can sell whatever
quantity of maple syrup it produces at the equilibrium price. Its demand is perfectly
elastic at the equilibrium price, as demonstrated by the horizontal demand curve (d)
at the price of $30 per gallon, because all other firms’ maple syrup is a perfect substi-
tute for Happy Tree’s syrup. With perfectly elastic demand, Happy Tree’s managers
effectively have no control over the price they set. If they set a price above the equi-
librium price, their sales collapse to zero—no one will buy from them because there

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192  CHAPTER 5 Perfect Competition

are other, perfect substitutes available at a lower price. There is no need for them to
set a price lower than the equilibrium price because they can sell whatever quantity
they want at the (higher) equilibrium price.

Marginal Revenue
To use marginal analysis, the managers at Happy Tree Maple Syrup must understand
how changes in output change the firm’s total revenue. The first two columns of
Table 5.2 show details of part of Happy Tree’s demand curve shown in Figure 5.1(b).
In the table, the quantity ranges from 1,494 gallons to 1,505 gallons of maple syrup.
(Because the firm is a small part of the market, we use “q” to indicate a firm’s quan-
tity and “Q” to indicate the market’s quantity.) Of course, Happy Tree can sell any
quantity it produces, from 1 gallon to whatever quantity its trees can produce, for
$30 per gallon. Happy Tree’s total revenue (TR), price (P) multiplied by quantity (q),
is included in the third column of Table 5.2.

To make their production decision, the managers at Happy Tree need to know
the marginal revenue. Marginal revenue shows how total revenue changes when the
firm sells another unit, so, more formally, marginal revenue (MR) is the change in
total revenue (TR) divided by the change in quantity (q): MR = ∆TR∆q . where the delta
symbol 1∆2 means “change in.” Typically, marginal revenue is calculated using a
small change in output—say, one unit.

Using this definition, the marginal revenue from increasing production of
Happy Tree’s maple syrup by one unit, from 1,494 gallons to 1,495 gallons, equals
$44,850 – $44,820

1,495 – 1,494 = $30.

Marginal revenue The
change in the total revenue
divided by the change in
quantity: MR = ∆TR∆q .

Figure 5.1 Market Demand Curve and Individual Firm Demand Curve in a Competitive Market

(a) Market Demand Curve (b) Individual Firm Demand Curve
The market demand curve for maple syrup (D) and
the market supply curve for maple syrup (S)
determine the equilibrium price of maple syrup,
$30 per gallon.

Happy Tree Maple Syrup is one of thousands of firms
producing maple syrup. As the arrow extending
between parts (a) and (b) indicates, Happy Tree takes
the equilibrium price of $30 as given. At this price,
Happy Tree is able to sell as much maple syrup as it
produces, so its demand curve (d) is horizontal.

Price (dollars per gallon
of maple syrup)

Quantity (millions of gallons
of maple syrup per year)

$60

$70

$10

20 2412 164 8

$20

$30

$40

$50

0

S

D

Price (dollars per gallon
of maple syrup)

Quantity (gallons of maple
syrup per year)

$60

$70

$10

2,500 3,0001,500 2,000500 1,000

$20

$30

$40

$50

0

d

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Column 4 of Table 5.2 shows the marginal revenue for the rest of the quantities in the
range, and Figure 5.2 illustrates the results. Notice anything striking? The marginal reve-
nue (MR) is always the same ($30) and is always equal to the price (P). As an equation,

P = MR 5.1

This equality is true for all perfectly competitive firms. Because the price equals the
marginal revenue for all quantities, the marginal revenue curve (MR) is horizontal
and is identical to the firm’s demand curve (d) shown in Figure 5.2.

Table 5.2 Demand, Total Revenue, and Marginal Revenue for Happy Tree Maple Syrup

The first two columns show part of the demand facing Happy Tree Maple Syrup. Total revenue (TR) equals P * q.
Marginal revenue (MR) is the change in total revenue caused by a change in sales. For a perfectly competitive
firm, marginal revenue equals the price: MR = P .

Price, P Quantity Demanded, q Total Revenue, TR Marginal Revenue, MR

$30.00 1,494 $44,820
$30.00

30.00

30.00

30.00
30.00

30.00

30.00

30.00

30.00

30.00

30.00

30.00 1,495 44,850

30.00 1,496 44,880

30.00 1,497 44,910

30.00 1,498 44,940

30.00 1,499 44,970

30.00 1,500 45,000

30.00 1,501 45,030

30.00 1,502 45,060

30.00 1,503 45,090

30.00 1,504 45,120

30.00 1,505 45,150

Price (dollars per gallon
of maple syrup)

Quantity (gallons of maple
syrup per year)

$60

$70

$10

2,500 3,0001,500 2,000500 1,000

$20

$30

$40

$50

0

d 5 MR

Figure 5.2 A Perfectly
Competitive Firm’s Demand
and Marginal Revenue
Curves

For a perfectly competitive
firm, the marginal revenue
curve (MR) is identical to the
firm’s demand curve (d).
Both are horizontal at the
market’s equilibrium price.

5.2 Short-Run Profit Maximization in Competitive Markets  193

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194  CHAPTER 5 Perfect Competition

Cost (dollars per gallon
of maple syrup)

Quantity (gallons of maple
syrup per year)

$60

$70

$10

2,500 3,0001,500 2,000500 1,000

$20

$30

$40

$50

0

MC

Figure 5.3 Marginal Cost
Curve

The marginal cost curve
(MC) is a U-shaped curve
that reaches a minimum at
750 gallons and then rises.

Marginal Cost
To use marginal analysis, managers need not only the marginal revenue but also the
other half of the comparison, the marginal cost. As you learned in Chapter 4, marginal
cost (MC) is the change in total cost (TC) divided by the change in output (q):

MC =
∆TC
∆q

Figure 5.3 shows Happy Tree’s marginal cost curve (MC). This U-shaped curve
should be familiar because it is similar to those you saw in Chapter 4. As the quan-
tity produced increases, the marginal cost curve in Figure 5.3 falls to its minimum (at
750 gallons) and then rises.

Using Marginal Analysis to Maximize Profit
Figure 5.4 combines the marginal revenue curve in Figure 5.2 and the marginal
cost curve in Figure 5.3. Marginal analysis shows that Happy Tree Maple Syrup
maximizes its profit by producing the quantity (q) at which marginal revenue
equals marginal cost 1MR = MC2, 2,000 gallons of maple syrup per year. You can
use Figure 5.4 to illustrate how marginal analysis leads to this conclusion. Consider
two quantity ranges:

• Quantity less than 2,000 gallons. Take a quantity less than 2,000 gallons—say,
1,000 gallons. Producing the 1,000th gallon increases total revenue by $30 (the
MR) but increases total cost by only $10 (the MC). If this gallon is produced,
profit increases by $20 1$30 – $102, which is equal to the length of the dou-
ble-headed arrow at this quantity. Because the 1,000th gallon increases Happy
Tree’s profit, it should be produced. This conclusion is confirmed by application
of the marginal analysis rule: If the marginal benefit of producing the unit—in

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this case, the marginal revenue (MR)—exceeds the marginal cost (MC) of
producing the unit, the unit should be produced. Applying this reasoning to
Figure 5.4, you will see that all of the gallons of maple syrup up to 2,000 gallons
should be produced because for each gallon in this range MR 7 MC, so each
gallon is profitable.

• Quantity greater than 2,000 gallons. Now take a quantity greater than 2,000
gallons—say, 2,500 gallons. At this quantity, the revenue from the 2,500th gallon
is $30 (the MR), and the cost of producing it is $60 (the MC). Producing this gal-
lon imposes a loss of $30 1$60 – $302, which is equal to the length of the dou-
ble-headed arrow at this quantity. So Happy Tree’s profit increases if it does not
produce the 2,500th gallon. Again, the marginal analysis rule confirms this con-
clusion: If the marginal benefit of producing the unit—the marginal revenue
(MR)—is less than the marginal cost (MC) of producing the unit, the unit should
not be produced. None of the gallons of maple syrup beyond 2,000 gallons
should be produced. Each gallon in this range has MR 6 MC, so each gallon
imposes a loss on Happy Tree.

By producing where MR = MC, the managers maximize Happy Tree’s profit
because the firm is producing all of the profitable units and none of the unprofit-
able units.1 Now that the managers know the profit-maximizing quantity, what
price should they set for Happy Tree’s maple syrup? As you have already learned,
the managers have no choice: In a competitive market, the price of a gallon of
maple syrup is the equilibrium price of $30. From a managerial standpoint, how-
ever, it is useful to ask “What is the highest price at which every unit produced

Price and cost (dollars per
gallon of maple syrup)

Quantity (gallons of maple
syrup per year)

$60

$70

$10

2,500 3,0001,500 2,000500 1,000

$20

$30

$40

$50

0

MC

d 5 MR

MR . MC MR , MC

Figure 5.4 Profit
Maximization

The firm maximizes its profit
by producing the quantity
where MR = MC , which
occurs at 2,000 gallons. If the
firm produces less, it loses
profit because it is not
producing some profitable
units. If the firm produces
more, it loses profit because
it is producing some
unprofitable units.

1 Section 5.B of the Appendix at the end of this chapter demonstrates how to use calculus to solve for the
profit-maximizing quantity.

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196  CHAPTER 5 Perfect Competition

can be sold?” because that price will maximize the firm’s profit. The firm’s demand
curve answers this question. The demand curve shows that when Happy Tree pro-
duces 2,000 gallons of syrup, the highest price consumers are willing to pay for
this quantity is $30 per gallon. If the managers set a higher price—say, $31 per
gallon—then consumers buy 0 gallons from Happy Tree because in a competitive
market they can buy maple syrup elsewhere for $30. In this unhappy case, Happy
Tree earns no revenue and incurs a loss. The managers could instead set a lower
price and sell all 2,000 gallons produced, but setting a lower price lowers profit.
The profit-maximizing price is $30.

This analysis can be summarized with the profit-maximization rule: Produce the
quantity for which MR = MC, and then set the highest price that sells the quantity
produced.

Say that you are a manager at the American Cancer Society, a nonprofit organiza-
tion, and are considering a mass mailing to ask people for donations. You know
that each letter will cost $1.00 + $0.00001Q, where Q is the number of letters
mailed. You also estimate that each recipient will donate $21. How many letters
should you mail?

Answer
Although the goal of the American Cancer Society is to raise funds to fight cancer
rather than to maximize profit, you still need to use marginal analysis to determine
how many letters to mail. You want to mail all the letters for which the donation
exceeds the cost, so the optimal number is the one at which MR = MC, where MR
is the donation from the recipient, $21, and MC is the cost of mailing the letter,
$1.00 + $0.00001Q. You will therefore use the equation $21 = $1.00 + 0.00001Q
to determine the number of letters to mail. Solving this equation shows that Q = 2
million letters. By mailing 2 million, you will mail all the letters that result in a dona-
tion above the cost of the letter and none of the letters with a cost exceeding the
amount of the resulting donation.

DECISION
SNAPSHOT

Marginal Analysis at the American
Cancer Society

• Produce the quantity for which MR = MC .

• Set the highest price for which every unit produced can be sold.

PROFIT-MAXIMIZATION RULE

Changes in Costs
If the marginal cost of production changes, you must change the quantity pro-
duced to maximize profit. Suppose that the price of one of the variable inputs
needed to produce Happy Tree’s maple syrup rises, perhaps the price of the fuel

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used to boil the tree sap to produce the maple syrup. You learned in Section 4.3
that an increase in variable cost increases the marginal cost. Figure 5.5 shows that
when a variable input rises in price, the marginal cost curve shifts upward from
MC0 to MC1. The increase in the marginal cost changes the profit-maximizing
quantity. Assuming that the price of maple syrup does not change, Figure 5.5
demonstrates that the profit-maximizing quantity of syrup decreases from 2,000
to 1,500 gallons per year. The increase in marginal cost means that the gallons
between 1,500 and 2,000 are no longer profitable—their marginal revenue is less
than their marginal cost. If you apply marginal analysis, you see that Happy Tree
should not produce these gallons of syrup because they would decrease profit.

As a perfectly competitive firm, there is nothing Happy Tree can do to offset the
higher costs. Happy Tree’s managers are at the mercy of the market. As long as the
firm stays open, the best the managers can do is respond to the increase in their cost
by decreasing the quantity they produce.

Amount of Profit
Once you have discovered the profit-maximizing quantity, your work is done, right?
Wrong—in addition to monitoring production to continue to minimize costs and/or
take account of changes in costs, you must be vigilant about changes in the price. In
contrast to the simplified maple syrup example, in some markets prices change fre-
quently—from day to day or even minute to minute. As a manager, in most indus-
tries you will not be able to respond to minute-by-minute price changes. But when a
price change lasts long enough, you will want to respond by changing your produc-
tion. Indeed, the price may even fall low enough that you want to close the firm,
either temporarily or permanently. To understand when this decision is necessary,
you must first determine the firm’s profit.

Price and cost (dollars per
gallon of maple syrup)

Quantity (gallons of maple
syrup per year)

$60

$70

$10

2,500 3,0001,500 2,000500 1,000

$20

$30

$40

$50

0

MC0
MC1

d 5 MR

Initial
quantity

Final
quantity

Figure 5.5 A Change in
Marginal Cost

An increase in Happy Tree’s
variable cost increases its
marginal cost, shifting the
marginal cost curve upward
from MC0 to MC1. Profit-
maximizing managers
respond to the increase in
marginal cost by decreasing
the firm’s production from
2,000 to 1,500 gallons.

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198  CHAPTER 5 Perfect Competition

Economic Profit
You know that producing the quantity at which marginal revenue equals marginal cost
1MR = MC2 maximizes profit, but to this point, the discussion has not included the
amount of that profit. Economists measure the firm’s total profit as its total revenue
minus its total opportunity cost. Recall from Chapter 1 (Section 1.4) and Chapter 4
(Section 4.3) that the owners’ competitive return (the return the owners could have made
by using their funds in another endeavor) is one part of the firm’s opportunity cost.

Figure 5.6, which shows the average total cost curve (ATC), the marginal cost
curve (MC), and marginal revenue curve (MR), can help you calculate total profit.
The total revenue is the price of the product (P) multiplied by the quantity (q), or
P * q, and the total cost is the average total cost (ATC) multiplied by the quantity (q),
or ATC * q.2 Therefore, the total profit is equal to

1P * q2 – 1ATC * q2 5.3
Note that both terms in Equation 5.3 have the same factor, q. Taking that factor out
and rewriting the equation, total profit is equal to

1P – ATC2 * q 5.4
Equation 5.4 has an immediate intuitive interpretation: The price minus the aver-

age total cost 1P – ATC2 is the profit per unit. Equation 5.4 shows that the total profit
equals the profit per unit multiplied by the previously determined profit-maximizing
number of units, q.

In Figure 5.6, this profit is equal to the area of the green rectangle. The
area of a rectangle equals the height multiplied by the base. The height of the

2 The result stems from the definition of average total cost, ATC =
Total cost

q . Multiplying both sides of
this equality by Q gives ATC * q = Total cost.

Price and cost (dollars per
gallon of maple syrup)

Quantity (gallons of maple
syrup per year)

$60

$70

$10

2,500 3,0001,500 2,000500 1,000

$20

$30

$40

$50

0

MC

A

B

ATC

d 5 MR

Economic
profit
$20,000

Figure 5.6 Economic Profit
for a Perfectly Competitive
Firm

The firm’s economic profit
equals its total revenue,
P * q, minus its total cost,
ATC * q. The area of the
green rectangle equals the
firm’s economic profit,
$20,000. A firm makes an
economic profit if P 7 ATC .

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rectangle in Figure 5.6 is the distance between points A and B. Point A is the price
($30), and point B is the average total cost of producing 2,000 gallons of syrup
($20), so the height is P – ATC, the profit per unit, or $30 – $20 = $10. The base
of the rectangle in the figure equals 2,000 gallons, the profit-maximizing quantity
(q). So the area of the rectangle is equal to the total profit, or 1$30 – $202 *
2,000 gallons = $20,000.

The profit just calculated is the firm’s total revenue minus its total opportunity
cost. Because the owners’ competitive return is already part of the opportunity cost,
the $20,000 profit calculated using Equation 5.4 and illustrated in Figure 5.6 is a
profit over and above the normal competitive return. This profit is an economic
profit, the firm’s profit over and above the competitive return. Figure 5.6 and Equa-
tion 5.4 show that a business makes an economic profit whenever the price per unit
is greater than the average total cost: P 7 ATC.

Competitive Return
Although managers (and owners) definitely prefer making an economic profit,
sometimes the best they can achieve is a competitive return. Figure 5.7 illustrates a
situation in which the market price of maple syrup has fallen to $15 per gallon. The
managers at Happy Tree continue to maximize profit by producing the quantity for
which MR = MC. Figure 5.7 shows that the best managers can do is produce 1,500
gallons of syrup because this quantity is the profit-maximizing amount when the
price is $15 per gallon.

Figure 5.7 also shows that when Happy Tree produces 1,500 gallons of maple
syrup, the average total cost equals the price ($15 per gallon). Total revenue and
total cost both equal $15 * 1,500 gallons, or $22,500. Because the total revenue and

Economic profit A firm’s
profit over and above the
competitive return.

Price and cost (dollars per
gallon of maple syrup)

Quantity (gallons of maple
syrup per year)

$60

$70

$10

2,500 3,0001,500 2,000500 1,000

$20

$30

$40

$50

0

MC

ATC

d 5 MR

Figure 5.7 Competitive
Return for a Perfectly
Competitive Firm

The firm’s economic profit
equals its total revenue,
P * q, minus its total cost,
ATC * q. If P = ATC , the
firm makes zero economic
profit; that is, its owners
make a competitive return on
the funds they have invested
in the business.

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200  CHAPTER 5 Perfect Competition

the total cost are equal, the owners of Happy Tree make no economic profit. You can
calculate this same result using Equation 5.4: Economic profit is 1P – ATC2 * q, or
1$15 – $152 * 1,500 gallons = $0. Zero economic profit does not mean that
Happy Tree is making no profit at all. Instead, the owners are making a competitive
return, the same profit they expect they would make if they used their resources in
some other competitive venture. A firm makes zero economic profit whenever
P = ATC because at that point the total revenue equals the total opportunity cost,
which includes the owners’ competitive return.

Economic Loss
Despite managers’ best efforts, a firm sometimes cannot make even a competitive
return. In this case, the best the managers can do is to minimize the firm’s loss.
Figure 5.8 illustrates this outcome for Happy Tree. Note that the equilibrium price in
the market has fallen still lower, to $13 per gallon. The managers continue to maxi-
mize profit, which in this case means minimizing loss, by producing the quantity
that sets MR = MC, 1,300 gallons of syrup at $13 per gallon.

When Happy Tree produces 1,300 gallons of syrup, average total cost is $16 per
gallon. Total revenue is $13 * 1,300 gallons, or $16,900, and total cost is $16 * 1,300
gallons, or $20,800. The “profit” is $16,900 – $20,800, or a loss of $3,900. Happy Tree
incurs an economic loss, the amount by which the firm’s total opportunity cost
exceeds its total revenue. Happy Tree’s owners are not happy because they are mak-
ing $3,900 less than a competitive return. A firm incurs an economic loss whenever
P 6 ATC because the firm’s total opportunity cost is greater than its total revenue.
The economic loss is equal to (P – ATC) * q, which is the area of the light red rect-
angle in Figure 5.8.

Economic loss The
amount by which the firm’s
total opportunity cost
exceeds its total revenue.

Price and cost (dollars per
gallon of maple syrup)

Quantity (gallons of maple
syrup per year)

$60

$70

$10

2,500 3,0001,500 2,000500 1,000

$20

$30

$40

$50

0

Economic
loss,
$3,900

MC

ATC

d 5 MR

Figure 5.8 Economic Loss for
a Perfectly Competitive Firm

The firm’s economic profit
equals its total revenue,
P * q, minus its total cost,
ATC * q. If the average total
cost exceeds the price,
P 6 ATC , the total cost
exceeds the total revenue.
The area of the light red
rectangle, $3,900, equals the
firm’s economic loss.

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• Economic profit: For any firm, if P 7 ATC , the firm makes an economic profit—
that is, more than a competitive return.

• Competitive return: For any firm, if P = ATC , the firm makes a competitive
return—that is, zero economic profit.

• Economic loss: For any firm, if P 6 ATC , the firm incurs an economic loss—
that is, less than a competitive return.

RULES FOR DETERMINING THE AMOUNT OF PROFIT

Shutting Down
The managers of a business that is incurring an economic loss face a very important
decision: Should their firm stay open, or should it close? If they believe that condi-
tions will improve in the future, so the economic loss will not persist, their initial
response might be to keep the firm open. Indeed, that is a reasonable option. Another
option is to close temporarily and then reopen. The managers must decide which
option is more profitable.

Suppose, however, that the managers believe that conditions will not change in
the future, so the economic loss will persist indefinitely. Even in this dismal situa-
tion, they might decide to keep the firm open temporarily because the loss might be
lower than if they close it. Managers should choose the option that minimizes the
amount of loss. So, let’s take a closer look at the losses in these two situations:

• Firm closes. A closed firm has no sales, so its total revenue is zero. Because the
closed firm does not employ any variable inputs, its variable cost (VC) is also
zero. Fixed costs (FC), however, are unavoidable in the short run, so the firm
must continue to pay them. Therefore, the closed firm’s loss is FC.

• Firm remains open. The firm’s loss is its total revenue minus its total cost, TR – TC.
It is useful to separate the total cost into fixed cost and variable cost, in which case
you can see that the loss when the firm remains open is TR – (FC + VC).

Now suppose that total revenue is greater than variable cost: TR 7 VC. In this
case, if the firm remains open, its revenue pays all of its variable cost with some rev-
enue left over to pay some of its fixed cost. The key observation is that if the business
is open, the loss is less than the fixed cost. In this case, the firm should remain open.

Next, suppose that TR 6 VC. In this case, the revenue the firm collects if it is
open cannot pay all of its variable cost. The total loss if open equals the fixed cost plus
whatever part of the variable cost cannot be paid. In this unfortunate situation, the
loss if the business is open is greater than the fixed cost, so to minimize the loss, the
managers must close the firm.

Shut-Down Rule
The analysis of the loss when open and closed shows that the decision to stay open or to
close hinges on the comparison of total revenue and variable cost. The decision to keep
a firm open if TR 7 VC and close if TR 6 VC is generally called the shut-down rule.

In summary, a perfectly competitive firm makes an economic profit if P 7 ATC,
makes a competitive return if P = ATC, and incurs an economic loss if P 6 ATC.
The following box summarizes these results.

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202  CHAPTER 5 Perfect Competition

This rule can be transformed into an alternative formulation that is useful. To
transform the rule, use price (P) multiplied by quantity (q) in place of total revenue
1because TR = P * q2 and average variable cost (AVC) multiplied by quantity (q) in
place of variable cost 1because VC = AVC * q2.3 The shut-down rule can then be
rewritten as “stay open if P * q 7 AVC * q and close if P * q 6 AVC * q.” There’s
one more step: Divide both sides of the inequalities by q, so the rule finally becomes
to “stay open if P 7 AVC and close if P 6 AVC.”

Price and cost (dollars per
gallon of maple syrup)

Quantity (gallons of maple
syrup per year)

$60

$70

$10

2,500 3,0001,500 2,000500 1,000

$20

$30

$40

$50

0

The firm closes if
the price is less
than the minimum
average variable
cost (AVC).

MC

ATC

AVC

Figure 5.9 Shutting Down

The minimum average
variable cost is $10 per
gallon of maple syrup. At any
price less than $10, Happy
Tree closes.

3 The second equality comes from the definition of AVC =
Variable cost

q . Multiplying both sides of the
equality by q yields AVC * q = Variable cost.

• Stay open: The firm stays open if TR 7 VC or, equivalently, if P 7 AVC . The
firm’s loss is less if it stays open than if it closes.

• Close: The firm closes if TR 6 VC or, equivalently, if P 6 AVC . The firm’s loss
is less if it closes than if it stays open.

SHUT-DOWN RULE

Figure 5.9 illustrates the modified version of the shut-down rule by adding the
average variable cost curve (AVC) to the marginal cost and average total cost curves
presented in Figure 5.8. As shown, the minimum average variable cost is $10 per
gallon of maple syrup. Consequently, at any price less than $10 per gallon, the price
is less than the average variable cost, so if you apply the shut-down rule, Happy Tree

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closes whenever the price is less than $10 per gallon. At any price higher than $10
per gallon, the firm remains open.

What should Happy Tree’s managers do if the price is exactly the minimum
average variable cost, $10 per gallon? Unfortunately, there is no clear-cut answer to
this question. At $10 per gallon, the loss will be the same whether Happy Tree
remains open or closes its doors. If there is a cost associated with closing and then
reopening, the firm might stay open. After taking into account all revenues and all
costs, if the loss is the same in both cases, it just might be time for a coin flip.

Long-Run Exit
In the short run, a firm that incurs an economic loss stays open as long as the total
revenue exceeds the variable cost. But what happens in the long run? As you learned
in Chapter 4, fixed costs become variable costs with the passage of time. For exam-
ple, when a lease comes up for renewal, the rent changes from a fixed cost to a vari-
able cost. Ultimately, as time passes, the variable cost increases enough that it

The market for rice is a perfectly competitive, worldwide market. Between 2013
and 2014, the price of rice fell approximately 18 percent, from $519 per ton to
$426 per ton. Lundberg Family Farms is a large rice grower located in Richvale,
California. This company has many different fields in which it can grow rice.
Assume that when the price of rice was $519 per ton, the company was making
zero economic profit, so that the owners were making a competitive return on the
funds they had invested in the company. As a manager at Lundberg Family
Farms, what decisions should you make in response to the fall in the price of rice?

Answer
As a manager of a perfectly competitive firm, you must first decide how much rice
to produce. By applying marginal analysis, you conclude that the fall in the price
of rice (which is a fall in the marginal revenue) means that the profit-maximizing
quantity of rice decreases. Selecting which fields you will plant determines how
much rice Lundberg Family Farms will produce. You must determine which of
your rice fields are still profitable: For which fields does the marginal revenue
from the field exceed the marginal cost of using the field? Fields that are less
fertile or require additional transportation after harvesting the rice might not be
profitable with the lower price of rice and accordingly should be left fallow.

After determining which fields you will plant, you face an additional decision:
Because the firm was making only a competitive return (zero economic profit)
with the higher price of rice of $519 per ton, when the price falls to $426 per ton,
the firm incurs an economic loss. You must determine whether the economic loss
is less if Lundberg Family Farms remains open or if it closes. This decision
requires you to compare the total revenue and the variable cost. Once you have
determined which fields to plant, if the total revenue exceeds the variable cost, you
minimize the loss by staying open. If the total revenue is less than the variable
cost, however, you minimize the loss by closing.

DECISION
SNAPSHOT

Lundberg Family Farms Responds to a Fall
in the Price of Rice

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204  CHAPTER 5 Perfect Competition

ultimately becomes greater than the total revenue 1TR 6 VC2. When this happens,
the managers’ decision switches from keeping the business open to closing it. If the
loss will recur when the business reopens, the business stays closed permanently, or
as an economist would put it, the business exits the market.

The managerial lesson is straightforward: A business incurring a persistent eco-
nomic loss might continue to operate for a while, but eventually it closes and exits
the market. In other words, no business will sustain a long-run economic loss. As a
manager, your responsibility is clear: When the passage of time converts fixed costs
to variable costs, you must determine whether the loss incurred by remaining open
is less than the loss incurred by exiting.

The Firm’s Short-Run Supply Curve
Suppose that the price of maple syrup is above the minimum average variable cost,
so that the firm is open. As a Happy Tree manager, how do you respond to a change
in the price? How much should you produce at different prices? Figure 5.10 helps
answer both of these questions.

Figure 5.10 shows the demand curves (d) for three prices: $15 per gallon, $30 per
gallon, and $45 per gallon. Managers maximize profit by producing the quantity for
which MR = MC, so when the price is $15 per gallon, Happy Tree produces 1,500
gallons; when it is $30 per gallon, Happy Tree produces 2,000 gallons; and when it is
$45 per gallon, Happy Tree produces 2,250 gallons.

These three price/quantity combinations are three points on Happy Tree’s supply
curve, the curve that shows the quantity the firm produces at different prices. All three
points fall on the marginal cost curve. In general, a short-run firm supply curve
shows the quantity the firm produces at different prices; it is the portion of the mar-
ginal cost curve above the minimum of the average variable cost. In Figure 5.10,
Happy Tree’s short-run supply curve is the wide blue part of the marginal cost curve.

Short-run firm supply
curve The curve that
shows the quantity the firm
produces at different
prices; the short-run firm
supply curve is the portion
of the marginal cost curve
above the minimum
average variable cost.

Price and cost (dollars per
gallon of maple syrup)

Quantity (gallons of maple
syrup per year)

$60

$70

$10

2,500 3,0001,500 2,000500 1,000

$20

$30

$40

$50

0

MC

ATC

AVCd$45 5 MR$45

d$30 5 MR$30

d$15 5 MR$15

Figure 5.10 The Firm’s Short-Run Supply Curve

At a price of $15 per gallon of syrup, Happy Tree
maximizes its profit by producing 1,500 gallons. If the
price is $30 per gallon, Happy Tree’s profit-maximizing
quantity increases to 2,000 gallons. And if the price is
$45 per gallon, Happy Tree produces 2,250 gallons.
Because Happy Tree maximizes its profit by producing
the quantity for which MR = MC , Happy Tree’s supply
curve is the wide blue portion of the marginal cost
curve above the minimum point on the average
variable cost curve.

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If the price is lower than the minimum average variable cost, the managers close the
firm, so that the quantity produced is zero.

The fact that the firm’s short-run supply curve is the same as its marginal cost
curve is no accident: Managers are producing the quantity that sets the price (which
equals the marginal revenue) equal to the marginal cost. At any price for which
Happy Tree remains open (at any price above the minimum average variable cost),
the quantity produced is a point on its marginal cost curve. In other words, a firm’s
short-run supply curve is equal to its marginal cost curve at all points above its aver-
age variable cost curve. For all prices below the minimum point on the average vari-
able cost curve, the managers maximize the firm’s profit (minimize its loss) by
producing zero output and just closing its doors.

Particleboard is made, in part, from sawdust. The market for particleboard is
worldwide and is perfectly competitive. Suppose that you are a manager of a firm
like Collins Products, located in Klamath Falls, Oregon, when the price of sawdust
falls from $75 per ton to $50 per ton. In the short run, how will you respond to
this fall in price? What do you expect will happen to the price of particleboard? In
the short run, what do you expect will happen to your company’s profit? Draw a
graph to support your answer.

Answer
Sawdust is a variable input because the more particleboard you produce, the
more sawdust you use. The fall in the price of sawdust means that your marginal
cost of producing particleboard falls, shifting the marginal cost curve down-
ward. For example, in the figure, the marginal cost curve shifts downward, from
MC0 to MC1. At the original quan-
tity you produced—30 million
square feet, as shown in the
figure—the marginal revenue
now exceeds the marginal cost.
To maximize your profit, you
should apply marginal analysis
and respond to the fall in cost by
increasing the quantity of particle-
board that you produce to 40 million
square feet. Because all particle-
board suppliers will be increasing
the quantity they produce, the
market supply curve shifts to the
right, so the price of particleboard
falls. In the short run, however,
you can expect to make an eco-
nomic profit.

DECISION
SNAPSHOT

A Particleboard Firm Responds to a Fall
in the Price of an Input

Price and cost (dollars per square
foot of particleboard)

Quantity (millions of square
feet of particleboard per year)

$0.50

5030 4010 20

$1.00

$1.50

$2.00

$2.50

0

d 5 MR

MC0 MC1

5.2 Short-Run Profit Maximization in Competitive Markets  205

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206  CHAPTER 5 Perfect Competition

The Short-Run Market Supply Curve
As you have already learned, in a perfectly competitive market the production deci-
sion of any single firm does not affect the equilibrium price. Instead, market demand
and the collective supply produced by all firms in the market determine the equilib-
rium price. The short-run market supply curve represents the quantity supplied by
all of the firms in the market at various prices in the short run.

To construct the short-run market supply curve, add the quantities produced by
the individual firms at any given price. For simplicity, assume that the market has only
two firms in it. Of course, a perfectly competitive market contains many more than sim-
ply two firms, but once you understand how the market supply curve is created for two
firms, understanding its creation for any number of firms is immediate. Figure 5.11
illustrates the quantities of maple syrup produced by the two firms. Firm 1’s supply
curve is s1, and firm 2’s supply curve is s2. At a price of $20 per gallon, firm 1 supplies
1,000 gallons, and firm 2 supplies 2,000 gallons. The quantity supplied in the market is
1,000 gallons plus 2,000 gallons, for a total market quantity of 3,000 gallons, at point A
on the short-run market supply curve (S). When the price is $30 per gallon, firm 1 sup-
plies 1,500 gallons, and firm 2 supplies 2,500 gallons, for a total market supply of 4,000
gallons (point B). At a price of $60 per gallon, the quantity supplied in the market is
2,000 gallons plus 3,000 gallons, or 5,000 gallons (point C). These are three points on the
short-run market supply curve. All the other points are calculated similarly: At any
price, add the quantity produced by firm 1 to that produced by firm 2.

Recall from Chapter 2 that an increase in the number of firms in the market shifts the
market supply curve to the right (see Section 2.2). Now you can see why in more detail:
At each price, the market quantity supplied equals the quantities supplied by the firms
already in the market plus the quantities supplied by the new entrants. So, for example,
if a third firm entered the market illustrated in Figure 5.11, to create the market supply
curve you would add the quantity supplied by the third firm at the price of $20, at the
price of $30, at the price of $60, and at all other prices to the quantities supplied by the
first two firms already in the market. Conversely, a decrease in the number of firms in
the market shifts the supply curve to the left: At each price, the market quantity supplied
is less because the quantities supplied by the firms that exit are no longer included.

Price and cost (dollars per
gallon of maple syrup)

Quantity (gallons of maple
syrup per year)

$60

$10

5,000 6,0003,000 4,0001,000 2,000

$20

$30

$40

$50

0

SMC2 5 s2MC1 5 s1

B

C

A

Figure 5.11 The Short-Run
Market Supply Curve

At a price of $20 per gallon,
firm 1 produces 1,000 gallons
and firm 2 produces 2,000
gallons, for a total market
supply of 3,000 gallons
(point A). At a price of $30 per
gallon, firm 1 produces 1,500
gallons and firm 2 produces
2,500 gallons so the market
supply is 4,000 gallons
(point B). At any price, the
market supply equals the
sum of the quantities supplied
by all of the firms in the
market.

M05_BLAI8235_01_SE_C05_pp186-226.indd 206 25/08/17 12:34 PM

Amount of Profit and Shutting Down at a Plywood Producer

Suppose that you are a manager at a perfectly competitive producer of plywood similar
to Nashville Plywood, a plywood producer located in Nashville, Tennessee. The following
figure shows your marginal cost curve (MC), average total cost curve (ATC), and average
variable cost curve (AVC).

a. At what price or prices do you make an economic profit?

b. At what price or prices do you make a competitive return?

c. At what price or prices do you incur an economic loss?

d. Below what price do you shut down the company?

Answer

a. At any price greater than $3,000 per thousand square feet of plywood, you make an
economic profit because P 7 ATC .

b. At the price of $3,000 per thousand square feet of plywood, you make a competitive
return because P = ATC .

c. At any price less than $3,000 per thousand square feet of plywood, you incur an
economic loss because P 6 ATC .

d. At any price less than $2,000 per thousand square feet of plywood, you shut down
the company because P 6 AVC .

SOLVED
PROBLEM

Price and cost (dollars per thousand
square feet of plywood)

Quantity (thousands of square
feet of plywood per day)

$6,000

$7,000

$1,000

50 6030 4010 20

$2,000

$3,000

$4,000

$5,000

0

MC ATC

AVC

5.2 Short-Run Profit Maximization in Competitive Markets  207

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208  CHAPTER 5 Perfect Competition

5.3 Long-Run Profit Maximization
in Competitive Markets

Learning Objective 5.3 Describe the long-run adjustments that managers in
perfectly competitive markets make to maximize profit.

In the short run, managers maximize their firm’s profit, but they are limited because
at least one input is fixed. In the long run, however, all of a firm’s inputs are variable,
which provides managers with additional options. Even managers who have maxi-
mized short-run profit might have an incentive to alter the quantity they use of a
newly variable input to further increase their firm’s profit.

Long-Run Effects of an Increase in Market Demand
The market as a whole and the managers of the individual firms within it all respond
to a change in market demand. As you will see, the long-run market adjustments
following a change in demand force individual managers to make further responses
in order to continue to maximize profit.

The Firm’s Adjustment to an Increase in Market Demand
Figure 5.12 helps illustrate the adjustments managers make in response to an
increase in market demand. Initially, the market demand curve is D0, and the
market supply curve is S; Happy Tree’s short-run marginal cost curve is MC0, its
short-run average total cost curve is ATC0, its long-run marginal cost curve is
LMC, and its long-run average cost curve is LAC. Recall from Chapter 4 that
these long-run curves reflect the marginal cost and average cost in the long run
after the managers have made adjustments to all inputs (see Section 4.4). For clar-
ity in illustrating the long-run marginal cost curve, assume that the LAC is
U-shaped, with a single minimum point. The LMC intersects the minimum point
on the LAC.

With demand curve D0, the price of maple syrup is $15 per gallon. This price
means Happy Tree’s demand and marginal revenue curve is d0 = MR0, so Happy
Tree’s managers maximize profit by producing 1,500 gallons of maple syrup. For
reasons that will become clear shortly, assume that Happy Tree is initially producing
at the minimum point on the LAC.

Suppose that the market demand for maple syrup permanently increases to D1,
so that the price of maple syrup rises to $30 per gallon. Happy Tree’s demand and
marginal revenue curve shifts upward to d1 = MR1. The managers’ short-run
response is to boost production to 2,000 gallons by employing more variable inputs
and moving upward along the short-run marginal cost curve. At 2,000 gallons, the
short-run marginal cost (MC0) is $30, which equals the new marginal revenue
(MR1). Because the short-run marginal cost equals the marginal revenue, marginal
analysis shows that Happy Tree’s managers have maximized their short-run profit.
Indeed, Happy Tree is now making an economic profit.

In the short run, the managers cannot change the quantity of fixed inputs they
use, so the short-run marginal cost curve remains MC0, and the short-run profit-
maximizing quantity is 2,000. The profit-maximizing long-run quantity is the amount
at which the long-run marginal cost equals the marginal revenue. Figure 5.13 shows
that Happy Tree’s LMC equals marginal revenue when it produces 2,500 gallons,

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5.3 Long-Run Profit Maximization in Competitive Markets  209

which means that if Happy Tree’s managers expect the price to remain at $30 per
gallon for a sufficient period of time, they can increase the firm’s profit by increasing
the scale of its operations. In the long run, the managers can buy more of the inputs
that are fixed in the short run, perhaps by buying more sugar maple trees and
increasing the size of the sugar house (the plant in which the sap is boiled) to move
along the LAC and minimize the average cost of producing its 2,500 gallons. With
the increase in the scale of operations, Figure 5.13 shows that the new short-run
average total cost curve (ATC1) allows production of 2,500 gallons at the minimum
long-run average cost for this quantity, $21 per gallon. Corresponding to the new
average total cost curve is the new short-run marginal cost curve (MC1). By produc-
ing 2,500 gallons, as long as the price remains equal to $30, the newly expanded
Happy Tree maximizes its short-run profit (because MR1 = MC1) and its long-run
profit (because MR1 = LMC). In other words, Happy Tree is not only making an
economic profit (because P 7 ATC) but also making the largest possible economic
profit when the price is $30 per gallon.

Price (dollars per gallon
of maple syrup)

Quantity (millions of gallons
of maple syrup per year)

$30

$35

$5

3.02.0 2.51.0 1.5

$10

$15

$20

$25

0

S

D1D0

Price and cost (dollars per
gallon of maple syrup)

Quantity (gallons of maple
syrup per year)

$30

$35

$5

2,5001,500 2,000500 1,000

$10

$15

$20

$25

0

MC0 ATC0 LMC

LAC

d0 5 MR0

d1 5 MR1

Figure 5.12 A Firm’s Short-Run Adjustment to an Increase in Demand

Initially, the demand curve is D0, and
the equilibrium price is $15 per gallon.
At this price, in part (b) Happy Tree’s
demand and marginal revenue curve
is d0 = MR0, and Happy Tree produces
1,500 gallons. The firm’s owners
make a competitive return because
P = ATC .

When the demand increases to D1, part (a) shows that the price
rises to $30 per gallon. Happy Tree’s demand and marginal revenue
curve shifts upward to d1 = MR1. The managers maximize profit by
producing 2,000 gallons, where the short-run marginal cost curve,
MC0, intersects the new marginal revenue curve, MR1. Happy Tree
now makes an economic profit because P 7 ATC .

(a) Before the Increase in Market Demand (b) A Firm’s Short-Run Response to an Increase in Market Demand

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210  CHAPTER 5 Perfect Competition

The Market’s Adjustment to an Increase in Market Demand
After Happy Tree Maple Syrup has adjusted the scale of operations so its average
total cost curve is ATC1, its managers are satisfied. The firm is maximizing its profit,
and unless something else changes, the managers foresee making no further changes.
Unfortunately for them, in a competitive market further change outside their control
can and does occur.

In Figure 5.13, Happy Tree is making an economic profit. Presumably all other
firms in the market are making an economic profit as well. The economic profit in
the market for maple syrup attracts entrepreneurs who are always seeking new
markets with the potential for an economic profit. As you learned in Section 5.1, a
perfectly competitive market has no barriers to entry, so entrepreneurs flock to the
syrup market. As new firms enter, the market supply curve shifts to the right, lower-
ing the price. How low the price goes depends on whether the entry of the new
firms affects the other firms’ costs.

Entry That Does Not Affect Firms’ Costs To start, assume that the entry of new
firms has no effect on other firms’ costs and that the firms have identical costs. The
question remains: How low will the price go? As long as there is an economic profit

Price and cost (dollars per
gallon of maple syrup)

Quantity (gallons of maple
syrup per year)

$30

$45

$40

$35

$5

3,0002,5001,500 2,000500 1,000

$10

$15

$20

$25

0

MC1

ATC1LMC

LAC

d1 5 MR1

Figure 5.13 A Firm’s Long-Run Adjustments

If the managers believe the price will remain $30 for an extended period of time, they
increase the scale of production to reduce costs. The short-run average total cost curve
and short-run marginal cost curve become ATC1 and MC1, respectively. The firm now
maximizes its profit by producing 2,500 gallons, where its new MC1 curve crosses the
MR1 curve. The firm has maximized its short-run and long-run economic profit because it
is producing 2,500 gallons, the quantity that sets its short-run marginal cost, MC1, and
its long-run marginal cost, LMC, equal to its marginal revenue MR1. It is producing this
quantity at the lowest possible average cost since it is producing at a point on the
long-run average cost curve.

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5.3 Long-Run Profit Maximization in Competitive Markets  211

to be made, new firms continue to enter the market. Entry stops when the economic
profit is eliminated, which occurs when the firms in the market are making zero
economic profit. Figure 5.14 shows that this outcome occurs only when the price of
maple syrup is forced all the way back down to the initial price, $15 per gallon. At
this price, and after the firms have again adjusted the scale of their operations, you
see that the price equals the average total cost, which is the condition required for
zero economic profit.

Other than again changing the scale of their production, the existing firms, such
as Happy Tree, play no active role in this series of adjustments. Instead, profit-seeking
entrepreneurs cause these changes. Because there are no barriers to entry, the man-
agers of the firms already in the market are, as always, at the mercy of the market
and can do nothing but sit back and watch both their price and their profit fall.

Entry That Does Affect Firms’ Costs Suppose that as entrepreneurs start up new
maple syrup enterprises, the demand for land with sugar maple trees increases,
thereby increasing its price and hence its cost for maple syrup firms. In this case,
entry raises the costs for all firms. What is the long-run outcome in this case?

If the entry of new firms raises the costs for all firms, the path leading to the
long-run outcome is similar to what you just learned: Firms continue to enter until

Price (dollars per gallon
of maple syrup)

Quantity (millions of gallons
of maple syrup per year)

$30

$35

$5

3.02.0 2.51.0 1.5

$10

$15

$20

$25

0

S0

S1

D1

Price and cost (dollars per
gallon of maple syrup)

Quantity (gallons of maple
syrup per year)

$30

$35

$5

2,5001,500 2,000500 1,000

$10

$15

$20

$25

0

MC0
ATC0

LMC

LAC

d0 5 MR0

Figure 5.14 The Long-Run Outcome

(a) Increase in Market Supply

In the long run, entry of new firms
increases the supply and lowers the
price. If entry by new firms does not
affect the existing firms’ costs, new
firms continue to enter the market
until the price equals the initial
price, $15 per gallon, which occurs
when the supply curve is S1.

In the long run the price is the same as the initial price, so the
“new” demand and marginal revenue curve is d0 = MR0, exactly
the same as the initial demand and marginal revenue curve. Happy
Tree again adjusts the scale of production, so its average total cost
curve is ATC0 and its marginal cost curve is MC0. The company
maximizes profit by producing 1,500 gallons, the quantity at which
MC0 intersects MR0. The firm is making a competitive return because
P = ATC . Once Happy Tree and the other firms in the market make
only a competitive return, entry of new firms into the market stops.

(b) A Firm’s Response to an Increase in Market Supply

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212  CHAPTER 5 Perfect Competition

the economic profit is gone, at which point entry ceases. The difference is this: In
addition to lowering the price, entry raises all the firms’ average costs. The lower
price and the higher cost both squeeze the economic profit. Because of the rise in
average total cost, the price will not fall all the way back to the original level. It will
fall only until it equals the new, higher average total cost. Once the price equals the
higher average total cost, the economic profit is eliminated, which stops entry by
new firms.

Decrease in Market Demand
If the market demand for maple syrup decreases, the reverse scenario plays out. In
the short run, the equilibrium price falls, each firm’s demand and marginal reve-
nue curve shifts downward, and the managers decrease production as their firms
incur economic losses. As time passes, the economic loss causes some managers to
close their businesses. As firms close, the market supply decreases, which raises
the price. The higher price decreases the surviving firms’ economic losses. How-
ever, as long as firms incur an economic loss, from time to time some exit the
industry by closing. As those firms close, they further decrease the supply, raising
the price still higher. Ultimately, the price rises enough to eliminate the economic
losses. In the long run, there are fewer firms in the market, but each firm makes at
least a competitive return. The market equilibrium quantity decreases, but the
effect on the price depends on how the costs of the surviving firms are affected by
the exit of the firms that close. If the costs of the remaining firms are unaffected,
then in the long run the price will return to its original level, the price before the
decrease in market demand.

Change in Technology
In many industries, technological change is practically a day-to-day occurrence. But
even in industries in which it is less frequent, technological change can be critical to
managers. For example, managers and owners of strawberry farms are paying
attention to entrepreneurs who are developing robots (such as the Agrobot with
14 arms) to harvest the fruit. Many maple syrup producers have switched from the
traditional method of collecting sap (hanging a bucket on the tree under the tap and
then sending workers out to the trees to collect the buckets) to using long blue tubes
extending from the tree’s tap to a vacuum pump that extracts a larger amount of
sap from the tree and delivers it to a central collection station. These sorts of techno-
logical changes affect the market as a whole as well as the managerial decisions at
individual firms.

The costs of a sap-sucking vacuum pump and a strawberry picking robot are fixed
costs. Both technologies decrease the use of workers, which decreases the producers’
variable cost. The increase in fixed cost raises a firm’s short-run average total cost (ATC)
at low levels of production, but the decrease in variable cost lowers the short-run aver-
age total cost and long-run average cost (LAC) at larger levels of production. The larger
levels of production are more relevant because managers will adopt new technology if
it lowers the cost of producing their equilibrium output. Accordingly, Figure 5.15 shows
that when the managers at Happy Tree adopt the new sap extraction technology, the
firm’s cost curves shift downward from the initial cost curves labeled with a “0” to the
cost curves labeled with a “1.”

Before the advance in technology, Happy Tree’s demand and marginal revenue
curve, d0 = MR0, was horizontal at the market equilibrium price of $25 per gallon
of syrup. Happy Tree was maximizing profit at point A, where MR0 = MC0,

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5.3 Long-Run Profit Maximization in Competitive Markets  213

Price and cost (dollars per
gallon of maple syrup)

Quantity (gallons of maple
syrup per year)

$30

$35

$5

2,5001,500 2,000500 1,000

$10

$15

$20

$25

0

MC1

MC0

ATC1
LAC1

LAC0ATC0

d1 5 MR1

d0 5 MR0 A B

C

Figure 5.15 The Effect of New Technology

Initially, Happy Tree’s cost curves are those labeled with a “0” (MC0, ATC0, and LAC0),
and its demand and marginal revenue curve is d0 = MR0. Happy Tree maximizes its
profit at point A, producing 1,500 gallons of syrup at a price of $25 per gallon. Happy Tree
makes zero economic profit. The new technology shifts the cost curves downward to
those labeled with a “1” (MC1, ATC1, and LAC1). If Happy Tree is one of the early adopters
of the new technology, so that the price has not yet changed from $25 per gallon, Happy
Tree initially maximizes its profit at point B, producing 2,250 gallons of syrup. Happy Tree
makes an economic profit. As more firms adopt the new technology and as new firms
enter the market, the market supply of syrup increases, driving the equilibrium price
lower. Eventually, the price falls to $10 per gallon. At this price, Happy Tree’s demand and
marginal revenue curve is d1 = MR1. Happy Tree’s managers now maximize profit at
point C, producing 2,000 gallons of syrup at a price of $10 per gallon. Happy Tree makes
zero economic profit. Those firms that did not adopt the new technology have cost
curves that remain MC0, ATC0, and LAC0, incur an economic loss, and eventually close.

producing 1,500 gallons of syrup at a price of $25 per gallon and making zero
economic profit. After Happy Tree’s managers adopt the new technology, they
initially maximize profit at point B, where MR0 = MC1, producing 2,250 gallons
of syrup at a price of $25 per gallon and make an economic profit.

But the good times won’t last! As more syrup producers use the new technology,
the market supply of maple syrup increases, which drives the price down. Eventu-
ally, enough incumbent firms have adopted the technology and new firms, also
using the new technology, have entered so that the market supply increases, lower-
ing the price to $10 per gallon. In the long run, Happy Tree’s demand and marginal
revenue curve becomes d1 = MR1, and the managers maximize profit by producing
at point C, where MR1 = MC1. The long-run outcome is sadly familiar for managers
of competitive firms: In the long run, the firms make zero economic profit, so the
owners make only a competitive return. But firms that opt not to adopt the new tech-
nology face an even bleaker fate. Because they do not gain the advantage of lower
costs, they incur economic losses and eventually close.

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214  CHAPTER 5 Perfect Competition

The Long Run at a Plywood Producer

You are still a manager at a firm similar to Nashville Plywood. The following figure
illustrates your marginal cost, average total cost, long-run marginal cost, and long-run
average cost curves.

a. In the short run, if the price of ply-
wood is $6,000 per thousand square
feet of plywood, what quantity of
plywood will your firm produce?
Does your firm make an economic
profit at this quantity?

b. If all other plywood producers have
the same cost curves as yours, what
will be the price of a thousand
square feet of plywood in the long
run? If you stay open, will you
increase or decrease the scale of
operations?

c. What quantity of plywood will you
produce in the long run? Does your
firm make an economic profit at this
price?

Answer

a. As a manager, to maximize your profit you will produce the quantity of plywood
that sets the marginal revenue equal to the marginal cost. For a perfectly competi-
tive firm, the price equals the marginal revenue, so your marginal revenue equals
$6,000 per thousand square feet. Using the figure, the profit-maximizing quantity
is 70,000 square feet of plywood because at this quantity the marginal cost, MC,
equals the marginal revenue. Since at this quantity P 7 ATC , your firm makes an
economic profit.

b. In a perfectly competitive market, in the long run the price equals the minimum
of the long-run average cost curve, $3,000 per thousand square feet of plywood.
Your firm’s current scale of production has the average total cost curve (ATC)
shown in the figure. You will increase the scale of production and move to a new
short-run ATC with its minimum equal to $3,000 per thousand square feet of
plywood.

c. In the long run, in a perfectly competitive market the price equals the minimum of
the long-run average cost (LAC), and the firms’ owners make only a competitive
return. Accordingly, in the long run, your company will produce 60,000 square feet
of plywood and will make zero economic profit.

SOLVED
PROBLEM

Price and cost (dollars per thousand
square feet of plywood)

Quantity (thousands of square
feet of plywood per day)

$6,000

$7,000

$8,000

$1,000

50 1101009070 806030 4010 20

$2,000

$3,000

$4,000

$5,000

0

MC ATC LMC
LAC

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5.4 Perfect Competition
Learning Objective 5.4 Apply the theory of perfectly competitive firms and
markets to help make better managerial decisions.

Managers can use marginal analysis—which involves comparing the additional ben-
efit of an action to its additional cost—to determine the profit-maximizing quantity
to produce. Marginal analysis is an important tool in the arsenal of managers of
firms in perfectly competitive markets because they can use it to make a wide vari-
ety of decisions.

Applying Marginal Analysis
To maximize profit, a firm produces the quantity that sets MR = MC. Unfortunately,
as a manager, no one will give you graphs or equations showing the marginal reve-
nue and marginal cost. Instead, your discovery of the profit-maximizing amount of
output is often a trial-and-error process, in which you use your judgment and are
guided by marginal analysis. Apply the lessons you have learned: If you believe that
the marginal revenue from an additional unit exceeds its marginal cost, marginal
analysis indicates that you want to produce that unit because it will increase your
firm’s total profit. Conversely, if you estimate that the marginal revenue from the
unit is less than its marginal cost, you do not want to produce that unit because
doing so will decrease the total profit.

The profit-maximization rule, MR = MC, can be rewritten as MR – MC = 0.
Although the change is small, the managerial interpretation of this modified ver-
sion can be large when it comes to using your judgment about whether to pro-
duce additional units. The amount MR – MC is the additional profit or loss on
each unit of production. The profit-maximization rule means that you, as a man-
ager, should continue to produce additional units of output as long as they are
profitable, which will be the case as long as MR – MC is positive. You should
stop producing additional units when you hit the unit for which MR – MC = 0.
If you continue beyond that point, you will produce units for which MR – MC is
negative, which creates losses for your firm. Consequently, reworking the profit-
maximization rule in the form of MR – MC = 0 causes you to ask whether pro-
ducing a unit is profitable—in which case it should be produced—or unprofitable—
in which case it should not be produced. Sometimes simply deciding whether a unit
will be profitable is significantly easier than separately estimating the unit’s marginal
revenue and marginal cost.

Optimal Long-Run Adjustments
You can learn a critical managerial lesson from the analysis of long-run profit maxi-
mization: Use caution. If you are managing a competitive firm and economic times
are good (demand, price, and profit are all high), do not expect the good times to last
forever. Even if an increase in demand is permanent, the initial increase in price and
resulting economic profit are temporary. With no barriers to entry, new firms will
enter your market, force the price lower, and compete away your economic profit.

It is extremely easy for managers to believe that the price of their product will
remain high for much longer than it actually does. Optimistic managers who make
this mistake and elect to expand the scale of their firm may certainly later regret
their decision. For example, if the managers at Happy Tree think the price of
maple syrup will be $30 per gallon indefinitely, they might expand the firm’s scale
of production, shifting the average cost curve to ATC in Figure 5.16. With this

MANAGERIAL
APPLICATION

5.4 Managerial Application: Perfect Competition  215

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216  CHAPTER 5 Perfect Competition

Price and cost (dollars per
gallon of maple syrup)

Quantity (gallons of maple
syrup per year)

$30

$35

$5

2,5001,500 2,000500 1,000

$10

$15

$20

$25

0

MC

ATC

LAC

d0 5 MR0

d1 5 MR1

Figure 5.16 Overexpansion

If the managers believe the price will remain $30 for an extended period of time, they
increase the scale of production so that their (short-run) average total cost curve is
ATC, with short-run marginal cost curve MC. As long as the price remains equal to $30,
the firm produces 2,500 gallons and makes an economic profit because P 7 ATC . But if
the price rapidly falls to $15 per gallon and if the firm cannot quickly decrease the scale
of its production, the firm incurs an economic loss. It produces 2,000 gallons, the
quantity where MC is equal to the lower MR of $15. But the firm incurs an economic
loss because P 6 ATC . To eliminate the firm’s economic loss, the managers must
decrease the scale of production, thereby moving down the long-run average cost
curve. Eventually, with the revised, smaller scale of production, the firm eliminates its
loss and makes zero economic profit, so the owners make a competitive return.

expansion, when the price is $30 per gallon Happy Tree produces 2,500 gallons
and makes an economic profit because P 7 ATC. Once the entry of new firms
drives the price down to $15 per gallon, Happy Tree’s managers are in a less
happy place. In that case, the firm produces 2,000 gallons (the quantity where MC
equals the lower MR of $15 per gallon) and incurs an economic loss because
P 6 ATC. Indeed, Happy Tree will incur economic losses until it can decrease the
scale of its operations and move down its long-run average cost curve. If the firm
cannot make this change quickly enough, it faces the decision of whether to
remain open or close its doors.

This cautionary tale is not a mere theoretical curiosity. You have probably seen
industries and firms that expanded like rapidly growing weeds, only to regret the
expansion shortly thereafter. For example, in the face of high demand for ethanol,
in the mid-2000s ethanol producers expanded rapidly to take advantage of what
they expected would be a long-lasting high price. Additionally, there are virtually
no barriers to entry into this market, so new producers streamed in. By the time the
price collapsed in 2008, scores of producers had overexpanded and ultimately
about half of them declared bankruptcy. The same cycle—increased demand,
expanded scale and entry, and then a fall in price and numerous bankruptcies—
occurred again in 2012.

M05_BLAI8235_01_SE_C05_pp186-226.indd 216 25/08/17 12:35 PM

Revisiting How Burger King Managers Decided to Let
Chickens Have It Their Way

As you learned at the beginning of the chapter, in 2016 Burger King execu-
tives announced that the company would
switch to 100 percent cage-free eggs by
2025. The executives made the announce-
ment nine years in advance because
they wanted to give time for the market
for cage-free eggs to adjust and evolve.
In particular, they want enough time
(1) to enable more farmers to enter the
cage-free egg market, (2) to give farmers
already producing cage-free eggs time to
increase their scale of operation, and (3) to
allow technological innovations to occur.
All of these changes will lower the price of
cage-free eggs.

Figure 5.17 shows the effect of
these changes by illustrating the situa-
tion at a (hypothetical) typical cage-free
egg producer. Suppose that in 2016 the
price was $3.50 for a dozen cage-free
eggs. In this case, the demand and mar-
ginal revenue curve was d2016 = MR2016.
Farmers maximized their profit by pro-
ducing at point A. These farmers made
an economic profit because the price
exceeded the average total cost. Now
let’s consider each change that Burger
King’s managers anticipate:

• Entry. Economic profit attracts
entry by new producers. As time
passes, entry increases the supply,
decreasing the price. Assuming
that the farmers do not change the
scale of their production, eventually the price falls
to $3.00 per dozen, so that the farmers wind up
producing at point B, where the price equals the
minimum average total cost.

• Increase in scale. From point B, however, with
the passing of more time the farmers make fur-
ther adjustments by increasing the scale of their
production and moving down the long-run average
cost curve (LAC2016) to point C. Once farmers are
producing at point C, competition forces the price
of a dozen eggs to $2.50.

• New technology. Perhaps the largest change
Burger King’s managers are anticipating is new
technology to produce cage-free eggs. This tech-
nology—perhaps the discovery of ways to reduce
hen mortality or the development of robots to mon-
itor the chickens—will change the farmers’ long-run
average cost, shifting the LAC curve downward, as
shown in Figure 5.17, to LAC2025. In this case, com-
petition pushes the farmers to produce at point D,
the minimum point on LAC2025, and the price of a
dozen cage-free eggs is only $1.00.

Price and cost (dollars
per dozen eggs)

Quantity (eggs per year)

$3.00

$3.50

$4.00

$4.50

$5.00

$0.50

600,000300,000 500,000400,000100,000 200,000

$1.00

$1.50

$2.00

$2.50

0

MC2016

A

B

C

D

ATC2016

LAC2025

LAC2016

d2016 5 MR2016

Figure 5.17 Costs at a Cage-Free Egg Producer

When Burger King’s executives announced they would switch to
cage-free eggs, the price of cage-free eggs was $3.50 per dozen, and
farmers were producing at point A. Because the farmers were
making an economic profit, entry occurs, lowering the price to $3.00
per dozen and leading the farmers to produce at point B. From point
B, as more time passes the farmers increase the scale of their
production, moving down the LAC curve to point C and lowering the
price still more to $2.50 per dozen. Burger King’s managers also
hope that over the period of time during which they are switching to
cage-free eggs, technological progress occurs, so that the long-run
average cost curve shifts downward to LAC2025. In this happy state of
affairs, the farmers eventually produce at point D on the new LAC
curve, at which the price of a dozen cage-free eggs will be only $1.00.

Revisiting How Burger King Managers Decided to Let Chickens Have It Their Way  217

(Continues)

M05_BLAI8235_01_SE_C05_pp186-226.indd 217 25/08/17 12:35 PM

218  CHAPTER 5 Perfect Competition

Summary: The Bottom Line

5.1 Characteristics of Competitive Markets
• Perfectly competitive markets have five characteristics:

(1) The market includes a large number of buyers and
sellers, (2) the market has no barriers to entry, (3) each
firm produces a homogeneous product, (4) buyers and
sellers have perfect information about the price and prod-
uct characteristics, and (5) there are no transaction costs.

• Firms in perfectly competitive markets are price takers.

5.2 Short-Run Profit Maximization
in Competitive Markets

• A perfectly competitive firm’s demand is perfectly
elastic at the market price, so its demand curve is hori-
zontal at that price. Marginal revenue is the change in
total revenue divided by the change in quantity. A per-
fectly competitive firm’s marginal revenue equals the
market price, so the marginal revenue curve is hori-
zontal and is the same as the firm’s demand curve.

• A firm maximizes profit by producing the quantity
that sets marginal revenue equal to marginal cost
1MR = MC2. If MR 7 MC, managers can increase
their firm’s profit by increasing production. If
MR 6 MC, managers can increase profit by decreasing
production. The profit-maximizing price is the highest
price the firm can set and sell the quantity it produces.
For a firm in a perfectly competitive market, the profit-
maximizing price equals the market price.

• The firm (1) makes an economic profit if the price
exceeds the average total cost 1P 7 ATC2, (2) makes
zero economic profit (its owners make a competitive
return) if the price equals the average total cost
1P = ATC2, and (3) incurs an economic loss if the
price is less than the average total cost 1P 6 ATC2.

• Managers will keep their firm open—even if it is
incurring an economic loss—if the price exceeds the
average variable cost 1P 7 AVC2, but they will close
it if the price is less than the average variable cost
1P 6 AVC2.

• The firm’s short-run supply curve is the portion of its
marginal cost curve above the shut-down point, the
minimum of the average variable cost.

5.3 Long-Run Profit Maximization
in Competitive Markets

• In the long run, managers can adjust all inputs.
• If a firm in a perfectly competitive market is making an

economic profit, new firms enter the market, increase
the supply, lower the price, and compete away the eco-
nomic profit. In the long run, firms in a perfectly com-
petitive market are limited to making a competitive
return—that is, zero economic profit.

5.4 Managerial Application: Perfect
Competition

• Marginal analysis shows that you, as the manager of a
perfectly competitive firm, maximize profit by produc-
ing the units of output for which MR – MC is positive
and stopping when you reach the unit for which
MR – MC equals zero.

• If a price change is expected to last for a more
extended period, you might adjust the scale of your
firm’s production by changing your fixed inputs.
Any change in price will not be permanent, however,
so your scale of production should not be changed so
much that your firm incurs large economic losses
after the entry of firms moderates the price change.

Using insights from the analysis of perfectly competitive
markets, Burger King’s managers decided that rather than
switch immediately to cage-free eggs, they would slowly
switch over nine years. Burger King’s managers know that

during this extended period of time, changes in the com-
petitive market will lower the price of cage-free eggs. The
decision made by these executives increased Burger King’s
profit.

Key Terms and Concepts
Barrier to entry

Economic loss

Economic profit

Marginal revenue

Perfectly competitive market

Price takers

Short-run firm supply curve

Transaction costs

Revisiting How Burger King Managers Decided to Let Chickens
Have It Their Way (continued)

M05_BLAI8235_01_SE_C05_pp186-226.indd 218 11/09/17 10:46 AM

Questions and Problems

2.6 You are managing a perfectly competitive
landscaping firm. You have carefully calcu-
lated that the cost of mowing and tending
one additional yard is $25 and the price of
that work is $40. To increase your profit, what
decision should you make? Explain your
answer.

2.7 In the figure, if the price is $500 per unit, what is
the firm’s profit-maximizing price and quantity?
What is the amount of the firm’s economic profit
or loss?

2.8 Suppose that you are a manager of a firm like
Sproule Farms, a perfectly competitive grower
of sugar beets. The market price of sugar beets
is $50 per ton. The table has your total cost.
What is the profit-maximizing quantity of sugar
beets? What is the amount of your economic
profit or loss?

Questions and Problems  219

Price and cost
(dollars per unit)

Quantity (units per month)

$600

$100

2,500 3,0001,500 2,000500 1,000

$200

$300

$400

$500

0

ATC

AVC

MC

Quantity (tons) Total Cost (dollars)

5,000 $235,510

5,001 235,550

5,002 235,600

5,003 235,651

5,004 235,703

5,005 235,756

5.1 Characteristics of Competitive Markets
Learning Objective 5.1 Summarize the
conditions that make a market perfectly
competitive.

1.1 Which of the following firms compete in a per-
fectly competitive market or a market that
closely approximates perfect competition?
a. Verizon Wireless
b. Swaz Potato Farms
c. Alcoa Aluminum
d. Gucci Perfumes

1.2 Why does it make no sense for the managers of a
perfectly competitive firm to spend money on
advertising?

1.3 No matter how many soft drinks you buy, you
have no effect on the price of soft drinks. The
soft drink industry includes two very large pro-
ducers and several smaller ones. Is this industry
perfectly competitive? Explain your answer.

1.4 Give three examples of products or firms pro-
tected by barriers to entry. Describe the barrier
to entry for each example.

1.5 In a perfectly competitive market, no individual
producer can affect the price of the product. How,
then, is the price of the product determined?

5.2 Short-Run Profit Maximization
in Competitive Markets
Learning Objective 5.2 Use marginal analysis
to determine the profit-maximizing quantity
that a perfectly competitive firm produces in
the short run.

2.1 In your own words, explain the concept of mar-
ginal analysis, making sure to include the marginal
aspect of this rule.

2.2 What is the difference between a market demand
curve and a perfectly competitive firm’s demand
curve?

2.3 How does a perfectly competitive firm’s price com-
pare to its marginal revenue? How does its demand
curve compare to its marginal revenue curve?

2.4 What is the relationship between marginal cost
and total cost?

2.5 A perfectly competitive firm is producing the
quantity that sets its marginal revenue equal to
its marginal cost. Explain to this firm’s manag-
ers why producing more output or less output
would decrease the firm’s profit.

M05_BLAI8235_01_SE_C05_pp186-226.indd 219 15/09/17 2:50 PM

220  CHAPTER 5 Perfect Competition

2.14 You are managing a perfectly competitive dairy
farm, and sadly you have determined that your
firm is incurring an economic loss. You do not fore-
see any future changes in your costs or the price of
milk. Discuss all factors that influence your deci-
sion about whether to close or remain open.

2.15 “A manager of any firm that is paying out more
in costs than it is making in revenue should shut
down operations at once.” Is this advice sound?
Explain your answer.

2.16 You are the manager of a large, perfectly competi-
tive wheat farm. The price of wheat is $6 per
bushel. The table gives your total costs for different
quantities. What is the profit-maximizing quantity
of wheat? Carefully explain your answer.

Price and cost
(dollars per unit)

Quantity (units per day)

$100

100 12060 8020 40

$200

$300

$400

$500

0

ATC

AVC

MC

2.10 In a perfectly competitive market, the equilib-
rium market price for a good is $60 per unit, and
a firm has a marginal cost curve given by

MC = 10 + 0.25q

What is the firm’s profit-maximizing quantity
and price?

2.11 Your company just spent $5.0 million on a state-
of-the-art production facility. As a result, the
marginal cost of producing the product is

MC = 10 + 0.0001q

If the market is perfectly competitive and the
price is $50 per unit, how many units will you
produce? If the price falls to $25, how many
units will you produce?

2.12 A perfectly competitive firm’s marginal cost
curve is upward sloping but not vertical. If the
price of the product increases, in the short run is
it possible for the firm’s economic profit to
decrease (or for its economic loss to increase)?
Explain your answer.

2.13 In the figure, in the short run what is the lowest
price at which the firm will remain open? At
this price, what does the firm’s economic loss
per day equal?

5.3 Long-Run Profit Maximization
in Competitive Markets
Learning Objective 5.3 Describe the long-run
adjustments that managers in perfectly com-
petitive markets make to maximize profit.

3.1 In the long run, why does a firm in a perfectly
competitive market produce the quantity that
minimizes its long-run average cost?

3.2 What sort of profit does a perfectly competitive
firm make in the long run?

Price and cost (dollars
per ton of pellets)

Quantity (thousands of tons
of pellets per year)

$40

50 6030 4010 20

$80

$120

$160

0

ATCMC

Quantity (bushels
of wheat)

Total Cost (dollars)

100,000 $555,000
100,001 555,002
100,002 555,005
100,003 555,009
100,004 555,014
100,005 555,020

2.9 Suppose that you are a manager at a firm like
Yulong Machine Company, a perfectly competi-
tive producer of pellets used in biomass plants to
generate electricity. The price of a ton of pellets is
$120. In the figure, producing 30,000 tons of pel-
lets per year minimizes the average total cost of
producing the pellets. Does producing 30,000
tons maximize your firm’s profit? Explain your
answer.

M05_BLAI8235_01_SE_C05_pp186-226.indd 220 25/08/17 12:35 PM

a. If the price is $20 per bushel and the firm
stays open, in the short run what is the
firm’s profit-maximizing price and quan-
tity? Explain whether the firm makes an eco-
nomic profit or loss.

b. Will firms enter or exit the market? In the long
run, will the price rise, fall, or not change? If
there are no technological changes, what will be
the price in the long run? Explain your answers.

3.4 The market for paper is perfectly competitive.
Draw a demand and supply figure showing the
entire paper market and another figure for a
typical paper manufacturing firm with the long-
run average cost (LAC), average total cost (ATC),
marginal cost (MC), demand (d), and marginal
revenue (MR) curves showing the long-run out-
come. Presuming that an increase in the number
of firms does not affect the firms’ cost curves,
describe the short-run and long-run effects of an
increase in the market demand for paper.

3.5 The plywood market is perfectly competitive.
The demand for home construction increases,
increasing the demand for plywood. If the
increase in demand for plywood is permanent,
should the managers of a plywood firm increase
their firm’s capacity? Why or why not?

3.6 You are the manager of a bagel producer that is in a
perfectly competitive industry comprised of iden-
tical firms. The cost of flour used to produce bagels
decreases from $25 to $20 per hundred pounds.

Price and cost (dollars
per bushel of peaches)

Quantity (bushels of
peaches per year)

$10

10,0006,000 8,0002,000 4,000

$20

$30

$40

$50

0

LACATC
MC

a. In the short run, how do you respond to the
fall in the price of flour?

b. Describe the long-run adjustments that take
place in the market.

c. What long-run decisions will you make as
the manager of your firm?

3.7 Describe the long-run outcome for a competitive
wild rice producer and the competitive wild rice
industry. Now suppose that the demand for
wild rice increases.
a. Discuss the adjustments by the firm and the

industry.
b. What happens to the firm’s long-run eco-

nomic profit?
Now suppose that demand increases again but

that the government forbids entry by new wild
rice producers.
c. Discuss the adjustments by the firm and the

industry.
d. What happens to the firm’s long-run eco-

nomic profit?
e. Is the firm’s long-run economic profit higher

when entry is forbidden or when entry is
allowed?

f. What is the managerial lesson illustrated in
your answer to part e?

5.4 Managerial Application: Perfect
Competition
Learning Objective 5.4 Apply the theory of
perfectly competitive firms and markets to
help make better managerial decisions.

4.1 As a manager of a house painting firm like the
Queen Anne Painting Company, a perfectly com-
petitive firm in Seattle, Washington, you are maxi-
mizing your profit and are currently making an
economic profit. For simplicity, assume that you use
only capital and labor. You determine that at your
current production, your long-run average cost
curve is downward sloping; that is, if you increased
both your capital and your labor by the same pro-
portion, your long-run average cost would fall.
a. Draw a figure to illustrate your situation. In

your figure include short-run average total cost
(ATC) and marginal cost (MC) curves, a long-
run average cost (LAC) curve, and a demand
and marginal revenue 1d = MR2 curve.

b. Using your figure, do you want to increase the
scale of your production? Explain your answer.

4.2 Managers of perfectly competitive firms must be
cautious when deciding to permanently expand
(or contract) the scale of production. What fac-
tors should go into the decision to expand the
scale of production? Which factors make it neces-
sary to proceed with caution?

Questions and Problems  221

3.3 Peach growing is perfectly competitive. For sim-
plicity, suppose that all peach growers have the
same cost curves. In the figure, each grower’s
initial average total cost curve is ATC, its initial
marginal cost curve is MC, and its long-run
average cost curve is LAC.

M05_BLAI8235_01_SE_C05_pp186-226.indd 221 25/08/17 12:35 PM

222  CHAPTER 5 Perfect Competition

MyLab Economics Auto-Graded Excel Projects
5.1 The Weinandt Family Farm in Wynot, NE raises

livestock and grows crops. Commonly grown
crops in Nebraska are corn and soybeans. Sup-
pose you are helping a farm similar to the Wein-
andt Farm make decisions about how much
corn to grow this year. As an agricultural prod-
uct, the market for corn meets the requirements
of a perfectly competitive market.
a. Using the market data provided, create a

market supply and demand graph.
b. What are the market equilibrium price and

quantity?
c. Using the firm cost and quantity data, find

FC, VC, ATC, AFC, AVC, and MC. Graph
ATC, AFC, AVC, and MC.

d. Based on your answers in part c, between
which quantities is ATC minimized?

e. Based on your answers in part c, between
which quantities should the farm aim to
produce?

f. Using the lower of these two quantities, cac-
ulate TR, TC, and the firm’s economic profit
or loss.

g. Will the farm decide to grow corn or leave
the fields bare? Explain your answer.

h. Will farms enter this market, leave the mar-
ket, or remain constant? Explain your
answer.

5.2 The Weinandt Family Farm in Wynot, NE raises
livestock and grows crops. Commonly grown
crops in Nebraska are corn and soybeans. Sup-
pose you are helping a farm similar to the Wein-
andt Farm make decisions about how much
corn to grow this year. As an agricultural prod-
uct, the market for corn meets the requirements
of a perfectly competitive market.
The original market demand (Qd1) and mar-
ket supply (Qs) are given. Suppose the market
demand shifts to Qd2 because, in addition to
being used as a food product, corn is now used
for ethanol production.
a. Using the market data provided, create a

market supply and demand graph which
includes both Qd1 and Qd2.

b. What are the market equilibrium price and
quantity before and after the demand shift?

Accompanies problem 5.1.

M05_BLAI8235_01_SE_C05_pp186-226.indd 222 25/08/17 12:35 PM

c. Using the firm cost and quantity data, find
FC, VC, ATC, AFC, AVC, and MC.

d. Based on your answers in part c and b,
between which quantities should the farm
aim to produce before and after the demand
shift?

e. Using the lower of these two quantities, calcu-
late TR, TC, and the firm’s economic profit or
loss before and after the change in demand.

f. Will farms enter this market, leave the mar-
ket, or remain constant after the demand
shift? Explain your answer.

MyLab Economics Auto-Graded Excel Projects  223

M05_BLAI8235_01_SE_C05_pp186-226.indd 223 25/08/17 12:35 PM

224

The most important result in Chapter 5 is the profit-maximization rule, MR = MC. Deriving
this rule using calculus is straightforward. We can start with the definition of marginal
revenue.

A. Marginal Revenue
Marginal revenue is the change in total revenue (TR) that results from a change in quantity (q),
or using calculus, marginal revenue (MR) is defined as

MR =
dTR
dq

A5.1

Total revenue equals price multiplied by quantity, P * q. For a perfectly competitive firm,
the price is the same no matter the quantity the firm produces. Consequently, for a perfectly
competitive firm,

dTR
dq

=
d1P * q2

dq
= P A5.2

Combining Equations A5.1 and A5.2 shows that for a perfectly competitive firm MR = P.

B. Maximizing Profit
Managers want to determine the amount of output that maximizes the firm’s profit. The profit
equals total revenue minus total cost, or

Profit1q2 = TR1q2 – TC1q2
To maximize profit, take the derivative of Profit(q) with respect to q, and set it equal to zero:

dProfit

dq
=

dTR
dq


dTC
dq

= 0 A5.3

Recall from Chapter 4 that the marginal cost (MC) equals the derivative of total cost (TC)
with respect to quantity, or MC = dTC>dq. Accordingly, in Equation A5.3, dTR>dq is MR and
dTC>dq is MC, so the equation can be rewritten as

MR – MC = 0 1 MR = MC

which is precisely the same result presented in the profit-maximization rule in Section 5.2 of
the chapter.

C. Maximizing Profit: Example
Suppose that you are a manager of a company like B.W. Recycling, a perfectly competitive
gold scrap recycler near Fort Lauderdale, Florida. Your company has daily fixed cost of $18,000
and variable cost given by VC = 0.05q3 – 4.5q2 + 600q. The total cost is equal to the sum of
the variable cost plus the fixed cost, or TC = 0.05q3 – 4.5q2 + 600q + 18,000. Using the power
rule to differentiate the total cost with respect to q gives your marginal cost function:

MC = 0.15q2 – 9.0q + 600 A5.4

CHAPTER 5 APPENDIX

The Calculus of Profit Maximization for Perfectly
Competitive Firms

M05_BLAI8235_01_SE_C05_pp186-226.indd 224 25/08/17 12:35 PM

The average total cost (ATC) equals TC>q, so the average total cost function is

ATC = 0.05q2 – 4.5q + 600 +
18,000

q
A5.5

If the market price for the recycled gold is $1,005 per ounce, then P = MR = $1,005.
To maximize profit, you must produce the quantity at which MR = MC, or using Equation A5.4

1,005 = 0.15q2 – 9.0q + 600 1 0 = 0.15q2 – 9.0q – 405 A5.6

Using the quadratic formula to solve the second part of Equation A5.6, the profit-maximizing
quantity is 90 ounces of gold.1 Of course, the profit-maximizing price equals the market price,
$1,005 per ounce.
To determine the economic profit or loss, using Equation A5.5 and the price we can first
calculate the economic profit per ounce as P – ATC, or

1,005 – c 10.05 * 9022 – 14.5 * 902 + 600 + 18,000
90

d = 1,005 – 800 = 205

The total economic profit equals the profit per ounce multiplied by the quantity of ounces, or

$205 * 90 = $18,450

Figure A5.1 illustrates these calculations. The MC curve is based on Equation A5.4, and the
ATC curve is based on Equation A5.5. The demand and marginal revenue curve is horizontal
at $1,005 per ounce. The profit-maximizing quantity is 90 ounces per day because this is the
quantity at which MR = MC. The price is $1,005 per ounce. Figure A5.1 shows that at the
profit-maximizing quantity, the firm’s average total cost is $800 per ounce. The firm’s eco-
nomic profit is therefore the area of the green rectangle, which is equal to $18,450.

1 The other root of Equation A5.6 is −30, which is meaningless because the quantity must be positive.

Price and cost (dollars
per ounce of gold)

Quantity (ounces of gold per day)

$1,200

$1,400

$200

150 18090 12030 60

$400

$600

$800

$1,000

0

MC
ATC

d 5 MR

Economic
profit
$18,450

Figure A5.1 Profit-Maximizing Quantity, Price, and
Economic Profit

The profit-maximizing quantity is the quantity at
which MR = MC , which is 90 ounces of gold per
day. The profit-maximizing price is equal to the
market price, $1,005 per ounce. The economic profit
per ounce equals the price per ounce minus the
average total cost of producing an ounce, or
P – ATC . At the profit-maximizing quantity, the
average total cost is $800 per ounce, so the firm’s
economic profit per ounce is $1,005 – $800, or
$205 per ounce. The firm’s total economic profit
equals the economic profit per ounce multiplied by
the number of ounces, $205 per ounce * 90 ounces,
which equals the area of the green rectangle in the
figure, $18,450.

CHAPTER 5 APPENDIX The Calculus of Profit Maximization for Perfectly Competitive Firms  225

M05_BLAI8235_01_SE_C05_pp186-226.indd 225 25/08/17 12:35 PM

Calculus Questions and Problems
A5.1 Suppose that Nuñez Consulting offers management

consulting services in a perfectly competitive mar-
ket and that the total cost the firm incurs when pro-
viding consulting services is

TC1q2 = 4,500 + 5q2

where q is the number of hours of consulting ser-
vices provided by Nuñez Consulting.
a. What is the average total cost of providing con-

sulting services as a function of the number of
hours of consulting services provided?

b. The price of consulting services is $500 per
hour. At what quantity is Nuñez Consulting’s
profit maximized? What is the maximum
amount of economic profit that Nuñez Consult-
ing can earn in this market?

c. Suppose that the price of a consulting services
rises to $600 per hour. At what quantity is Nuñez
Consulting’s profit maximized after this price
change? What is the maximum amount of eco-
nomic profit that Nuñez Consulting can earn?

A5.2 Suppose that Laylita sells empanadas at a perfectly
competitive local farmers’ market and that her total
cost of producing an empanada is

TC1q2 = 40 + 0.1q2 – 0.2q
where q is the total number of empanadas that she

produces.
a. What is the average total cost of producing

empanadas as a function of the quantity of
empanadas produced?

b. At what quantity, q*, is the average total cost of
producing an empanada minimized? What is
the value of the average total cost at q*?

c. The price of an empanada is $4.20. What quan-
tity of empanadas should Laylita produce to
maximize her profit? If she remains open, what
is her economic profit or loss?

d. Suppose that the price of an empanada falls to
$3. What quantity of empanadas should Laylita
produce to maximize her profit? If she remains
open, what is her economic profit or loss?

A5.3 Gerardo’s Geraniums is a flower farm, specializing
in the production of cut geraniums. The cut gera-
nium market is a perfectly competitive market.
Gerardo has hired an economist to determine his
total cost function, which the economist reports as

TC1q2 = 30,000 + 0.0025q2

where q is the number of cut flowers Gerardo’s
Geraniums produces.

a. What is Gerardo’s Geraniums’ marginal cost of
supplying an additional cut geranium?

b. Suppose that the price of a cut geranium is
$2.50. How many cut geraniums will Gerardo’s
Geraniums supply?

c. Suppose that the price of a cut geranium rises
to $3.00. How many cut geraniums will Gerar-
do’s Geraniums supply?

A5.4 Jessica is a 10-year-old entrepreneur. She produces
lemonade in her family’s kitchen and sells that lem-
onade at a stand that she sets up in front of her
family’s house each Saturday afternoon. Jessica
lives in a neighborhood with many other entrepre-
neurial children, all selling identical lemonade.
Therefore, along Jessica’s street, the lemonade mar-
ket is perfectly competitive. The price of a cup of
lemonade on Jessica’s street is $2. Jessica’s total cost
of setting up her lemonade stand and producing
lemonade is

TC1q2 = 10 + 0.025q2

where q is the number of cups of lemonade Jessica
produces.
a. What is Jessica’s marginal cost of producing an

additional cup of lemonade?
b. What is Jessica’s marginal revenue of produc-

ing an additional cup of lemonade?
c. What is the profit-maximizing number of cups

of lemonade? What is Jessica’s economic profit
at this quantity?

A5.5 Larry’s Lasers is a laser hair-removal firm that oper-
ates in the perfectly competitive laser hair-removal
market. Dr. Larry specializes in removing women’s
facial hair, and his total cost of performing these
procedures is

TC1q2 = 200,000 + 5q2 – 100q
where q is the number of facial hair removal proce-

dures he performs.
a. What is Larry’s Lasers’ marginal cost of per-

forming an additional facial hair removal
procedure?

b. Suppose that the price of a facial hair removal
procedure is $2,300. How many facial hair
removal procedures does Larry perform?

c. If the price of a facial hair removal procedure is
$2,300, does Larry make an economic profit? If
so, how much?

d. What is the long-run price of a facial hair
removal procedure?

226  CHAPTER 5 APPENDIX The Calculus of Profit Maximization for Perfectly Competitive Firms

M05_BLAI8235_01_SE_C05_pp186-226.indd 226 25/08/17 12:35 PM

 227

Premature Rejoicing by the Managers at KV Pharmaceutical

A pharmaceutical company typically spends approx-imately 10 years and over $1 billion to research,
develop, and test a potential drug in order to prove its safety
and effectiveness to the federal Food and Drug Administra-
tion (FDA). The company can apply for a government pat-
ent for exclusive rights to sell the drug for 20 years from
the date of filing, though sometimes the company can gain
extra time if the FDA is slow to approve the drug.

An exception to this general policy is the orphan drug
policy. Orphan drugs are legally defined as drugs devel-
oped for diseases that affect 200,000 or fewer individuals
in the United States. Under this policy, a pharmaceutical
company that receives FDA approval has a seven-year
period of marketing exclusivity even if the company does
not have a patent on the drug.

In 1956, the FDA approved hydroxyprogesterone
caproate to treat various issues during pregnancy, including
premature birth. After the patent expired, the market evolved.
From 2000 until 2011, a number of different compounding
pharmacies (smaller companies that manufacture drugs for
specific individuals) made the drug under the name 17P. In this
competitive market, the price for a shot of 17P was approxi-
mately $15. To prevent premature birth, typically doctors pre-
scribe weekly shots for the last 20 weeks of the pregnancy.

Studies conducted after 2000 indicated that 17P
helped prevent subsequent premature births in women
with a history of premature births. KV Pharmaceutical
used these studies to gain orphan drug designation and
then conducted its own test with 463 women, which con-
firmed the findings. KV Pharmaceutical submitted these
studies to the FDA. The March of Dimes, a charity group
concerned with preventing premature births, lobbied the
FDA for quick approval of KV’s submission. Based on KV’s
study, the FDA granted the firm the standard seven-year
period of orphan-drug marketing exclusivity for its drug,
which the firm called Makena. The FDA’s decision effec-
tively made the firm a monopoly. Believing that the FDA
ruling gave KV Pharmaceutical a seven-year monopoly, its
managers celebrated, and its stock price doubled. Manag-
ers set the price at $1,500 per dose, up approximately 100
times from the $15 competitive price for 17P.

How did the managers at KV Pharmaceutical determine
the price of their drug? How can they ensure that it is the
profit-maximizing price? This chapter will show you how to
answer these key questions about KV Pharmaceutical and
other monopolies. At the end of the chapter, we revisit the
situation faced by KV Pharmaceutical’s managers and show
how they made a fundamental error in their pricing process.

Sources: Courtney Hutchison and ABC News Medical Unit, “KV Pharma Cuts Price of Costly Premature Birth
Prevention Drug,” ABC News. April 1, 2011; Yesha Patel and Martha M. Rumore, “Hydroxprogesterone Caproate
Injection (Makena) One Year Later,” Pharmacy and Therapeutics, July 2012, pp. 404–411; Tom Schoenberg, “K-V
Pharmaceutical Loses FDA Lawsuit over Makena Drug,” Bloomberg, September 6, 2012.

Monopoly and Monopolistic
Competition
Learning Objectives
After studying this chapter, you will be able to:

6.1 Explain the relationship between a monopoly’s demand curve and its marginal revenue curve.
6.2 Discuss how managers of a monopoly can determine the quantity and price that

maximize profit and how they compare to those of a perfectly competitive firm.
6.3 Describe how managers of a dominant firm determine the quantity and price that

maximize profit.
6.4 Explain how managers of a monopolistically competitive firm determine the quantity and

price that maximize profit.
6.5 Apply what you have learned about monopolies, dominant firms, and monopolistically

competitive firms to make better managerial decisions.

6CHAPTE
R

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228  CHAPTER 6 Monopoly and Monopolistic Competition

Introduction
In Chapter 5, you learned that the price-taking behavior of a firm in a perfectly compet-
itive market severely limited its managers’ pricing responsibilities. In this chapter, you
will see that a manager’s pricing responsibilities increase when a firm has market power,
the ability to determine the price of its good or service. Later chapters will examine
different pricing schemes that managers of firms with market power can use. First,
however, you need to understand the economic fundamentals of managerial decisions
in these firms. To explain these fundamentals, Chapter 6 includes five sections:

• Section 6.1 explains the conditions that define a monopoly market and compares a monop-
oly’s demand curve and marginal revenue curve to those of a perfectly competitive firm.

• Section 6.2 explains how managers of monopolies can use marginal analysis to determine
the profit-maximizing quantity and price and compares these results to those in a perfectly
competitive market.

• Section 6.3 explains why managers of dominant firms face the same decisions as those of
monopolies—but with an added wrinkle: They must take into account the actions of all of
the competitive firms in the market.

• Section 6.4 examines how monopolistically competitive firms compete with a large number
of other firms, all producing similar but somewhat differentiated products. Because of a
limited degree of market power, managers of these firms make profit-maximizing decisions
similar to those of monopolies, but the amount of economic profit differs.

• Section 6.5 applies what you have learned about monopolies, dominant firms, and monop-
olistically competitive firms to help you make better managerial decisions.

6.1 A Monopoly Market
Learning Objective 6.1 Explain the relationship between a monopoly’s
demand curve and its marginal revenue curve.

Chapter 5 covered perfectly competitive markets and perfectly competitive firms.
Now it is time to turn your attention to monopoly markets and monopoly firms to
explain how they determine their profit-maximizing price and quantity. The first
step is understanding the definition of a monopoly. Then you will learn how a firm’s
monopoly position affects its demand and marginal revenue.

Defining Characteristics of a Monopoly Market
It is tempting to define a monopoly market as a market with a single seller. Although
this aspect is the most prominent characteristic, it is not the only one. A more com-
plete definition of a monopoly market includes three parts:

1. Single seller. There is only one firm in the market, which gives it immense
market power. As noted in the introduction, market power is the ability of a
firm to determine the price of its good or service. By definition, perfectly com-
petitive firms have no market power, but monopoly firms do—they are free to
decide the price of their product. Essentially, the managers of a monopoly firm
set the price in a monopoly market, while the market sets the price in a perfectly
competitive market.

2. No close substitute. The good or service a monopoly produces has no close sub-
stitutes. This characteristic is necessary to adequately define the market. For

Market power The ability
of a firm to determine the
price of its good or service.

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6.1 A Monopoly Market  229

instance, you cannot assert that McDonald’s is a monopoly at a particular inter-
section if there is a Burger King one block away. Both McDonald’s and Burger
King sell their own unique versions of a hamburger, but most consumers find
them very close substitutes. McDonald’s and Burger King are examples of firms
in monopolistic competition, a market structure you will learn more about in
Section 6.4. On the other hand, Roche Holdings’ drug Herceptin is a monoclonal
antibody used to treat certain breast and gastric cancers, and there is no other
drug that has a similar genetic target. The market for Herceptin meets this part
of the definition of a monopoly market.

3. Insurmountable barriers to entry. As you learned in Chapter 5, a barrier to entry is
any factor that makes it difficult for new firms to enter a market. In a monopoly,
the barriers to entry are insurmountable, which is why there is only one firm in the
market. Patents, trademarks, copyrights, and significant cost advantages for a firm
already in the market can serve as barriers to entry. For example, the market for
Herceptin is a monopoly because Roche Holdings has a patent that prevents other
pharmaceutical or biotech companies from producing the drug. As long as the
patent remains in force, it is an insurmountable barrier to entry. Barriers to entry
ensure there is only one firm in the market. They play a crucial role in the firm’s
long-run outcome. You will learn more about their long-run role in Section 6.2.

So a complete definition of a monopoly market is a market with only a single seller,
which is producing a product that has no close substitute and is protected by an
insurmountable barrier to entry.

Demand and Marginal Revenue for a Monopoly
Although a monopoly and a perfectly competitive firm differ in important character-
istics, the managers’ ultimate goal in both firms is the same: to maximize profit. Man-
agers of a perfectly competitive firm control only the quantity they produce because
the price is determined by the market. As you learned in Chapter 5, marginal analysis
helps guide these managers to the profit-maximizing quantity. Managers of a monop-
oly might appear to have a more difficult task because they must determine both the

Monopoly market A
market with only a single
seller, which is producing a
product that has no close
substitute and is protected
by an insurmountable
barrier to entry.

You are a government official responsible for monitoring the behavior of monop-
olies to discover violations of antitrust laws. For a small fee, airlines can fly in and
out of the airport in Rochester, New York. Say that Delta Airlines is the only carrier
flying from Rochester to LaGuardia Airport in New York City, but JetBlue Airways
flies from Rochester to JFK International, also in New York City. Do you decide
that Delta Airlines is a monopoly? Explain your answer.

Answer
Delta Airlines is not a monopoly for two reasons. First, flying to JFK International
Airport is a close substitute for flying to LaGuardia Airport. Second, there is no
insurmountable barrier to entry: If another airline wants to fly from Rochester to
LaGuardia Airport, it can do so at only a small expense.

DECISION
SNAPSHOT Is Delta Airlines a Monopoly?

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230  CHAPTER 6 Monopoly and Monopolistic Competition

quantity to produce and the price to charge. It turns out, however, that marginal anal-
ysis is a powerful tool for monopoly managers as well. Of course, to use marginal
analysis, the monopoly’s managers must know the firm’s marginal revenue and
marginal cost. Let’s begin by examining marginal revenue.

Monopoly’s Demand and Marginal Revenue Curves
In your study of a perfectly competitive firm, you had to distinguish between the
firm’s demand curve and the market demand curve (see Section 5.2). You do not
need to make this distinction for a monopoly. Because the monopoly is the only firm
in the market, the monopoly’s demand curve is the same as the market demand
curve. For example, Roche Holdings’ patent on Herceptin makes it the only com-
pany allowed to sell Herceptin, so the market demand curve for Herceptin is also
Roche Holdings’ demand curve for it.

Suppose that you are a manager for a pharmaceutical company that also has a
patent on a drug. Similar to Roche Holdings, your company is the only one allowed
to sell that drug. Figure 6.1 shows the (hypothetical) market demand curve for this
drug. Because you are the only seller, the market demand curve is also your firm’s
demand curve.

Even with the difference in demand, marginal revenue is calculated for a monop-
oly firm in the same way as for a perfectly competitive firm: the change in total reve-
nue resulting from a change in quantity sold, or

MR =
∆TR
∆Q

Although the definition of marginal revenue is the same for a perfectly competitive
firm and a monopoly, a monopoly’s marginal revenue curve differs from that of a per-
fectly competitive firm because of the differences in their demand curves. Table 6.1
shows some data from points on the demand curve for your drug from Figure 6.1.

D

Price (thousands of
dollars per treatment)

Quantity (thousands of
treatments per year)

$90

$0

$10

$20

35030025020015010050

$30

$40

$50

$60

$70

$80

2$20

2$10

Figure 6.1 The Market
Demand Curve and
Monopoly Firm Demand
Curve

Because your firm is the
only company allowed to
sell your drug, the market
demand curve, D, is also
your demand curve for the
drug.

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6.1 A Monopoly Market  231

Figure 6.2 illustrates your demand curve and the resulting marginal revenue curve.
Both curves show that for any quantity, the price, measured from the demand curve,
is greater than the marginal revenue, measured from the marginal revenue curve.
Why is P 7 MR? In Table 6.1, you can see that your pharmaceutical company can
sell 199,999 units at a price of $50,000.20 for each unit. Because the demand curve is
downward sloping, the managers can sell an additional unit, the 200,000th unit, only
if they lower the price for all the units. Table 6.1 shows that the price of a treatment
must fall to $50,000.00 in order to sell the 200,000th unit. The extra unit directly adds
$50,000.00 to your firm’s total revenue, but to sell that unit, you had to lower the
price of a treatment from $50,000.20 to $50,000.00, a loss of $0.20 in revenue on each
of the initial 199,999 treatments you had been selling at the higher price. The price
reduction means that your firm loses a total of $0.20 * 199,999 or $39,999.80 in reve-
nue on the quantity that it had been selling. So the total change in revenue from sell-
ing the 200,000th unit equals $50,000.00 – $39,999.80 or $10,000.20, making the
marginal revenue from the 200,000th unit $10,000.20.

D

MR

Price (thousands of
dollars per treatment)

Quantity (thousands of
treatments per year)

$90

$0

$10

$20

35030025020015010050

$30

$40

$50

$60

$70

$80

2$20

2$10

Figure 6.2 A Monopoly’s
Demand and Marginal
Revenue Curves

The graph shows the
market demand curve (D)
and the resulting marginal
revenue curve (MR) for
your drug. For any
quantity, P 7 MR. Because
the demand curve is linear,
the marginal revenue is
also linear, with the same
intercept on the price axis
and a slope that is twice
the slope of the demand
curve.

Table 6.1 Demand, Total Revenue, and Marginal Revenue

The first two columns are (part of) the demand facing your firm. Total revenue equals
P * Q. Marginal revenue is the change in total revenue caused by a change in quantity,
or ∆TR∆Q . For a monopoly, price is greater than marginal revenue, P 7 MR.

Price,
P

Quantity
Demanded, Q

Total Revenue,
TR

Marginal
Revenue, MR

50,000.40 199,998 $9,999,979,999.20
$10,000.60

10,000.20

9,999.80

9,999.40

50,000.20 199,999 9,999,989,999.80

50,000.00 200,000 10,000,000,000.00

49,999.80 200,001 10,000,009,999.80

49,999.60 200,002 10,000,019,999.20

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232  CHAPTER 6 Monopoly and Monopolistic Competition

This reasoning applies to all units produced and makes clear why P 7 MR for
a monopoly: To sell an additional unit, you must lower the price, thereby losing
some revenue on the initial units already sold. Recall that for a perfectly competi-
tive firm, P = MR because the competitive firm’s demand curve is horizontal—the
managers do not need to lower the price to sell additional units. When a perfectly
competitive firm sells another unit, there is no need to subtract a loss in revenue
from the initial units because the constant price means there is no loss in revenue.

Figure 6.2 shows that there are quantities where the marginal revenue (MR) is
negative. This occurs when there are so many units sold before the price change that
the revenue lost on these initial units is larger than the revenue gained on the newly
sold unit. In this case, the change in total revenue is negative, which makes the mar-
ginal revenue negative.

Marginal Revenue Curve for a Linear Demand Curve
Figure 6.2 also shows that when the demand curve is linear, the marginal revenue curve
also is linear. In addition, while both curves have the same intercept on the price axis,
the marginal revenue curve is twice as steep as the demand curve.1 This mathemat-
ical result is correct only for linear demand curves. For these sorts of curves, it is a very
handy result because it allows you to quickly determine the marginal revenue curve.
The result that for a monopoly P 7 MR is more general. Indeed, as long as the demand
curve is downward sloping, P 7 MR no matter if the demand curve is linear or not.

Elasticity, Price, and Marginal Revenue
Closer analysis of the definition of marginal revenue reveals an important relation-
ship among the elasticity of demand, the price, and the marginal revenue. Some
mathematics relegated to a footnote2 shows that the marginal revenue from a one-
unit change in Q is equal to

MR = a ∆P
∆Q

* Qb + P 6.1

Equation 6.1 reflects the two effects of a change in the quantity on the total revenue:
(1) the effect of the change in the price on the initial quantity, the first term (in
parentheses), and (2) the effect of the change in quantity itself. With an increase
in the quantity, Equation 6.1 divides the marginal revenue from the increase in Q
into the following:

1. 1 �P�Q : Q2 term. An increase in the quantity sold requires a decrease in price. In
other words, there must be a downward movement along the demand curve.

The amount of the decrease in price depends on the slope of the demand curve,
∆P∆Q. Because the slope of the demand curve is negative, the term 1 ∆P∆Q * Q2 is
negative. This term captures the effect of the lower price decreasing the reve-

nue collected from all the initial units previously sold—that is, from Q units.
2. P term. An increase in the quantity directly increases the total revenue. This

increase in the total revenue equals P * ΔQ, so a one-unit increase in the quantity
raises the total revenue by P. The second term, P, captures this effect.

1 We prove this result in Section 6.A of the Appendix at the end of this chapter.

2 Using the definition of total revenue 1P * Q2 in the equation for marginal revenue gives MR = ∆TR∆Q =
∆1P * Q2

∆Q =
1∆P * Q2 + 1P * ∆Q2

∆Q = 1 ∆P∆Q * Q2 + P.

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6.1 A Monopoly Market  233

You can rearrange Equation 6.1 into a form that is more valuable for managers
and managerial decision making3:

MR = P * a1 – 1
e
b = P * a e – 1

e
b 6.2

Equation 6.2 shows important relationships among the firm’s marginal revenue, price,
and price elasticity of demand for its product that hold for any demand curve4. As a
manager, you can use these relationships to help make decisions. For example, if you
know or have an estimate of your firm’s price elasticity of demand (recall that this can
change at different points on a demand curve), you can use it along with the price of
the product to calculate the marginal revenue of a unit. In addition to its managerial
use, Equation 6.2 has two significant implications for your study of monopoly:

1. The equality MR = P * 11 – 1e2 shows that unless 1e equals zero, marginal revenue
is less than the price, in which case the marginal revenue curve lies below the

demand curve. The amount by which the marginal revenue is less than the price
depends on e, the price elasticity of demand—the larger e, the larger 11 – 1e2 and
therefore the closer MR to P.

2. The equality MR = P * 1e – 1e 2 demonstrates that the marginal revenue is

• Positive when the price elasticity of demand exceeds 1 because 1e – 1e 2 is positive.
• Zero when the price elasticity of demand equals 1 because 1e – 1e 2 is zero.
• Negative when the price elasticity of demand is less than 1 because 1e – 1e 2 is

negative.

Using the definitions of elastic, unit-elastic, and inelastic demand from Chapter 3
(see Section 3.4), these results mean that for any demand curve, the marginal revenue
is positive when demand is elastic, zero when demand is unit elastic, and negative
when demand is inelastic.

3 In Section 6.B in the Appendix at the end of this chapter, we prove Equation 6.2 using calculus.
4 The price elasticity of demand equals the percentage change in the quantity demanded caused by a one-
percentage-point change in the price. The more substitutes for a product, the stronger the response to a change
in the price, which means the larger the elasticity. Chapter 3 defines and discusses elasticity in more detail.

The Relationship Among the Price Elasticity of Demand,
Marginal Revenue, and Price

Use the relationship among the price elasticity of demand, marginal revenue, and price
to answer the following questions.

a. If the price elasticity of demand is 3 and the price is $100, what is the marginal revenue?

b. If the price elasticity of demand is 1 and the price is $100, what is the marginal revenue?

c. If the price elasticity of demand is 0.4 and the price is $100, what is the marginal
revenue?

d. If the price elasticity of demand is 1.1 and the marginal revenue is $100, what is the price?

SOLVED
PROBLEM

(Continues)

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234  CHAPTER 6 Monopoly and Monopolistic Competition

6.2 Monopoly Profit Maximization
Learning Objective 6.2 Discuss how managers of a monopoly can determine
the quantity and price that maximize profit and how they compare to those of
a perfectly competitive firm.

Now that you understand the basics of a monopoly market, you are ready to investi-
gate how managers of a monopoly can maximize their profit. Then you will learn
how the profit-maximizing price and quantity compare for monopoly markets and
perfectly competitive markets.

Profit Maximization for a Monopoly
In Chapter 5, marginal analysis demonstrated that managers of a perfectly competitive
firm maximize profit by producing the amount of output that sets the marginal revenue
(MR) equal to the marginal cost (MC). Marginal analysis and the profit-maximization
rule can help managers of a monopoly maximize their firm’s profit as well.

Profit Maximization for a Monopoly: Marginal Analysis
The key to maximizing profit in any firm, whether it is a monopoly or one of thve many
firms in a perfectly competitive market, is to produce all of the profitable units and
none of the unprofitable units. Using this fundamental insight, in Chapter 5 you learned
that marginal analysis led to the profit-maximization rule: Produce the quantity for which
MR = MC, and then set the highest price that sells the quantity produced. Managers of
monopolies can use the same profit-maximization rule to maximize their firm’s profit.

To use marginal analysis and the profit-maximization rule, you compare the mar-
ginal revenue of a unit to its marginal cost. Continuing the example with you as a
manager of a pharmaceutical company, Figure 6.3 includes the marginal cost curve
for your firm’s drug along with the demand and marginal revenue curves that appear
in Figure 6.2. As Figure 6.3 shows, the marginal revenue of all quantities up to 150,000
exceeds their marginal cost. Following the profit-maximization rule, you produce all
of these units. The figure also shows that the marginal revenue of all quantities
beyond 150,000 is less than their marginal cost. So you produce none of these units.
The conclusion from this analysis is identical to that for a perfectly competitive firm:
To maximize profit, your firm produces the quantity of output for which the marginal
revenue equals the marginal cost 1MR = MC or MR – MC = 02.

You must now set a price. Monopolies, and other firms with market power, have
control over the price they set. In this chapter, assume that the same price is set for
all units sold and for all buyers. In Chapter 10, you will learn about other pricing
strategies that can lead to increased profit.

Answer
All of the answers require using the equation MR = P * 1e – 1e 2 to quantify the relationship
among the marginal revenue, price, and price elasticity of demand.

a. MR = $100 * 13 – 13 2 = $66.67. When e 7 1, the marginal revenue is positive.
b. MR = $100 * 11 – 11 2 = $0. When e = 1, the marginal revenue equals zero.
c. MR = $100 * 10.4 – 10.4 2 = – $150. When e 6 1, the marginal revenue is negative.
d. Rearrange the equation MR = P * 1e – 1e 2 to MR * 1 ee – 1 2 = P , so
P = $100 * 1 1.11.1 – 1 2 = $1,100.

SOLVED PROBLEM (continued )

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6.2 Monopoly Profit Maximization  235

According to the profit-maximization rule, the price is determined from the
demand curve as the highest price that sells the quantity produced. In Figure 6.3, the
demand curve shows that the highest price buyers are willing to pay for 150,000
treatments is $60,000 per treatment, so $60,000 is the profit-maximizing price.

Markup Equation
In Figure 6.3, the price of a treatment, $60,000, is twice the marginal cost of $30,000.
The factor by which the price is higher than the marginal cost, PMC, or 2.0 in this case, is
the markup. You can use the relationship among the price elasticity of demand, price,
and marginal revenue shown in Equation 6.2, MR = P * 1e – 1e 2, to determine the
role the price elasticity of demand plays in determining the profit-maximizing price
and markup. When the managers maximize profit, MR = MC. Accordingly, substi-
tuting MC for MR, Equation 6.2 becomes

MC = P * a e – 1
e

b 6.3

Rearranging Equation 6.3 illustrates two key results. First, dividing both sides of
Equation 6.3 by e – 1e shows the role the price elasticity of demand plays in setting
the profit-maximizing price:

P = MC * a e
e – 1

b 6.4

Second, dividing both sides of Equation 6.4 by MC gives the markup equation, the
equation showing the markup of the price over marginal cost:

P

MC
= a e

e – 1
b = 1 + a 1

e – 1
b 6.5

Markup equation The
equation showing the
markup of the price over
marginal cost: PMC =

e
e – 1.

D

MR

MC

Price and cost (thousands of
dollars per treatment)

Quantity (thousands of
treatments per year)

$90

$0

$10

$20

35030025020015010050

$30

$40

$50

$60

$70

$80

2$20

2$10

Profit-maximizing
price

Profit-
maximizing
quantity

MR . MC MR , MC

Figure 6.3 Profit Maximization for a Monopoly

The quantity that sets MR = MC (150,000
treatments) maximizes your company’s profit. This
quantity produces all of the profitable units (those
for which MR 7 MC ) and none of the unprofitable
units (those for which MR 6 MC ). The demand
curve shows that the profit-maximizing price is
$60,000 per treatment, the highest price demanders
will pay for 150,000 treatments.

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236  CHAPTER 6 Monopoly and Monopolistic Competition

Equation 6.4 shows how to use your estimates of the marginal cost and price
elasticity of demand to set the profit-maximizing price, and Equation 6.5 shows
how the markup depends on the price elasticity of demand. The equations also
show a key qualitative result: The smaller the price elasticity of demand, the
higher the price and the larger the markup. Figure 6.4 illustrates these general
results. In Figure 6.4(a), at the profit-maximizing quantity on the demand curve
(point A), the price elasticity of demand is 3.0.5 When the price elasticity of demand
equals 3, the markup is 33 – 1, or 1.5, so the price is 1.5 times the marginal cost, $30.
In Figure 6.4(b), however, the price elasticity of demand at the profit-maximizing
point (point B) is smaller, 1.67. Consequently, the markup, 1.671.67 – 1, or 2.5, is larger,
so that the price, $50, is higher.

The intuition that a smaller price elasticity of demand leads to a higher price is
as important as the actual formula. Recall from Chapter 3 that the fewer substitutes
for a good, the smaller its price elasticity of demand. That observation combined
with the markup equation means that the fewer the substitutes for a good, the
higher the price a monopoly can charge. This intuition (and the quantitative result in
Equation 6.4) explains why pharmaceutical companies that produce unique, lifesav-
ing drugs are free to set sky-high prices for those drugs.

5 From Chapter 3, the price elasticity of demand along a linear demand curve is e = � b * 1P>Qd2 � , where
b is the change in the quantity demanded from a $1 change in price. In Figure 6.4(a), b equals 40 units per
dollar, so at point A the price elasticity of demand is � 40 * 1$30>4002 � = 3.0. In Figure 6.4(b), b equals
13.33 units per dollar, so at point B the price elasticity of demand is � 13.33 * 1$50>4002 � = 1.67.

Price and cost
(dollars per unit)

Quantity (units per day)

$60

$10

1,000 1,200600 800200 400

$20

$30

$40

$50

0

D

MR

MC

A

Profit-maximizing
price

Price and cost
(dollars per unit)

Quantity (units per day)

$60

$10

1,000 1,200600 800200 400

$20

$30

$40

$50

0

DMR

MC

B

Profit-maximizing
price

Figure 6.4 Markup and Elasticity

(a) Markup with Larger Elasticity (b) Markup with Smaller Elasticity
To maximize profit, managers produce 400 units per
day. The profit-maximizing markup of price over
marginal cost is ee – 1. At point A on the demand curve,
the price elasticity of demand 1e2 is 3.0, so the markup
is 33 – 1 = 1.5. Consequently, the profit-maximizing
price equals $20 * 1.5 = $30 per unit.

To maximize profit, managers produce 400 units per
day. The profit-maximizing markup of price over
marginal cost is ee – 1. At point B on the demand curve,
the price elasticity of demand 1e2 is 1.67, so the
markup is 1.671.67 – 1 = 2.5. Consequently, the profit-
maximizing price equals $20 * 2.5 = $50 per unit.

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6.2 Monopoly Profit Maximization  237

Suppose that you are a manager in the pricing department of a tire-producing
company like Michelin US. Your research department reports that the best esti-
mate of the price elasticity of demand for your tires is 1.6 but that the elasticity
might be as large as 1.8 or as small as 1.4. Your marginal cost is $100 per tire.
What is the range of the profit-maximizing price for your product? What might
you ask your research department to do next?

Answer
Equation 6.4 shows that the profit-maximizing price equals MC * ee – 1. If the price

elasticity of demand is 1.8, then the price equals $100 * 1.81.8 – 1, or $225 per tire. If

the price elasticity of demand is 1.4, then the price equals $100 * 1.41.4 – 1, or $350
per tire. Consequently, your profit-maximizing price per tire ranges from $350 to
only $225, a rather wide range. You might return to your research department and
ask the analysts to try to tighten the range for the price elasticity of demand.

DECISION
SNAPSHOT

Profit-Maximizing Range of Prices
for Tires

Amount of Profit
In Chapter 5, you learned that a perfectly competitive firm makes an economic profit
if P 7 ATC, makes a competitive return if P = ATC, and incurs an economic loss if
P 6 ATC. Thankfully, you do not need to memorize yet another rule because the
same set of results holds true for monopoly firms. In fact, these relationships apply
to any firm.

Figure 6.5 includes the average total cost curve (ATC) for your firm’s drug, assum-
ing that it makes an economic profit. In the figure, the price ($60,000 per treatment)
exceeds the average total cost ($40,000), which shows that your company is making
an economic profit. The area of the green rectangle in Figure 6.5 is 1P – ATC2 * Q.
As you learned in Chapter 5, this area equals the amount of the firm’s economic profit
because it is the economic profit per unit 1P – ATC2 multiplied by the quantity
sold (Q). In Figure 6.5, the economic profit is 1$60,000 – $40,0002 * 150,000 treat-
ments, which comes out to $3 billion.

Figure 6.5 shows the monopoly is making an economic profit, so it would be easy
to suppose that all monopolies make an economic profit. However, the fact that there is
only one firm in the industry is no guarantee that a monopoly will make an economic
profit, much less an exorbitant one. If production costs are high relative to demand,
profits will be low, and economic losses may even occur. For instance, take the classic
online failure, Pets.com. This pet-food delivery company was founded in 1998 and
used a sock puppet dog in its advertising. Pets.com faced no competition in the market
for home delivery of pet supplies, so it was effectively a monopoly. The company had
both high costs—it offered free shipping for heavy products, such as dog food and cat
litter, which were expensive to ship—and low demand—consumers tend to buy pet
food and litter when they run out and therefore did not want to wait for delivery from
Pets.com. Observers suggested that P 6 ATC for each item Pets.com shipped; that is,
each bag of dog food and cat litter shipped increased Pets.com’s loss. Pets.com incurred
a large economic loss and survived for approximately two years before it declared
bankruptcy. What happened to the sock puppet dog remains a mystery.

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238  CHAPTER 6 Monopoly and Monopolistic Competition

Shut-Down Rule for a Monopoly
Pets.com ultimately closed. In Chapter 5, you learned the shut-down rule for a firm
in a perfectly competitive market: The firm closes if total revenue is less than total
variable cost and remains open if total revenue is greater than total variable cost.
Equivalently, the firm closes if price is less than average variable cost 1P 6 AVC2
and remains open if price is greater than average variable cost 1P 7 AVC2. When
does a monopoly close? It turns out that the same shut-down rule applies. If any firm
cannot make enough revenue to cover its variable costs, which means P 6 AVC, the
firm minimizes its loss by closing.

Long-Run Profit Maximization for a Monopoly
Because there is only one firm in a monopoly market, when the firm is in long-run
equilibrium, the market is also in long-run equilibrium. Recall from Chapter 5 that
when firms in a perfectly competitive market are making an economic profit, entry
occurs, and in the long run, the entry drives the firms’ economic profit to zero. In a
monopoly, however, the presence of insurmountable barriers to entry prevents entry
by new firms, so the firm can continue to make an economic profit. Even so, the
managers may still need to adjust the scale of production to minimize the firm’s
long-run average cost and increase its economic profit even more.

Figure 6.6 shows the long-run outcome for your pharmaceutical firm after you
have changed the scale of production of your firm’s drug by adjusting the firm’s
inputs. The managers are maximizing long-run profit by producing so that marginal
revenue equals long-run marginal cost, or MR = LMC. In the figure, the firm maxi-
mizes its long-run profit by producing 175,000 treatments and setting a price of
$55,000 per treatment. The company is producing its profit-maximizing quantity,
175,000, at the lowest possible average cost, $15,000, and is making the largest possi-
ble economic profit, $7 billion. As long as no other firm can enter the market, the
economic profit can persist.

D

MR

MC ATC

Price and cost (thousands
of dollars per treatment)

Quantity (thousands of
treatments per year)

$90

$0

$10

$20

35030025020015010050

$30

$40

$50

$60

$70

$80

2$20

2$10

Economic profit,
$3 billion

Figure 6.5 Economic Profit
for a Monopoly

Your firm is making an
economic profit because
its price, $60,000 per
treatment, exceeds its
average total cost, $40,000
per treatment. The amount
of the economic profit
equals the area of the
green rectangle.

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6.2 Monopoly Profit Maximization  239

Comparing Perfect Competition and Monopoly
You have learned that the profit-maximization rule and the shut-down rule apply to
both monopoly firms and firms in perfectly competitive markets. How does the equilib-
rium in a perfectly competitive market compare to the equilibrium in a monopoly market?
Understanding the differences is essential for the formulation of public policy, such as
antitrust policy (presented in Chapter 9).

Comparing a Perfectly Competitive Market and a Monopoly Market
Although the goal of managers of both monopolies and firms in perfectly competi-
tive markets is to maximize profit, their impact on society differs dramatically. As
you learned in Section 2.4, perfectly competitive markets maximize society’s total
surplus of benefit over cost. Figure 6.7(a) illustrates the maple syrup market first
presented in Chapter 5. In a perfectly competitive market for maple syrup, the equi-
librium quantity is 12 million gallons, and the price is $30 per gallon. In this perfectly
competitive market, the total surplus of benefit over cost to society is equal to the
area of the green triangle.6 The area equals the largest possible amount of total sur-
plus, which is why economists generally favor perfectly competitive markets.

Suppose that one firm becomes a monopoly by buying all of the others and
somehow manages to create a barrier to entry that keeps any other firm from enter-
ing the market. Instead of having many separate firms under independent owner-
ship and control, there is now a single firm with many separate plants or production

D

MR

LMC
LAC

Price and cost (thousands
of dollars per treatment)

Quantity (thousands of
treatments per year)

$90

$0

$10

$20

35030025020015010050

$30

$40

$50

$60

$70

$80

2$20

2$10

Economic profit,
$7 billion

Figure 6.6 Long-Run Profit
Maximization

Your firm is maximizing its
long-run economic profit
because its marginal
revenue equals its long-
run marginal cost,
MR = LMC . You are
producing the profit-
maximizing quantity,
175,000 treatments, at the
lowest average cost for
this quantity, $15,000 per
treatment. The price is
$55,000 per treatment so
the economic profit equals
the area of the green
rectangle, $7 billion.

6 Applied to the maple syrup market, Chapter 2 explained that for any gallon of maple syrup, the maxi-
mum price a consumer is willing to pay, measured by the demand curve, is the marginal benefit from that
gallon. The supply curve measures the marginal cost of any gallon. So the difference between the demand
curve and the supply curve equals society’s surplus of marginal benefit over marginal cost for each gallon
of syrup. The total surplus is the sum of the surpluses of all gallons produced, 12 million gallons in
Figure 6.7(a).

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240  CHAPTER 6 Monopoly and Monopolistic Competition

facilities. Figure 6.7(b) shows this situation in the monopoly market. The market
demand curve (D) is the monopoly firm’s demand curve. Associated with this
demand curve is the monopoly’s marginal revenue curve (MR). This marginal reve-
nue curve was present when the market was competitive, but because it was irrele-
vant, it was omitted from Figure 6.7(a). Now, however, the MR curve matters.
Because the monopolist’s managers equate marginal revenue and marginal cost to
determine the profit-maximizing output, you also need the marginal cost curve. As
you learned in Chapter 5, the competitive supply curve is the sum of the individual
competitive firms’ supply curves, and each individual firm’s supply curve is that
firm’s marginal cost curve. Once these firms are brought under single ownership as
a monopoly, the sum of the individual firms’ marginal cost curves becomes the
monopoly’s marginal cost curve, MC in Figure 6.7(b). The monopoly’s managers
now use marginal analysis to maximize their profit by producing 8 million gallons
and setting a price of $40 per gallon.

You can see that, when compared to a perfectly competitive market, the monopoly
sets a higher price—$40 per gallon versus $30—and produces a smaller quantity—
8 million gallons versus 12 million. The higher price means that the firm’s owners
are better off at the expense of the consumers. Economists have traditionally had lit-
tle to say about such reallocations between groups because both producers and con-
sumers are members of society and everyone counts. Rather, economists’ main
objection to monopoly stems from the resulting misallocation of resources, which
can be seen by considering the total surplus to society. In Figure 6.7(b), all of the
8 million gallons of syrup the monopoly produces have a surplus to society because

Price (dollars per gallon
of maple syrup)

Quantity (millions of gallons
of maple syrup per year)

$60

$10

20 2412 164 8

$20

$30

$40

$50

0

D

SEquilibrium
price

Equilibrium
quantity

Total
surplus

Price (dollars per gallon
of maple syrup)

Quantity (millions of gallons
of maple syrup per year)

$60

$10

20 2412 164 8

$20

$30

$40

$50

0

D

MC

MR

Profit-maximizing
price

Profit-maximizing
quantity

Total
surplus Deadweight

loss

Figure 6.7 Comparing the Total Surplus to Society in a Competitive Market and a Monopoly Market

(a) Total Surplus in a Competitive Market (b) Total Surplus in a Monopoly Market
The equilibrium quantity is 12 million gallons, and the
equilibrium price is $30 per gallon. Society’s total
surplus of benefit over cost is equal to the area
between the demand and supply curves (the area of
the green triangle). This is the maximum possible
amount of surplus.

The managers of the monopoly maximize profit by
producing the quantity that sets MR equal to MC, 8
million gallons, and setting a price of $40 per gallon.
With this price and quantity, society’s total surplus
equals the area of the green trapezoid. This surplus is
less than that shown in Figure 6.7(a) for a competitive
market because of the deadweight loss, which is equal
to the area of the red triangle.

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6.2 Monopoly Profit Maximization  241

their marginal benefit exceeds their marginal cost. The total surplus for these 8 million
gallons is the sum of all the individual surpluses, which equals the area of the green
trapezoid in Figure 6.7(b).

Comparing the green triangle in Figure 6.7(a) to the green trapezoid in
Figure 6.7(b), you can see that society’s total surplus is less with the monopoly. The
difference in total surplus to society is the deadweight loss. The deadweight loss is
society’s loss of total surplus from producing less than or more than the efficient
quantity, 12 million gallons. In Figure 6.7(b), where the monopoly produces less
than the efficient quantity, the deadweight loss from the monopoly is equal to the
area of the red triangle, $40 million per year. The deadweight loss is the funda-
mental economic social harm created by monopoly. The damage a monopoly causes
is the production of too little output and the decrease in the number of employees
and other resources involved in producing the product. Neither the economic
profit nor the high monopoly price is the social problem. Instead, these are symp-
toms of the real problem, which from the social perspective is the misallocation of
resources and the resulting deadweight loss. The deadweight loss from monopoly
is the basis for the nation’s antitrust laws, but aside from this rationale, it has no
direct relevance to managers.

Comparing a Perfectly Competitive Firm and a Monopoly Firm
You know that managers of both perfectly competitive firms and monopoly firms follow
the same profit-maximization rule: Produce the quantity that sets marginal revenue
equal to marginal cost 1MR = MC2, and charge the highest price possible that still
allows the firm to sell the quantity produced. This similarity, however, masks the differ-
ences between monopolies and perfectly competitive firms summarized in Table 6.2.

Barriers to entry are significant to a firm and its managers because they enable a
monopoly to make a long-run economic profit. Let’s turn to a more detailed exam-
ination of this important concept.

Barriers to Entry
As you learned in Chapter 5, a barrier to entry is any factor that makes it difficult for
new firms to enter a market. Examples include legal barriers (such as patents, trade
secrets, copyrights, and trademarks), control of an essential raw material, the exis-
tence of overwhelming economies of scale, government control of entry, sunk costs,
and—possibly—advertising.

Deadweight loss The loss
in total surplus from
producing less than or
more than the efficient
quantity.

Table 6.2 Comparing a Perfectly Competitive Firm to a Monopoly

Perfectly Competitive
Firm

Monopoly

Amount of markup?
Zero; the price equals
marginal cost

Positive; the amount of the markup of the
price over marginal cost depends on the price
elasticity of demand

Can make a short-run economic
profit?

Yes Yes

Can make a long-run economic
profit?

No
Yes; some type of barrier to entry protects the
economic profit from entry by new firms

Always produces at the minimum
average total cost in the long run?

Yes
No; the firm might produce at the minimum
average total cost but does not necessarily do so

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242  CHAPTER 6 Monopoly and Monopolistic Competition

Patents, Trade Secrets, Copyrights, and Trademarks
Chapter 15 presents a more complete discussion of patents, trade secrets, copyrights,
and trademarks. This chapter focuses on how they serve as legal barriers to entry,
how they provide their owners some legal protection from infringement, and the
different types of products they protect.

• Patents. Patents protect products or specific production processes by giving
the owner the exclusive right to produce a certain commodity or to use a spe-
cific production process for a 20-year period that begins at the time the pat-
ent application is filed. Granting a patent ensures that no competitor can
legally copy the inventor ’s creation during the life of the patent. Although it
affords legal protection against blatant copying, a patent does not provide
absolute protection. The market power from a patent is limited because pat-
ents are often narrowly defined, which may allow other firms to approximate
closely the process or product without infringing. For example, Merck pat-
ented the first statin (a cholesterol-lowering drug), Mevacor, and began mar-
keting it in the United States in 1987. Ultimately, however, other companies
began selling six other, closely related statins. After Mevacor enjoyed a U.S.
market share of 100 percent for the first three years, other companies started
selling their statins, and its market share fell to less than 15 percent within
seven years.

• Trade secrets. The fact that patents are often narrowly defined may leave man-
agers concerned that a patent on a product or production process will not pre-
vent competitors from selling or using a closely related product. For this reason,
some managers opt to keep their production process a trade secret. KFC’s “secret
recipe of eleven herbs and spices” is a trade secret. Less tasty examples include
Google’s search algorithms and the ingredients of the WD-40 Company’s name-
sake product, WD-40.

• Copyrights. Copyright law gives legal protection to works of authorship, such
as movies, songs, and books. This book is copyrighted, as is the film
Avatar, which to date has grossed $2.7 billion. The length of copyright protec-
tion varies. For works produced after January 1, 1978, the copyright protec-
tion lasts for the life of the creator plus an additional 70 years, but the
copyright for a work-for-hire (such as a pamphlet) is typically 95 years from
the first publication.

• Trademarks. Trademarks protect brand names, symbols, or designs that iden-
tify the source of the product. For example, The Walt Disney Company has
trademarked Mickey Mouse, and Nike, Inc., has trademarked its “Swoosh”
logo. No one else can use Mickey Mouse or the “Swoosh” design without per-
mission from Disney or Nike, respectively. In the United States, trademark
owners are protected for 10 years, but they can renew their trademarks
indefinitely.

The economic value of patent, trade secret, copyright, or trademark protection
depends on the value of the protected item in the marketplace. For example, a patent
on a solar-powered mousetrap would not be worth much because few people want
to buy them. Similarly, copyright protection on a film about famous economists that
no one wants to see is worthless. In contrast, a patent on a cure for cancer would be
worth a fortune. Patents, trade secrets, copyrights, and trademarks offer legal pro-
tection to a monopoly and protect its economic profit by preventing the entry of
copycat producers into the market.

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6.2 Monopoly Profit Maximization  243

Control of an Essential Raw Material
It should be obvious that if one firm controls the supply of an essential input, other
firms will be unable to compete. The classic example of this situation is the alleged
control of bauxite reserves in the 1930s and 1940s by the Aluminum Company of
America (Alcoa). Through purchases and long-term contracts, Alcoa was purported
to have preempted control of the available supplies of bauxite ore, the ore used to
produce aluminum. Through that control, Alcoa allegedly prevented the entry of
other firms into the U.S. aluminum market. More recently, in 1987, De Beers had
approximately a 90 percent share of the gem diamond market because it controlled
virtually all of the world’s raw gem diamonds.

In some cases, it may be possible to restrict the availability of the raw material.
For example, New York’s ban on hydraulic fracturing (fracking) has limited the sup-
ply of natural gas from the Marcellus Shale. Although this ban does not create a
monopoly producer of natural gas, it does protect natural gas firms from entry by
competitors located in New York.

Ultimately, it is difficult for managers to preserve their grasp on an essential raw
material. For example, Alcoa lost its alleged death grip on bauxite after the U.S. gov-
ernment financed a vast expansion of U.S. aluminum capacity during World War II
and then sold its interests to competing firms after the war. De Beers also failed to
protect its positions and fell prey to competition from new sources of raw diamonds
that were not under the firm’s control: Today, De Beers’ market share is under
40 percent.

Economies of Scale
Sometimes new firms do not enter the industry because they would be at a sub-
stantial cost disadvantage to the larger established firm. Natural monopolies,
such as water, sewage, electricity, and natural gas utilities, are extreme examples.
Natural monopolies have massive economies of scale, so that as their produc-
tion increases, their long-run average cost constantly falls throughout the range
of demand. Recall from Chapter 4 that economies of scale refers to the region of
the long-run average cost curve where the long-run average cost falls as produc-
tion increases; it is the downward-sloping segment of the curve. A natural
monopoly’s economies of scale are so extensive that the firm’s minimum efficient
scale—the quantity at which the long-run average cost first reaches its mini-
mum—exceeds the quantity customers demand. Figure 6.8 illustrates this situa-
tion. Suppose that a firm like Georgia Power, an electric utility operating out of
Atlanta, reaches its minimum efficient scale of 60 billion kilowatt hours per year
at a cost of 6¢, while at the price of 6¢, customers demand only 47 billion kilowatt
hours per year.

The interaction between the demand for the product and the technological
conditions that require large scale for efficient, low-cost production limits the
number of firms in the market. For example, Figure 6.8 shows that this electric
utility company’s managers maximize profit by producing 20 billion kilowatt
hours per year—the quantity that sets the marginal revenue (MR) equal to the
long-run marginal cost (LMC)—and setting a price of 14¢ per kilowatt hour—the
highest price consumers will pay for 20 billion kilowatt hours per year. The firm’s
average cost of producing 20 billion kilowatts is 10¢ per kilowatt hour. If another
firm enters the market, it will be unable to immediately attain the economies of
scale that this firm enjoys. Suppose that the new firm has the same long-run aver-
age cost as this one but produces only one-half of the output, or 10 billion kilowatt
hours. Even though the new firm’s scale of production is remarkably large, the

Natural monopoly A firm
with economies of scale so
large that as its production
increases, its long-run
average cost constantly
falls throughout the range
of demand.

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244  CHAPTER 6 Monopoly and Monopolistic Competition

new entrant still has higher costs. The new firm’s lowest possible average cost of
producing 10 billion kilowatt hours is 15¢ per kilowatt hour, much higher than the
existing firm’s average cost of 10¢ per kilowatt hour. Indeed, the 15¢-per-kilowatt-
hour cost is above the existing firm’s monopoly price of 14¢ per kilowatt hour. If
the new firm tried to match this price, it would incur a significant economic loss.
The prospect of such an economic loss will deter many—likely all—other firms
from entering the market. The profound economies of scale operate as a barrier to
entry and create a natural monopoly.

As Figure 6.8 shows, because the minimum efficient scale is larger than the
quantity demanded, the long-run average cost curve (LAC) continues to decrease
even after it crosses the demand curve (D). This result poses a problem for society
because it means that one firm can produce the quantity demanded in the market at
a lower total cost than could two or more firms. For example, with one firm in the
market, the electric utility can produce 20 billion kilowatt hours at an average cost
of 10¢ per kilowatt hour, for a total cost of 10¢ * 20 billion or $2.0 billion. If two
equal-sized firms produced the 20 billion kilowatt hours, each would produce 10
billion kilowatt hours at an average cost of 15¢ per kilowatt hour. Each firm’s total
cost would be 15¢ * 10 billion = $1.5 billion. The total cost of producing 20 billion
kilowatt hours in a market with two firms is $3.0 billion 1$1.5 billion + $1.5 billion2,
higher than the total cost of the single firm. Why is the total cost lower with only
one firm? With only one firm distributing electricity in a city, only one set of poles
and wires must be erected, but if two (or more) companies distribute power, two (or
more) sets of poles and wires are necessary which drastically increases the total cost
of distributing power.

The lower total cost with one firm makes it socially desirable to have a single
firm supply the entire market. As a monopoly, however, the firm produces less than
a competitive market would, thereby creating a deadweight loss. Because of this

D
MR

LMC

LAC

Price and cost (cents
per kilowatt hour)

Quantity (billions of kilowatt
hours per year)

18¢

20¢

0

70605040302010

10¢

12¢

14¢

16¢

Profit-maximizing price

Profit-maximizing
quantity

Figure 6.8 A Natural Monopoly

This electric utility company has such extensive
economies of scale that its minimum efficient scale
of 60 billion kilowatt hours, with a long-run average
cost of 6¢, exceeds the quantity demanded of
47 billion kilowatt hours at a price of 6¢.
To maximize profit, managers produce 20 billion
kilowatt hours because that is the quantity at which
the marginal revenue equals the long-run marginal
cost. The profit-maximizing price is 14¢ per kilowatt
hour and its average cost is 10¢ per kilowatt hour. If
another firm entered the market, the new firm’s
scale of production would be less than 20 billion
kilowatt hours. The smaller scale of production
places the new firm at a severe competitive
disadvantage because its average cost would be
much higher than this firm’s average cost.

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6.2 Monopoly Profit Maximization  245

social tension—lower costs versus deadweight loss—state governments generally
regulate natural monopolies. While all firms face some government regulation, the
magnitude of the regulation imposed on natural monopolies, such as utilities, is con-
siderably higher. In particular, the regulators (state public utility commissions) effec-
tively determine what price the firm can charge and require production of the
quantity consumers demand. In exchange, the government grants the firm a legal
franchise that prevents other firms from entering the market. The regulatory goal is
to preserve the social benefits of the lower costs while avoiding the social drawback
of the deadweight loss. The type of regulation used and the question of whether the
regulators achieve their admirable goals are best described in courses dealing exclu-
sively with government regulation of business.

The overwhelming economies of scale relative to demand enjoyed by a natural
monopoly make for a highly effective barrier to entry. To serve as a barrier to entry,
however, economies of scale do not need to be so extreme. The presence of econo-
mies of scale that are merely substantial also creates an entry barrier. In Figure 6.9,
the managers of a monopoly producer of eyeglasses maximize profit by producing
300 million pairs of eyeglasses per year and setting a price of $250 per pair. The firm
makes an economic profit because the price ($250) exceeds the long-run average
cost ($150). If another firm enters the market and immediately also produces
300 million pairs of eyeglasses, the total quantity produced by the two firms is 600
million. The demand curve shows that in this case the price falls to $100 per pair.
Both firms would incur an economic loss. More generally, an entrant that produces
a substantial quantity in order to gain economies of scale so it can successfully com-
pete causes a large decrease in price and creates the possibility of an economic loss.
The risk of an economic loss deters entry into the market even though the firm
already in the market is making an economic profit. On the other hand, an entrant
that produces only a small quantity does not lower the price significantly but has

D
MR

LMC

LAC

Price and cost (dollars per
pair of eyeglasses)

Quantity (millions of pairs of
eyeglasses per year)

$350

$400

0 700600500400300200100

$50

$100

$150

$200

$250

$300

Figure 6.9 Economies of
Scale as a Barrier to Entry

The firm maximizes its
profit by producing 300
million pairs of eyeglasses
per year and setting a price
of $250 per pair. If a new
firm enters the market and,
in order to gain economies
of scale, also produces
300 million pairs, the total
market quantity becomes
600 million pairs. The
demand curve shows that
at this quantity the price
falls to $100 per pair so that
both firms incur economic
losses.

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246  CHAPTER 6 Monopoly and Monopolistic Competition

higher costs because it does not gain any economies of scale. So the new entrant
(again) faces the possibility of an economic loss. Once again, the risk of an economic
loss may be enough to prevent entry.

Government Control of Entry
The government controls market entry in a variety of industries. The agency that
exercises jurisdiction can confer market power on a firm, at least locally, simply by
restricting or prohibiting the entry of competing firms, as in the electric utility exam-
ple. Industries in which the government regulates entry include banking, television
and radio broadcasting, and hospitals. In other markets, such as that for sugar, gov-
ernment tariff and quota restrictions mean that firms need government approval to
import sugar. None of these markets is strictly a monopoly because the firms in them
face at least some competition, but the government limitations often create substan-
tial barriers to entry.

In other circumstances, government regulations do not prohibit entry but instead
impose requirements that must be met before entry is allowed. Certification and
licensing are examples. At the individual level, physicians, nurses, and lawyers must
pass qualifying exams before they are allowed to practice. So, too, must hair stylists,
interior designers, and greenhouse managers. Many people will agree that requiring
physicians, nurses, and lawyers to pass qualifying exams is reasonable but will
doubt the validity of the similar requirements imposed on people who cut hair,
design home interiors, and oversee plant greenhouses. Clearly, these professions are
not monopolies, but the licensing requirements serve as barriers to entry and boost
the salaries earned by those in these professions.

Sunk Costs
Over the years, the economics literature has pointed to the existence of substantial
sunk costs from entering a market as a barrier to entry. As you learned in Chapter 1,
sunk costs are costs that cannot be recovered because they were paid or incurred
in the past. Many of the costs necessary to enter a market become sunk because
they cannot be recouped upon exit. For example, when the managers at Alamo
Drafthouse Cinema open a new theater, they must purchase specialized digital
projectors. Say that these cost $100,000 per screen, so opening an 8-plex theater
requires spending $800,000 on projectors. In addition, the owners must spend a
sizable amount on advertising to alert potential customers to the theater ’s open-
ing. If the theater fails, the resale price of the projectors is substantially less than
$800,000, and all of the funds spent on advertising are irretrievable. Because sunk
costs are lost if the entering firm later exits the industry, the presence of large
sunk costs increases the financial risk of entering the market, thereby creating a
barrier to entry. Clearly, the greater the sunk costs of entry, the higher the barrier
to entry.

Advertising
As noted above, advertising can increase the sunk cost of entering a market, but
economists have debated its other effects on market entry. On the one hand, adver-
tising by the incumbent producers can create brand loyalty that new entrants must
overcome. On the other hand, advertising by the new entrant can make consumers
aware of the new product’s attributes and price, facilitating profitable entry into the
market. So, in addition to creating a sunk cost, advertising can both discourage and
encourage market entry. Because its net effect varies from one industry to another,
the status of advertising as a barrier to entry is unclear.

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6.3 Dominant Firm  247

Merck’s Profit-Maximizing Price, Quantity, and Economic Profit

The following figure shows hypothetical demand, marginal revenue, marginal cost, and
average total cost curves for Januvia, a patented medicine made by Merck & Company
to help treat diabetes. Januvia has a very large market share in its market (that for DPP-4
inhibitors) because of its safety profile, so for simplicity we assume it is a monopoly. Use
the figure to answer the following questions.

a. What is the profit-maximizing quantity and price? What is the average total cost of
the profit-maximizing quantity?

b. Is Merck & Company making an economic profit or incurring an economic loss? How
much is the economic profit or loss?

Answer

a. The profit-maximizing quantity is the quantity that sets MR = MC , which is
200 million pills per month. The profit-maximizing price is the highest price the
managers can set and sell 200 million pills, which from the demand curve in the
figure is $5 per pill. The average total cost at the quantity of 200 million is $2 per pill.

b. Merck & Company is making an economic profit because P 7 ATC . The economic
profit equals 1P – ATC2 * Q, or 1$5 – $22 * 200 million = $600 million.

SOLVED
PROBLEM

D
MR

MC

ATC

Price and cost
(dollars per pill)

Quantity (millions of pills per month)

$7

$9

$8

0 400350300250200100 15050

$1

$2

$3

$4

$5

$6

6.3 Dominant Firm
Learning Objective 6.3 Describe how managers of a dominant firm
determine the quantity and price that maximize profit.

Outside the economics classroom, a single-firm monopoly is a relatively rare sight.
There are, however, many markets containing multiple firms in which one firm is
substantially larger than the others. Take the corn chip market. Frito-Lay, a division

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248  CHAPTER 6 Monopoly and Monopolistic Competition

of PepsiCo, controls about 76 percent of the corn chip market in the United States.
General Mills is the next largest company. It produces Bugles, which has about a
12 percent market share. The market also includes a number of small, regional pro-
ducers, each with market shares smaller than 3 percent. In this market structure,
Frito-Lay is considered a dominant firm, and the other producers are the competi-
tive fringe. A dominant firm, the one large firm in a market that includes many
other, smaller competing firms, has the lion’s share of the market. The competitive
fringe is a collective term for the many smaller firms in the market competing with
the one large, dominant firm.

The dominant firm model assumes that the dominant firm acts as a monopoly,
using its demand curve to maximize its profit, while the firms in the competitive
fringe act as perfectly competitive firms, maximizing their profit by taking the mar-
ket price—the dominant firm’s price—as given.

Dominant Firm’s Profit Maximization
Figure 6.10 is a hypothetical depiction of the corn chip market. Start by supposing
that Frito-Lay has a monopoly in this market. Using the profit-maximization rule,
Frito-Lay’s managers produce 140,000 tons of corn chips and set a price of $2.05 per
pound.

In reality, Frito-Lay is a dominant firm rather than a monopoly, so its managers
face the challenge of taking the collective supply response of the competitive fringe
into account when making their production and pricing decisions.

Dominant firm The one
large firm in a market that
includes many other,
smaller competing firms.

Competitive fringe The
many smaller firms in a
market that includes a
dominant firm.

D

MR

MC

Price and cost (dollars per
pound of corn chips)

Quantity (thousands of tons of
corn chips per year)

$2.25

$2.50

0

$0.25

$0.50

35030025020015010050

$0.75

$1.00

$1.25

$1.50

$1.75

$2.00

Monopoly profit-
maximizing price

Monopoly profit-
maximizing
quantity

Figure 6.10 A Monopoly
and the Market Demand
Curve

The graph shows the
hypothetical market
demand curve (D), the
marginal revenue curve
(MR), and marginal cost
curve (MC) for Frito-Lay. If
Frito-Lay was a monopoly,
its managers would
maximize profit by
producing 140,000 tons of
corn chips and setting a
price of $2.05 per pound.

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6.3 Dominant Firm  249

Residual Demand
In the more realistic case of Frito-Lay as a dominant firm, the competitive fringe
affects the demand for Frito-Lay’s corn chips. Figure 6.11 is a hypothetical depiction
of this effect. The graph shows the market demand curve (D) and the supply curve
of the competitive fringe (SCF). The demand that Frito-Lay faces does not equal the
market demand. Instead, it is the market demand minus the quantity supplied by
the competitive fringe, referred to as the residual demand. In Figure 6.11, the resid-
ual demand is RD. To see how the residual demand is constructed, take the price of
$2.00 per pound. At this price, the market demand curve (D) shows that the total
quantity demanded is 150,000 tons of chips, and the competitive fringe supply curve
(SCF) shows that the fringe firms produce 100,000 tons. Frito-Lay’s residual demand
is the quantity left over for consumers to demand from Frito-Lay and equals
150,000 – 100,000, or 50,000 tons. Consequently, at a price of $2.00 per pound,
Frito-Lay’s residual demand is 50,000 tons. The rest of the residual demand is deter-
mined similarly. Therefore, the dominant firm’s demand curve (D) has two parts: It
is the residual demand curve (RD) until it reaches the price at which it intersects the
market demand curve (D). After it reaches this point, the dominant firm’s demand
curve is identical to the market demand curve because after this point the com-
petitive fringe’s supply curve shows that its production is zero. Figure 6.12 illus-
trates the residual demand curve more clearly (without the irrelevant upper part
of the market demand curve).

The marginal revenue curve for the dominant firm also has two separate parts.
The top part is the marginal revenue curve that corresponds to the residual demand
curve—the light green line labeled RMR in Figure 6.12. At the quantity where the

Residual demand The
market demand minus
the quantity produced by
the competitive fringe.

D

RD

SCF

Price and cost (dollars per
pound of corn chips)

Quantity (thousands of tons of
corn chips per year)

$2.25

$2.50

0

$0.25

$0.50

35030025020015010050

$0.75

$1.00

$1.25

$1.50

$1.75

$2.00

Figure 6.11 Residual Demand Curve

The graph shows the hypothetical market demand
curve (D) for corn chips. The dominant firm, Frito-
Lay, faces the residual demand curve, which is
the market demand minus the quantity supplied
by the small, competitive fringe firms. For example,
at the price of $1.75 per pound of corn chips, the
supply curve of the competitive fringe (SCF) shows
that these firms produce 50,000 tons of chips. At
this price, the total quantity demanded is 200,000
tons of chips, so Frito-Lay’s residual demand is
200,000 minus 50,000, or 150,000 tons of chips. The
remainder of Frito-Lay’s residual demand is derived
similarly. Frito-Lay’s demand curve is the light blue
residual demand curve (RD) until it intersects the
market demand curve (D), after which Frito-Lay’s
demand curve becomes the same as the dark blue
market demand curve.

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250  CHAPTER 6 Monopoly and Monopolistic Competition

residual demand curve merges into the market demand curve, 250,000 tons, the
dominant firm’s marginal revenue curve drops downward and becomes the same as
the market marginal revenue curve, the dark green line labeled MR.

To maximize profit, Frito-Lay’s managers use the residual demand curve (RD)
and residual marginal revenue curve (RMR) because they represent the demand and
the marginal revenue for their chips, respectively. Frito-Lay produces the quantity
that sets its residual marginal revenue equal to its marginal cost (RMR = MC), so
Frito-Lay produces 150,000 tons of corn chips. The managers set the price using the
residual demand, resulting in a price of $1.75 per pound. The competitive fringe firms
are price takers, so they take the price of $1.75 as given and as their supply curve
shows, produce a total of 50,000 tons of corn chips at this price. The total quantity of
chips produced in the market is 200,000 tons—150,000 tons by the dominant firm and
50,000 tons by the competitive fringe firms. The price is $1.75 per pound. This price
and total quantity reflect a point on the market demand curve (D) shown in Figure 6.11.

Effect on the Dominant Firm of the Competitive Fringe
You can see the effect of competition on the choices the dominant firm’s managers
make. Faced with competition from the fringe firms, the managers increase production
from their monopoly amount of 140,000 tons of chips to 150,000 tons and lower the
price from the monopoly price of $2.05 per pound to $1.75 per pound. You can under-
stand why the managers lower the price by using the markup equation, Equation 6.5:

P
MC

= a e
e – 1

b

D

RD

RMR

MC

MR

SCF

Price and cost (dollars per
pound of corn chips)

Quantity (thousands of tons of
corn chips per year)

$2.25

$2.50

0

$0.25

$0.50

35030025020015010050

$0.75

$1.00

$1.25

$1.50

$1.75

$2.00

Dominant firm
profit-maximizing
price

Dominant firm
profit-maximizing
quantity

Figure 6.12 A Dominant Firm’s Profit Maximization

The dominant firm faces the light blue residual
demand curve, RD, until it intersects the market
demand curve at 250,000 tons of chips, after which
its demand curve becomes the dark blue market
demand curve, D. The marginal revenue curve for
the residual demand curve is the light green
residual marginal revenue curve, RMR, until the
quantity at which the residual demand curve
merges with the market demand curve, 250,000
tons of chips. After that, the marginal revenue
curve drops down and becomes the dark green
market marginal revenue curve, MR. The dominant
firm produces the quantity that sets its marginal
cost equal to its residual marginal revenue,
MC = RMR, and sets the price using the residual
demand curve. In the figure, the dominant firm
produces 150,000 tons of corn chips and sets a
price of $1.75 per pound. The competitive fringe
supply curve, SCF, shows that at this price the
fringe firms produce 50,000 tons of corn chips.

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6.3 Dominant Firm  251

The markup depends on the price elasticity of demand 1e2: The larger the
price elasticity of demand, the smaller the markup. At any quantity, the price
elasticity of demand is larger on the residual demand curve than on the market
demand curve. Why? Because a given change in the price leads to a larger change
in the quantity demanded along the residual demand curve than along the mar-
ket demand curve. Suppose that the price falls. Then the quantity demanded
along the market demand curve increases. The quantity demanded along the
residual demand curve also increases, but for two reasons: (1) The quantity
demanded in the market as a whole increases (the same effect just noted), and
(2) the fringe firms decrease the amount they sell. Because the change in the
quantity demanded is larger along the residual demand curve than the market
demand curve, the elasticity of demand for Frito-Lay’s chips is larger when it
faces competition. Consequently, the presence of the competitive fringe decreases
Frito-Lay’s price markup. This result is analogous to that illustrated in Figure 6.4,
in which a monopoly’s markup falls as the price elasticity of demand for its
product increases.

A dominant firm’s profit is less with the presence of the competitive fringe than
if it were a monopoly. As illustrated in Figure 6.12, even with an increase in produc-
tion (which conceivably could increase profit), the price falls substantially (which
substantially decreases the firm’s profit). From the perspective of Frito-Lay’s manag-
ers, the presence of the other firms decreases Frito-Lay’s profit. Indeed, the larger the
number of other firms, the greater the supply of the fringe firms, and the larger the
decrease in Frito-Lay’s profit. The managerial lesson is easy to state but difficult to
accomplish: Managers of dominant firms must strive to decrease the number of
competitive fringe firms.

Data centers and local area networks use Ethernet switches to join computers
together. Suppose that you are a manager at a firm like Cisco Systems, and yours
is the dominant firm in this market. Your market share exceeds 60 percent.
Suppose also that the next largest market shares are much smaller: Hewlett-
Packard has 9 percent, Alcatel-Lucent has 3 percent, Dell has 2 percent, and a
number of still smaller firms share the remaining 26 percent. Several of the
competitive fringe firms close. How should you adjust your firm’s quantity and
price in response to their exit from the market?

Answer
When several fringe firms exit, the supply of the competitive fringe decreases, so
your residual demand and marginal revenue increase. You should respond to the
increase in demand and marginal revenue by raising the quantity and price of
your Ethernet switches, increasing your firm’s economic profit.

DECISION
SNAPSHOT

How a Technology Firm Responds to
Changes in the Competitive Fringe

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252  CHAPTER 6 Monopoly and Monopolistic Competition

The Demand for Shoes at a Dominant Firm

The following table shows the hypothetical demand and competitive fringe supply for
the market for athletic shoes. Your firm has a market share of approximately 45 percent
and dominates this market. The next largest firm has a market share of less than 10 per-
cent. The table shows the market demand and competitive supply at different prices.
Use the table to solve the following problems.

a. Complete the table by calculating the residual demand at each price.

b. Use the formula from Chapter 3 for the price elasticity of demand, e = � b * 1P>Qd2 � ,
where b is the change in the quantity from a $1 change in price (calculated for any
two points on the demand curve as the change in quantity divided by the change in
price), to calculate the price elasticity of demand on the market demand curve and on
the residual demand curve at prices of $90, $85, $80, and $75 per pair of shoes. How
do the price elasticities of demand on the two demand curves compare?

Price (dollars per
pair of shoes)

Market Demand
(millions of shoes)

Competitive
Supply (millions of

shoes)

Residual Demand
(millions of shoes)

$90 100 40

85 120 30

80 140 20

75 160 10

70 180 0

65 200 0

Answer

a. The residual demand equals the market demand minus the competitive supply, so at
the price of $90, the residual demand equals 100 million shoes – 40 million shoes =
60 million shoes. Moving down the column, in millions of shoes, the rest of the residual
demands are 90, 120, 150, 180, and 200.

b. On the market demand curve, b = 4,000,000, and on the residual demand curve,
b = 6,000,000. At the price of $90 on the market demand curve, the price elasticity of
demand is 3.6, and on the residual demand curve, the price elasticity of demand is 9.0;
at the price of $85, they are 2.8 and 5.7; at the price of $80, they are 2.3 and 4.0; and at
the price of $75, they are 1.9 and 3.0. At each price, the price elasticity of demand is
larger on the residual demand curve than on the market demand curve.

SOLVED
PROBLEM

6.4 Monopolistic Competition
Learning Objective 6.4 Explain how managers of a monopolistically
competitive firm determine the quantity and price that maximize profit.

To this point in the chapter, you have learned about firms that are either alone in the
market or large relative to the competition. Not all firms with market power are
alone or dominant, however. For example, Apple has some control over the price it

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6.4 Monopolistic Competition  253

sets for its iPhone, but it faces numerous similar-sized competitors, including Sam-
sung, Google, LG, Microsoft, Huawei, Xiaomi, and HTC. Although Apple has a large
market share—about 15 percent worldwide—effectively it is only one firm among
many selling smartphones. The smartphone market is a monopolistically competi-
tive market, and Apple is a monopolistically competitive firm. Let’s begin our study
of monopolistic competition by discussing the characteristics that define this market
structure and the firms that compete within it.

Defining Characteristics of Monopolistic Competition
As its name implies, monopolistic competition combines elements of perfect compe-
tition and monopoly. Monopolistic competition is a market with many firms, with
no barriers to entry, and in which each firm produces a differentiated product. Let’s
begin with the two characteristics that monopolistic competition shares with perfect
competition and conclude with the one it shares with monopoly:

1. Many sellers. Both monopolistically competitive markets and perfectly com-
petitive markets include many firms, which limits each firm’s market power
over its price. Unlike the situation in a perfectly competitive market, however,
a monopolistically competitive firm’s market power is not totally eliminated
(see item 3).

2. No barriers to entry. Both perfectly competitive and monopolistically competi-
tive markets have many firms for the same reason: There are no barriers to entry.
This characteristic is a key difference between monopolistically competitive
firms and monopolies.

3. Differentiated products. Each product produced by a monopolistically competi-
tive firm is slightly different from the ones produced by other firms. Smart-
phones are an example of a differentiated product. All of the producers listed
above produce smartphones, but each smartphone is different—differentiated—
from the others. Although Apple’s smartphone is a substitute for those pro-
duced by its competitors, it is not a perfect substitute, which gives Apple some
market power to set its price.

Short-Run Profit Maximization for a Monopolistically
Competitive Firm
Assume that the managers of a monopolistically competitive firm want to maximize
profit. Like the managers of the other types of firms presented, these managers can
use marginal analysis and the profit-maximization rule to achieve their goal. They
need to determine their firm’s marginal revenue and combine it with their marginal
cost to determine the profit-maximizing quantity.

Demand, Marginal Revenue, and Marginal Cost for a Monopolistically
Competitive Firm
What does a monopolistically competitive firm’s demand curve look like? Con-
sider Apple and the iPhone. Because Apple’s smartphone differs from those of its
competitors, if Apple raises its price, some consumers will still buy it because they
prefer the iPhone. Likewise, if Apple lowers its price, not all consumers will switch
to an Apple smartphone because some still prefer their Android phones. So the
demand curve for an Apple smartphone is downward sloping, illustrated in
Figure 6.13 by hypothetical demand curve D. As you saw with the downward-sloping

Monopolistic
competition A market with
many firms, with no
barriers to entry, and in
which each firm produces
a differentiated product.

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254  CHAPTER 6 Monopoly and Monopolistic Competition

monopoly and dominant firm demand curves, the downward-sloping monopolisti-
cally competitive firm’s demand curve makes its marginal revenue curve (MR) lie
beneath the demand curve so that P 7 MR. The marginal cost curve (MC) shown
in Figure 6.13 is the same as the marginal cost curves used for monopolies and
perfectly competitive firms.

Figure 6.13 looks very similar to Figure 6.3, which shows the same curves for a
monopoly. This similarity, however, conceals a key difference: Figure 6.3 shows
demand and marginal revenue curves for the market, while Figure 6.13 shows the
demand and marginal revenue curves for the firm’s specific product.

Short-Run Profit Maximization for a Monopolistically Competitive
Firm: Marginal Analysis
The managers at a monopolistically competitive firm like Apple face the same profit-
maximization problem as the managers at a monopoly or dominant firm: They must
produce the quantity for which marginal revenue equals marginal cost and use the
demand to set their price. Figure 6.14 shows that short-run profit maximization is
the same for a monopolistically competitive firm as for a monopoly or dominant
firm. The figure shows that managers produce 200 million smartphones per year, the
quantity that sets the firm’s marginal revenue equal to its marginal cost, MR = MC,
or, equivalently, MR – MC = 0. All of the phones up to 200 million are profitable
because for each of them MR 7 MC. None of the phones beyond 200 million is prof-
itable because for each of them MR 6 MC. The firm then uses the demand for its
smartphones to set the highest price that consumers will pay for the 200 million
smartphones produced, $500.

As Figure 6.14 shows, the firm is making an economic profit because its price
exceeds its average total cost 1P 7 ATC2. The amount of the economic profit equals
the area of the green rectangle, 1$500 per phone – $300 per phone2 * 200 million
phones, or $40 billion. But can the firm’s economic profit last? Answering that
important question is the topic of the next section.

Figure 6.13 Demand,
Marginal Revenue, and
Marginal Cost Curves for
a Monopolistically
Competitive Firm

The downward-sloping
demand curve (D) for a
monopolistically
competitive firm makes
the marginal revenue
curve (MR) lie below the
demand curve. The
marginal cost curve (MC)
is the same as the
marginal cost curves for
monopolies and perfectly
competitive firms.

D

MR

MC

Price and cost (dollars
per smartphone)

Quantity (millions of smartphones per year)

$900

$0

$100

$200

35030025020015010050

$300

$400

$500

$600

$700

$800

2$200

2$100

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6.4 Monopolistic Competition  255

Long-Run Equilibrium for a Monopolistically
Competitive Firm
To this point, the analysis of a monopolistically competitive firm has been identical
to that of a monopoly. There is a key difference, however: A barrier to entry does not
protect the economic profit. Other firms can produce differentiated products similar
to those produced by the original firm. Once again, take Apple as an example. After
Apple released the first iPhone, many companies started to produce similar smart-
phones, such as the Samsung Galaxy and HTC One. As new products appear on the
market, some consumers prefer them, so the initial firm’s demand decreases, and its
demand and marginal revenue curves shift leftward. As long as the firms in the mar-
ket make an economic profit, new firms continue to enter. Entry stops only when the
firms are making zero economic profit, so that the owners are making only a com-
petitive return.

Figure 6.15 illustrates the long-run equilibrium for a monopolistically com-
petitive firm. As you can see, its managers maximize profit by producing 100 mil-
lion smartphones, the quantity for which MR = MC. Because of the new
competition it faces, the firm no longer makes an economic profit, since the price
equals the average total cost, P = ATC. In Figure 6.15, the price and average total
cost are $400 per smartphone. The long-run, zero economic profit result means that
the firm produces where its ATC curve is tangent to (just touches at one point) its
demand curve.

This conclusion reinforces what you learned in Chapter 5 about perfectly com-
petitive firms. If a monopolistically competitive firm is making a short-run eco-
nomic profit, the absence of a barrier to entry leads to increased competition in the
long run, which in turn forces the firm to produce at a point where it makes no
economic profit. This result clearly highlights the managerial importance of a bar-
rier to entry!

Figure 6.14 Short-Run Profit Maximization for a
Monopolistically Competitive Firm

The managers maximize profit by producing
200 million smartphones, the quantity that sets
MR = MC . The price of $500 is set using the
demand: It is the highest price that consumers will
pay for the 200 million smartphones produced.
The firm is making an economic profit because its
price exceeds its average total cost. The amount of
the economic profit equals the area of the green
rectangle, $40 billion.

D

MR

MC

ATC

Price and cost (dollars
per smartphone)

Quantity (millions of smartphones per year)

$900

$0

$100

$200

35030025020015010050

$300

$400

$500

$600

$700

$800

2$200

2$100

Profit-maximizing
price

Profit-
maximizing
quantity

MR . MC MR , MC

Economic profit,
$40 billion

M06_BLAI8235_01_SE_C06_pp227-273.indd 255 25/08/17 12:27 PM

256  CHAPTER 6 Monopoly and Monopolistic Competition

J-Phone’s Camera Phone

In 2000, the Japanese cell phone company J-Phone introduced the first widely successful
cell phone camera. It caught on quickly because it had a new feature not included in any of
the competitors’ phones: Customers were able to snap pictures and then immediately share
them with friends. J-Phone was a monopolistically competitive firm because it competed
with several other cell phone producers, each producing their own unique cell phone.

a. As a manager of J-Phone, how would you expect the price of your phone to change
over the next five years? How would you expect your sales to change over the same
period of time?

b. How do your answers to part a affect your decision about whether to expand your
manufacturing facilities?

Answer

a. Because J-Phone competes in a monopolistically competitive market, you must
expect that your wildly popular phone will soon face new competition from other
cell phone companies, causing the price of a cell phone with a camera to fall. (In
fact, prices fell quickly from $500 in 2000 to less than $300 in 2005.) You also must
expect that J-Phone’s market share will decrease when other companies market
their new phones. (Indeed, that is precisely what occurred: J-Phone’s market share
initially rose from 16.4 percent in 2001 to 18.5 percent in 2003 before falling back to
approximately 15.5 percent in 2005.)

b. Your answers to part a must give you pause when it comes to expanding your
manufacturing plant. You should worry that once your demand and price fall with
the arrival of new competition, you will be stuck with an uneconomically large
production facility if you expand.

SOLVED
PROBLEM

Figure 6.15 Long-Run Equilibrium for a
Monopolistically Competitive Firm

The managers maximize profit by producing
100 million smartphones, the quantity that sets
MR = MC . The price, $400 per smartphone, is
determined using the demand curve (D). In the
long run, competition from new producers
decreases the demand for smartphones
sufficiently that the firm no longer makes an
economic profit. The price equals the firm’s
average total cost.

D
MR

MC

ATC

Price and cost (dollars
per smartphone)

Quantity (millions of smartphones per year)

$900

$0

$100

$200

35030025020015010050

$300

$400

$500

$600

$700

$800

2$200

2$100

Profit-maximizing
price

Profit-
maximizing
quantity

M06_BLAI8235_01_SE_C06_pp227-273.indd 256 25/08/17 12:27 PM

6.5 Managerial Application: The Monopoly, Dominant Firm, and Monopolistic Competition Models  257

6.5 The Monopoly, Dominant Firm, and
Monopolistic Competition Models

Learning Objective 6.5 Apply what you have learned about monopolies,
dominant firms, and monopolistically competitive firms to make better
managerial decisions.

The most crucial managerial lesson about monopolies, dominant firms, and monop-
olistically competitive firms has been presented repeatedly throughout this chapter:
Use marginal analysis to determine the profit-maximizing quantity of production.
Managers in virtually all types of firms can reach the profit-maximizing quantity by
comparing the estimated marginal revenue to the estimated marginal cost and then
increasing production if marginal revenue exceeds marginal cost or decreasing pro-
duction if marginal revenue falls short of marginal cost.

A second, almost equally significant lesson is the importance of barriers to entry,
which enable you to maintain your firm’s economic profit indefinitely. If your barri-
ers to entry disappear, so, too, will your economic profit. Successful managers search
for ways to strengthen existing barriers or erect new ones, such as lobbying the gov-
ernment to impose regulations or requirements for new suppliers to fulfill.

Using the Models in Managerial Decision Making
As a manager, it is unlikely that you will have a figure showing marginal revenue,
marginal cost, and demand. But you still need to make decisions about the quantity
to produce and the price to charge. Section 5.4 pointed out that for perfectly compet-
itive firms, the profit-maximization rule, can be restated as “Produce all the units for
which MR – MC 7 0, and stop when you hit the unit with MR – MC = 0.” This
same result applies to firms with market power. In other words, managers of monop-
olies, dominant firms, and monopolistically competitive firms can all use the profit-
maximization rule to determine their profit-maximizing quantity.

Determining the Profit-Maximizing Price
The second part of the profit-maximization rule, “Set the highest price that sells the
quantity produced,” is immediately applicable if you have an estimate of your
demand. You can use your profit-maximizing quantity in your estimated demand
function and solve for the price. If you do not have an estimate of demand, you
have additional tools at your disposal: the relationships among price, marginal
cost, and elasticity of demand shown in Equation 6.4 and 6.5 and summarized in
the following box.

You can use estimates of your marginal cost and price elasticity of demand to set
the profit-maximizing price or, perhaps more realistically, to set a range of prices for
your product. Suppose that you again work for a pharmaceutical firm and your

MANAGERIAL
APPLICATION

• Price and marginal cost: The profit-maximizing relationship between price and

marginal cost is 1P = MC * ee – 12.
• Markup equation: The profit-maximizing markup of price over marginal cost is

PMC =
e

e – 1.

RELATIONSHIPS AMONG PRICE, MARGINAL COST, AND ELASTICITY
OF DEMAND

M06_BLAI8235_01_SE_C06_pp227-273.indd 257 25/08/17 12:27 PM

258  CHAPTER 6 Monopoly and Monopolistic Competition

company has another, newly developed drug with a marginal cost of $1,