The University of Texas Pan American The United States Labor Market Discussion

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The University of Texas Pan American

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In addition to it being illegal to enter the US without a visa or to over-stay one’s visa, it is also illegal for US employers to hire undocumented or “illegal” immigrants. Meanwhile, federal US enforcement of immigration laws tends to concentrate resources on reducing illegal immigration rather than on prosecuting US firms for employing undocumented workers. Using supply and demand analysis, show what would happen to the wage and employment level of undocumented workers if the government pursued more active enforcement of employers. According to your model, what would happen to the wage and employment level of documented workers?


Book is attached, must reference and answer the question. (CHAPTER 8)

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Labor Economics Seventh Edition George J. Borjas Harvard University LABOR ECONOMICS, SEVENTH EDITION Published by McGraw-Hill Education, 2 Penn Plaza, New York, NY 10121. Copyright © 2016 by McGraw-Hill Education. All rights reserved. Printed in the United States of America. Previous editions © 2013, 2010, and 2008. No part of this publication may be reproduced or distributed in any form or by any means, or stored in a database or retrieval system, without the prior written consent of McGraw-Hill Education, including, but not limited to, in any network or other electronic storage or transmission, or broadcast for distance learning. Some ancillaries, including electronic and print components, may not be available to customers outside the United States. This book is printed on acid-free paper. 1 2 3 4 5 6 7 8 9 0 DOC/DOC 1 0 9 8 7 6 5 ISBN 978-0-07-802188-6 MHID 0-07-802188-X Senior Vice President, Products & Markets: Kurt L. 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Library of Congress Cataloging-in-Publication Data Borjas, George J. Labor economics / George J. Borjas. — Seventh edition. pages cm ISBN 978-0-07-802188-6 (alk. paper) 1. Labor economics. 2. Labor market—United States. I. Title. HD4901.B674 2016 331.0973—dc23 2014031865 The Internet addresses listed in the text were accurate at the time of publication. The inclusion of a website does not indicate an endorsement by the authors or McGraw-Hill Education, and McGraw-Hill Education does not guarantee the accuracy of the information presented at these sites. www.mhhe.com About the Author George J. Borjas George J. Borjas is the Robert W. Scrivner Professor of Economics and Social Policy at the John F. Kennedy School of Government, Harvard University. He is also a research associate at the National Bureau of Economic Research and a Research Fellow at IZA. Professor Borjas received his Ph.D. in economics from Columbia University. Professor Borjas has written extensively on labor market issues. He is the author of several books, including Wage Policy in the Federal Bureaucracy (American Enterprise Institute, 1980), Friends or Strangers: The Impact of Immigrants on the U.S. Economy (Basic Books, 1990), Heaven’s Door: Immigration Policy and the American Economy (Princeton University Press, 1999), and Immigration Economics (Harvard University Press, 2014). He has published more than 125 articles in books and scholarly journals, including the American Economic Review, the Journal of Political Economy, and the Quarterly Journal of Economics. Professor Borjas was elected a Fellow of the Econometric Society in 1998, and a Fellow of the Society of Labor Economics in 2004. In 2011, Professor Borjas was awarded the IZA Prize in Labor Economics. He was an editor of the Review of Economics and Statistics from 1998 to 2006. He also has served as a member of the Advisory Panel in Economics at the National Science Foundation and has testified frequently before congressional committees and government commissions. iii The McGraw-Hill Series in Economics Essentials of Economics Brue, McConnell, and Flynn Essentials of Economics Third Edition Mandel Economics: The Basics Second Edition Schiller Essentials of Economics Ninth Edition Principles of Economics Colander Economics, Microeconomics, and Macroeconomics Ninth Edition Frank and Bernanke Principles of Economics, Principles of Microeconomics, and Principles of Macroeconomics Sixth Edition Frank and Bernanke Brief Editions: Principles of Economics, Principles of Microeconomics, and Principles of Macroeconomics Second Edition Karlan and Morduch Economics, Microeconomics, and Macroeconomics First Edition McConnell, Brue, and Flynn Economics, Microeconomics, and Macroeconomics Twentieth Edition McConnell, Brue, and Flynn Brief Editions: Economics, Microeconomics, and Macroeconomics Second Edition Miller Principles of Microeconomics First Edition Samuelson and Nordhaus Economics, Microeconomics, and Macroeconomics Nineteenth Edition Schiller The Economy Today, The Micro Economy Today, and The Macro Economy Today Thirteenth Edition Slavin Economics, Microeconomics, and Macroeconomics Eleventh Edition Economics of Social Issues Guell Issues in Economics Today Seventh Edition Sharp, Register, and Grimes Economics of Social Issues Twentieth Edition Econometrics Gujarati and Porter Basic Econometrics Fifth Edition Gujarati and Porter Essentials of Econometrics Fourth Edition Hilmer and Hilmer Practical Econometrics First Edition Managerial Economics Baye and Prince Managerial Economics and Business Strategy Eighth Edition Brickley, Smith, and Zimmerman Managerial Economics and Organizational Architecture Sixth Edition Thomas and Maurice Managerial Economics Eleventh Edition Intermediate Economics Frank Microeconomics and Behavior Ninth Edition Advanced Economics Romer Advanced Macroeconomics Fourth Edition Money and Banking Cecchetti and Schoenholtz Money, Banking, and Financial Markets Fourth Edition Urban Economics O’Sullivan Urban Economics Eighth Edition Labor Economics Borjas Labor Economics Seventh Edition McConnell, Brue, and Macpherson Contemporary Labor Economics Tenth Edition Public Finance Rosen and Gayer Public Finance Tenth Edition Seidman Public Finance First Edition Environmental Economics Field and Field Environmental Economics: An Introduction Sixth Edition International Economics Appleyard and Field International Economics Eighth Edition Bernheim and Whinston Microeconomics Second Edition King and King International Economics, Globalization, and Policy: A Reader Fifth Edition Dornbusch, Fischer, and Startz Macroeconomics Twelfth Edition Pugel International Economics Sixteenth Edition To Sarah, Timothy, and Rebecca v Preface to the Seventh Edition The original motivation for writing Labor Economics grew out of my years of teaching labor economics to undergraduates. After trying out many of the textbooks in the market, it seemed to me that students were not being exposed to what the essence of labor economics was about: to try to understand how labor markets work. As a result, I felt that students did not really grasp why some persons choose to work, while other persons withdraw from the labor market; why some firms expand their employment at the same time that other firms are laying off workers; or why earnings are distributed unequally in most societies. The key difference between Labor Economics and competing textbooks lies in its philosophy. I believe that knowing the story of how labor markets work is, in the end, more important than showing off our skills at constructing elegant models of the labor market or remembering hundreds of statistics and institutional details summarizing labor market conditions at a particular point in time. I doubt that many students will (or should!) remember the mechanics of deriving a labor supply curve or the way that the unemployment rate is officially calculated 10 or 20 years after they leave college. However, if students could remember the story of the way the labor market works—and, in particular, that workers and firms respond to changing incentives by altering the amount of labor they supply or demand—the students would be much better prepared to make informed opinions about the many proposed government policies that can have a dramatic impact on labor market opportunities, such as a “workfare” program requiring that welfare recipients work or a payroll tax assessed on employers to fund a national health care program or a guest worker program that grants tens of thousands of entry visas to high-skill workers. The exposition in this book, therefore, stresses the ideas that labor economists use to understand how the labor market works. The book also makes extensive use of labor market statistics and reports evidence obtained from hundreds of research studies. These data summarize the stylized facts that a good theory of the labor market should be able to explain, as well as help shape our thinking about the way the labor market works. The main objective of the book, therefore, is to survey the field of labor economics with an emphasis on both theory and facts. The book relies much more heavily on “the economic way of thinking” than competing textbooks. I believe this approach gives a much better understanding of labor economics than an approach that minimizes the story-telling aspects of economic theory. Requirements vi The book uses economic analysis throughout. All of the theoretical tools are introduced and explained in the text. As a result, the only prerequisite is that the student has some familiarity with the basics of microeconomics, particularly supply and demand curves. The exposure acquired in the typical introductory economics class more than satisfies this prerequisite. All other concepts (such as indifference curves, budget lines, production functions, and isoquants) are motivated, defined, and explained as they appear in our story. The book does not make use of any mathematical skills beyond those taught in high school algebra (particularly the notion of a slope). Preface to the Seventh Edition vii Labor economists also make extensive use of econometric analysis in their research. Although the discussion in this book does not require any prior exposure to econometrics, the student will get a much better “feel” for the research findings if they know a little about how labor economists manipulate data to reach their conclusions. The appendix to Chapter 1 provides a simple (and very brief) introduction to econometrics and allows the student to visualize how labor economists conclude, for instance, that wealth reduces labor supply, or that schooling increases earnings. Additional econometric concepts widely used in labor economics—such as the difference-in-differences estimator or instrumental variables—are introduced in the context of policy-relevant examples throughout the text. Changes in the Seventh Edition The Seventh Edition continues and expands traditions established in earlier editions. In particular, the text has a number of new detailed policy discussions and uses the evidence reported in state-of-the-art research articles to illustrate the many applications of modern labor economics. As before, the text continues to make frequent use of such econometric tools as fixed effects, the difference-in-differences estimator, and instrumental variables—tools that play a central role in the toolkit of labor economists. In keeping with my philosophy that textbooks are not meant to be encyclopedias, some of the material that had been a staple in earlier editions has been shortened and sometimes even excluded, so that the Seventh Edition is roughly the same length as previous editions. Users of the textbook reacted favorably to the substantial rearrangement of material (mainly of labor supply) that I carried out in previous editions. The Seventh Edition continues this reframing by tightening up and bringing together much of the discussion on immigration. Specifically, I have moved the derivation of the immigration surplus model to the general discussion of international migration in the labor mobility chapter. This rearrangement of the material gave me the opportunity to add a new section that shows how the gains from immigration can be greatly increased if immigrants generate human capital externalities in the receiving country’s labor market. The extension of the immigration surplus model allows for an even more policy-relevant (and economically interesting) coverage of an important topic—a topic that many students find to be a particularly useful application of the theoretical models of labor economics. The last edition introduced a Mathematical Appendix that appears at the end of the textbook. This appendix presents a mathematical version of some of the canonical models in labor economics, including the neoclassical model of labor-leisure choice, the model of labor demand, and the schooling model. It is important to emphasize that the Mathematical Appendix is an “add-on.” None of the material in this appendix is a prerequisite to reading or understanding any of the discussion in the core chapters of the textbook. Instructors who like to provide a more technical derivation of the various models can use the appendix as a takeoff point for their own presentation. Many instructors welcomed the addition of the mathematical appendix to the textbook. I, in turn, would truly welcome any suggestions about how the appendix can be expanded in future editions. Among the specific changes contained in the Seventh Edition are: 1. Several new “Theory at Work” boxes. The sidebars now include a discussion of how workers take advantage of the institutional features of the Earned Income Tax Credit viii Preface to “bunch up” their hours and ensure they receive the maximum subsidy; the interesting relation between increases in the minimum wage and teenage drunk driving; the important role that “Rosenwald schools” played in narrowing the education gap between white and African-American workers; and the labor market impact of explicit gender discrimination in employment ads in China. 2. A careful updating of all the data tables in the text. To the extent possible, the tables now include information on the rapidly growing demographic group of “Asians” in the U.S. labor market and the text often discusses the differences between Asians and other racial/ethnic groups. 3. A careful summary and discussion of unemployment trends in the United States since the financial crisis of 2008 and the subsequent Great Recession. 4. New sections that discuss the labor market effects of Obamacare; the experimental evidence on the link between various methods of incentive pay for teachers and student achievement; the labor market impact of the explosive growth in trade with China; the potentially important role played by the human capital spillovers presumably generated by high-skill immigration; and the link between compensating differentials and income taxes. As in previous editions, each chapter contains “Web Links,” guiding students to websites that provide additional data or policy discussions. There is an updated list of “Selected Readings” that includes both standard references in a particular area as well as recent applications. Finally, each chapter in the Seventh Edition continues to offer 15 end-of-chapter problems, but there is at least one brand new problem in each chapter. Organization of the Book The instructor will find that this book is much shorter than competing labor economics textbooks. The book contains an introductory chapter, plus 11 substantive chapters. If the instructor wished to cover all of the material, each chapter could serve as the basis for about a week’s worth of lectures in a typical undergraduate semester course. Despite the book’s brevity, the instructor will find that all of the key topics in labor economics are covered. The discussion, however, is kept to essentials as I have tried very hard not to deviate into tangential material, or into 10-page-long ruminations on my pet topics. Chapter 1 presents a brief introduction that exposes the student to the concepts of labor supply, labor demand, and equilibrium. The chapter uses the “real-world” example of the Alaskan labor market during the construction of the oil pipeline to introduce these concepts. In addition, the chapter shows how labor economists contrast the theory with the evidence, as well as discusses the limits of the insights provided by both the theory and the data. The example used to introduce the student to regression analysis is drawn from “real-world” data—and looks at the link between differences in mean wages across occupations and differences in educational attainment as well as the “female-ness” of occupations. The book begins the detailed analysis of the labor market with a detailed study of labor supply and labor demand. Chapter 2 examines the factors that determine whether a person chooses to work and, if so, how much, while Chapter 3 examines the factors that determine how many workers a firm wants to hire. Chapter 4 puts together the supply decisions of workers with the demand decisions of employers and shows how the labor market “balances out” the conflicting interests of the two parties. Preface to the Seventh Edition ix The remainder of the book extends and generalizes the basic supply–demand framework. Chapter 5 stresses that jobs differ in their characteristics, so that jobs with unpleasant working conditions may have to offer higher wages in order to attract workers. Chapter 6 stresses that workers are different because they differ either in their educational attainment or in the amount of on-the-job training they acquire. These human capital investments help determine the economy’s wage distribution. Chapter 7 discusses how changes in the rate of return to skills in the 1980s and 1990s changed the wage distribution in many industrialized economies, particularly in the United States. Chapter 8 describes a key mechanism that allows the labor market to balance out the interests of workers and firms, namely labor turnover and migration. The final section of the book discusses a number of distortions and imperfections in labor markets. Chapter 9 analyzes how labor market discrimination affects the earnings and employment opportunities of minority workers and women. Chapter 10 discusses how labor unions affect the relationship between the firm and the worker. Chapter 11 notes that employers often find it difficult to monitor the activities of their workers, so that the workers will often want to “shirk” on the job. The chapter discusses how different types of incentive pay systems arise to discourage workers from misbehaving. Finally, Chapter 12 discusses why unemployment can exist and persist in labor markets. The text uses a number of pedagogical devices designed to deepen the student’s understanding of labor economics. A chapter typically begins by presenting a number of stylized facts about the labor market, such as wage differentials between blacks and whites or between men and women. The chapter then presents the story that labor economists have developed to understand why these facts are observed in the labor market. Finally, the chapter extends and applies the theory to related labor market phenomena. Each chapter typically contains at least one lengthy application of the material to a major policy issue, as well as several boxed examples showing the “Theory at Work.” The end-of-chapter material also contains a number of student-friendly devices. There is a chapter summary describing briefly the main lessons of the chapter; a “Key Concepts” section listing the major concepts introduced in the chapter (when a key concept makes its first appearance, it appears in boldface). Each chapter includes “Review Questions” that the student can use to review the major theoretical and empirical issues, a set of 15 problems that test the students’ understanding of the material, as well as a list of “Selected Readings” to guide interested students to many of the standard references in a particular area of study. Each chapter then ends with “Web Links,” listing websites that can provide more detailed information about particular issues. Supplements for the Book There are several learning and teaching aids that accompany the seventh edition of Labor Economics. These resources are available to instructors for quick download and convenient access via the Instructor Resource material available through McGraw-Hill Connect®. A Solutions Manual and Test Bank have been prepared by Robert Lemke of Lake Forest College. The Solutions Manual provides detailed answers to all of the end-of-chapter problems. The comprehensive Test Bank offers over 350 multiple-choice questions in Word and electronic format. Test questions have now been categorized by AACSB learning categories, Bloom’s Taxonomy, level of difficulty, and the topic to which they relate. x Preface The computerized Test Bank is available through McGraw-Hill’s EZ Test Online, a flexible and easy-to-use electronic testing program. It accommodates a wide range of question types and you can add your own questions. Multiple versions of the test can be created and any test can be exported for use with course management systems such as Blackboard. The program is available for Windows and Macintosh environments. PowerPoint Presentations prepared by Michael Welker of Franciscan University of Steubenville, contain a detailed review of the important concepts presented in each chapter. The slides can be adapted and edited to fit the needs of your course. A Digital Image Library is also included, which houses all of the tables and figures featured in this book. Digital Solutions McGraw-Hill Connect® Economics Less Managing. More Teaching. Greater Learning. McGraw-Hill’s Connect® Economics is an online assessment solution that connects students with the tools and resources they’ll need to achieve success. McGraw-Hill’s Connect Economics Features Connect Economics allows faculty to create and deliver exams easily with selectable test bank items. Instructors can also build their own questions into the system for homework or practice. Other features include: Instructor Library The Connect Economics Instructor Library is your repository for additional resources to improve student engagement in and out of class. You can select and use any asset that enhances your lecture. The Connect Economics Instructor Library includes all of the instructor supplements for this text. Student Resources Any supplemental resources that align with the text for student use will be available through Connect. Student Progress Tracking Connect Economics keeps instructors informed about how each student, section, and class is performing, allowing for more productive use of lecture and office hours. The progress-tracking function enables you to: • View scored work immediately and track individual or group performance with assignment and grade reports. • Access an instant view of student or class performance relative to learning objectives. • Collect data and generate reports required by many accreditation organizations, such as AACSB. Diagnostic and Adaptive Learning of Concepts: LearnSmart and SmartBook offer the first and only adaptive reading experience designed to change the way students read and learn. Students want to make the best use of their study time. The LearnSmart adaptive self-study technology within Connect Economics provides students with a seamless combination of practice, assessment, and remediation for every concept Preface to the Seventh Edition xi in the textbook. LearnSmart’s intelligent software adapts to every student response and automatically delivers concepts that advance students’ understanding while reducing time devoted to the concepts already mastered. The result for every student is the fastest path to mastery of the chapter concepts. LearnSmart: • Applies an intelligent concept engine to identify the relationships between concepts and to serve new concepts to each student only when he or she is ready. • Adapts automatically to each student, so students spend less time on the topics they understand and practice more those they have yet to master. • Provides continual reinforcement and remediation, but gives only as much guidance as students need. • Integrates diagnostics as part of the learning experience. • Enables you to assess which concepts students have efficiently learned on their own, thus freeing class time for more applications and discussion. Smartbook is an extension of LearnSmart—an adaptive eBook that helps students focus their study time more effectively. As students read, Smartbook assesses comprehension and dynamically highlights where they need to study more. For more information about Connect, go to connect.mheducation.com, or contact your local McGraw-Hill sales representative. McGraw-Hill’s Customer Experience Group We understand that getting the most from your new technology can be challenging. That’s why our services don’t stop after you purchase our products. You can e-mail our Product Specialists 24 hours a day to get product-training online. Or you can search our knowledge bank of Frequently Asked Questions on our support website. For Customer Support, call 800-331-5094, or visit www.mhhe.com/support. McGraw-Hill Create™ is a self-service website that allows you to create customized course materials using McGraw-Hill’s comprehensive, crossdisciplinary content and digital products. You can even access third-party content such as readings, articles, cases, and videos. Arrange the content you’ve selected to match the scope and sequence of your course. Personalize your book with a cover design and choose the best format for your students–eBook, color print, or black-and-white print. And, when you are done, you’ll receive a PDF review copy in just minutes! Go paperless with eTextbooks from CourseSmart and move light years beyond traditional print textbooks. Read online or offline anytime, anywhere. Access your eTextbook on multiple devices with or without an internet connection. CourseSmart eBooks include convenient, built-in tools that let you search topics quickly, add notes and highlights, copy/paste passages, and print any page. Acknowledgments I have benefited from countless e-mail messages sent by users of the textbook—both students and instructors. These messages often contained very valuable suggestions, most of which found their way into the Seventh Edition. I strongly encourage users to contact me (gborjas@harvard.edu) with any comments or changes that they would like to see included in the next revision. I am grateful to Robert Lemke of Lake Forest College, who updated the quiz questions for this edition, helped me expand the menu of end-of-chapter problems, and collaborated in and revised the Solutions Manual and Test Bank; and Michael Welker, Franciscan University of Steubenville, who created the PowerPoint presentation for the Seventh Edition. I am particularly grateful to many friends and colleagues who have generously shared some of their research data so that I could summarize and present it in a relatively simple way throughout the textbook, including Daniel Aaronson, David Autor, William Carrington, Chad Cotti, John Friedman, Barry Hirsch, Lawrence Katz, Alan Krueger, David Lee, Bhashkar Mazumder, and Solomon Polachek. Finally, I have benefited from the comments and detailed reviews made by many colleagues on the earlier editions. These colleagues include: Ulyses Balderas Sam Houston State University Laura Boyd Denison University Lawrence Boyd University of Hawaii, West Oahu Kristine Brown University of Illinois–Champaign John Buck Jacksonville University Darius Conger Ithaca College Jeffrey DeSimone University of Texas Arlington Richard Dibble New York Institute Technology Andrew Ewing University of Washington Julia Frankland Malone University Steffen Habermalz Northwestern University xii Mehdi Haririan Bloomsburg University of Pennsylvania Masanori Hashimoto Ohio State University–Columbus James Hill Central Michigan University Robert N. Horn James Madison University Jessica Howell California State University–Sacramento Sarah Jackson Indiana University of Pennsylvania–Indiana Thomas Kniesner Syracuse University Cory Koedel University of Missouri–Columbia Myra McCrickard Bellarmine University Elda Pema Naval Postgraduate School Esther Redmount Colorado College Acknowledgments xiii Jeff Sarbaum University of North Carolina–Greensboro Martin Shields Colorado State University Todd Steen Hope College Erdal Tekin Georgia State University Alejandro Velez Saint Mary’s University Elizabeth Wheaton Southern Methodist University Janine Wilson University of California–Davis Contents in Brief 1 Introduction to Labor Economics 2 Labor Supply 3 Labor Demand 1 21 144 5 Compensating Wage Differentials 196 229 7 The Wage Structure 8 Labor Mobility 282 312 9 Labor Market Discrimination xiv 412 11 Incentive Pay 458 12 Unemployment 494 84 4 Labor Market Equilibrium 6 Human Capital 10 Labor Unions 362 MATHEMATICAL APPENDIX: SOME STANDARD MODELS IN LABOR ECONOMICS 541 NAME INDEX 552 SUBJECT INDEX 560 Contents Chapter 1 Introduction to Labor Economics Summary 79 Key Concepts 79 Review Questions 79 Problems 80 Selected Readings 83 Web Links 83 1 1-1 An Economic Story of the Labor Market 2 1-2 The Actors in the Labor Market 3 1-3 Why Do We Need a Theory? 7 Summary 11 Review Questions 11 Key Concepts 11 Web Links 11 Appendix: An Introduction to Regression Analysis 12 Key Concepts 20 Chapter 2 Labor Supply 21 2-1 2-2 2-3 2-4 2-5 2-6 2-7 2-8 2-9 2-10 Measuring the Labor Force 22 Basic Facts about Labor Supply 24 The Worker’s Preferences 27 The Budget Constraint 31 The Hours of Work Decision 33 To Work or Not to Work? 39 The Labor Supply Curve 42 Estimates of the Labor Supply Elasticity 45 Labor Supply of Women 50 Policy Application: Welfare Programs and Work Incentives 54 2-11 Policy Application: The Earned Income Tax Credit 59 2-12 Labor Supply over the Life Cycle 64 2-13 Policy Application: The Decline in Work Attachment among Older Workers 73 Theory at Work: Dollars and Dreams 40 Theory at Work: Winning the Lotto Will Change Your Life 43 Theory at Work: Work and Leisure in Europe and the United States 48 Theory at Work: Gaming the EITC 63 Theory at Work: Cabbies in New York City 69 Theory at Work: The Notch Babies 75 Chapter 3 Labor Demand 84 3-1 3-2 The Production Function 85 The Employment Decision in the Short Run 88 3-3 The Employment Decision in the Long Run 94 3-4 The Long-Run Demand Curve for Labor 98 3-5 The Elasticity of Substitution 105 3-6 Policy Application: Affirmative Action and Production Costs 106 3-7 Marshall’s Rules of Derived Demand 109 3-8 Factor Demand with Many Inputs 112 3-9 Overview of Labor Market Equilibrium 114 3-10 Policy Application: The Employment Effects of Minimum Wages 115 3-11 Adjustment Costs and Labor Demand 127 3-12 Rosie the Riveter as an Instrumental Variable 133 Theory at Work: California’s Overtime Regulations and Labor Demand 104 Theory at Work: Minimum Wages and Drunk Driving 125 Theory at Work: Work-Sharing in Germany 132 Summary 139 Key Concepts 139 Review Questions 140 Problems 140 Selected Readings 143 Web Links 143 xv xvi Contents Chapter 4 Labor Market Equilibrium 4-1 4-2 4-3 4-4 4-5 4-6 4-7 4-8 Selected Readings Web Links 228 144 Equilibrium in a Single Competitive Labor Market 145 Competitive Equilibrium across Labor Markets 147 Policy Application: Payroll Taxes and Subsidies 152 Policy Application: Payroll Taxes versus Mandated Benefits 159 Policy Application: The Labor Market Impact of Immigration 163 Policy Application: Environmental Disasters and the Labor Market 177 The Cobweb Model 180 Noncompetitive Labor Markets: Monopsony 183 Theory at Work: The Intifadah and Palestinian Wages 146 Summary 190 Key Concepts 191 Review Questions 191 Problems 191 Selected Readings 194 Web Links 195 Chapter 5 Compensating Wage Differentials 5-1 5-2 5-3 5-4 5-5 5-6 Chapter 6 Human Capital 6-1 6-2 6-3 6-4 6-5 6-6 6-7 6-8 6-9 6-10 6-11 6-12 6-13 The Market for Risky Jobs 197 The Hedonic Wage Function 203 Policy Application: How Much Is a Life Worth? 207 Policy Application: Safety and Health Regulations 210 Compensating Differentials and Job Amenities 213 Policy Application: Health Insurance and the Labor Market 219 Summary 222 Key Concepts 223 Review Questions 223 Problems 223 229 Education in the Labor Market: Some Stylized Facts 230 Present Value 232 The Schooling Model 232 Education and Earnings 239 Estimating the Rate of Return to Schooling 244 Policy Application: School Construction in Indonesia 247 Policy Application: School Quality and Earnings 249 Do Workers Maximize Lifetime Earnings? 254 Schooling as a Signal 257 Postschool Human Capital Investments 263 On-the-Job Training 264 On-the-Job Training and the Age-Earnings Profile 268 Policy Application: Evaluating Government Training Programs 273 Theory at Work: Destiny at Age 6 243 Theory at Work: Booker T. Washington and Julius Rosenwald 250 Theory at Work: Is the GED Better Than Nothing? 261 Theory at Work: Earnings and Substance Abuse 272 196 Theory at Work: Life On the Interstate 210 Theory at Work: Jumpers in Japan 213 227 Summary 275 Key Concepts 276 Review Questions 276 Problems 277 Selected Readings 280 Web Links 281 Chapter 7 The Wage Structure 7-1 7-2 7-3 282 The Earnings Distribution 283 Measuring Inequality 285 The Wage Structure: Basic Facts 288 Contents 7-4 7-5 7-6 Policy Application: Why Did Wage Inequality Increase? 291 The Earnings of Superstars 300 Inequality across Generations 303 Theory at Work: Computers, Pencils, and the Wage Structure 297 Theory at Work: Rock Superstars 302 Theory at Work: Nature and Nurture 306 Summary 306 Key Concepts 307 Review Questions 307 Problems 307 Selected Readings 310 Web Links 311 Chapter 8 Labor Mobility 8-1 8-2 8-3 8-4 8-5 8-6 8-7 8-8 8-9 8-10 8-11 8-12 8-13 312 Geographic Migration as a Human Capital Investment 313 Internal Migration in the United States 314 Family Migration 319 Immigration in the United States 322 Immigrant Performance in the U.S. Labor Market 324 The Decision to Immigrate 330 The Economic Benefits from Immigration 335 Policy Application: High-Skill Immigration and Human Capital Externalities 338 Policy Application: Intergenerational Mobility of Immigrants 342 Job Turnover: Facts 346 The Job Match 350 Specific Training and Job Turnover 352 Job Turnover and the Age-Earnings Profile 353 Theory at Work: Power Couples 322 Theory at Work: Hey Dad, My Roommate Is So Smart, I Got a 4.0 GPA 343 Theory at Work: Health Insurance and Job-Lock 351 Summary 356 Key Concepts 357 Review Questions 357 Problems 358 Selected Readings Web Links 361 xvii 361 Chapter 9 Labor Market Discrimination 362 9-1 9-2 9-3 9-4 9-5 9-6 9-7 Race and Gender in the Labor Market 363 The Discrimination Coefficient 365 Employer Discrimination 366 Employee Discrimination 373 Customer Discrimination 374 Statistical Discrimination 376 Experimental Evidence on Discrimination 381 9-8 Measuring Discrimination 382 9-9 Policy Application: Determinants of the Black–White Wage Ratio 387 9-10 Discrimination against Other Groups 395 9-11 Policy Application: Determinants of the Female–Male Wage Ratio 398 Theory at Work: Beauty and the Beast 372 Theory at Work: Discrimination in the NBA 377 Theory at Work: Employment Discrimination in China 383 Theory at Work: “Disparate Impact” and Black Employment in Police Departments 390 Theory at Work: Shades of Black 394 Theory at Work: 9/11 and the Earnings of Arabs and Muslims in the United States 397 Theory at Work: Orchestrating Impartiality 401 Summary 405 Key Concepts 406 Review Questions 406 Problems 406 Selected Readings 410 Web Links 411 Chapter 10 Labor Unions 10-1 10-2 10-3 10-4 412 Unions: Background and Facts 413 Determinants of Union Membership 417 Monopoly Unions 423 Policy Application: Unions and Resource Allocation 425 xviii Contents 10-5 10-6 10-7 10-8 10-9 Efficient Bargaining 427 Strikes 433 Union Wage Effects 439 Nonwage Effects of Unions 445 Policy Application: Public-Sector Unions 448 Theory at Work: The Rise and Fall of PATCO 422 Theory at Work: The Cost of Labor Disputes 436 Theory at Work: Occupational Licensing 444 Theory at Work: Do Teachers’ Unions Make Students Better Off? 449 Theory at Work: Lawyers and Arbitration 450 Summary 451 Key Concepts 452 Review Questions 452 Problems 453 Selected Readings 457 Web Links 457 Chapter 11 Incentive Pay 458 11-1 Piece Rates and Time Rates 458 11-2 Tournaments 465 11-3 Policy Application: The Compensation of Executives 472 11-4 Policy Application: Incentive Pay for Teachers 474 11-5 Work Incentives and Delayed Compensation 477 11-6 Efficiency Wages 480 Theory at Work: Windshields by the Piece 463 Theory at Work: How Much is Your Soul Worth? 466 Theory at Work: Incentive Pay Gets You to LAX on Time 468 Theory at Work: Playing Hard for the Money 471 Theory at Work: Are Men More Competitive? 474 Theory at Work: Did Henry Ford Pay Efficiency Wages? 484 Summary 489 Key Concepts 489 Review Questions 490 Problems 490 Selected Readings 493 Web Links 493 Chapter 12 Unemployment 12-1 12-2 12-3 12-4 12-5 12-6 12-7 12-8 12-9 12-10 12-11 494 Unemployment in the United States 495 Types of Unemployment 503 The Steady-State Rate of Unemployment 504 Job Search 506 Policy Application: Unemployment Compensation 513 The Intertemporal Substitution Hypothesis 520 The Sectoral Shifts Hypothesis 521 Efficiency Wages and Unemployment 522 Implicit Contracts 526 Policy Application: The Phillips Curve 528 Policy Application: The Unemployment Gap between Europe and the United States 532 Theory at Work: The Long-Term Effects of Graduating in a Recession 501 Theory at Work: Jobs and Friends 507 Theory at Work: Cash Bonuses and Unemployment 515 Theory at Work: The Benefits of UI 519 Summary 535 Key Concepts 536 Review Questions 536 Problems 537 Selected Readings 540 Web Links 540 Mathematical Appendix: Some Standard Models in Labor Economics 541 Indexes 552 Name Index 552 Subject Index 560 1 Chapter Introduction to Labor Economics Observations always involve theory. —Edwin Hubble Most of us will allocate a substantial fraction of our time to the labor market. How we do in the labor market helps determine our wealth, the types of goods we can afford to consume, with whom we associate, where we vacation, which schools our children attend, and even the types of persons who find us attractive. As a result, we are all eager to learn how the labor market works. Labor economics studies how labor markets work. Our interest in labor markets arises not only from our personal involvement but also because many social policy issues concern the labor market experiences of particular groups of workers or various aspects of the employment relationship between workers and firms. The policy issues examined by modern labor economics include 1. Why did the labor force participation of women rise steadily throughout the past century in many industrialized countries? 2. What is the impact of immigration on the wage and employment opportunities of native-born workers? 3. Do minimum wages increase the unemployment rate of less-skilled workers? 4. What is the impact of occupational safety and health regulations on employment and earnings? 5. Are government subsidies of investments in human capital an effective way to improve the economic well-being of disadvantaged workers? 6. Why did wage inequality in the United States rise so rapidly after 1980? 7. What is the impact of affirmative action programs on the earnings of women and minorities and on the number of women and minorities that firms hire? 8. What is the economic impact of unions, both on their members and on the rest of the economy? 1 2 Chapter 1 9. Do generous unemployment insurance benefits lengthen the duration of spells of unemployment? 10. Why did the unemployment rate in the United States begin to approach the typically higher unemployment rate of European countries after 2008? This diverse list of questions clearly illustrates why the study of labor markets is intrinsically more important and more interesting than the study of the market for butter (unless one happens to be in the butter business!). Labor economics helps us understand and address many of the social and economic problems facing modern societies. 1-1 An Economic Story of the Labor Market This book tells the “story” of how labor markets work. Telling this story involves much more than simply recounting the history of labor law in the United States or in other countries and presenting reams of statistics summarizing conditions in the labor market. After all, good stories have themes, characters that come alive with vivid personalities, conflicts that have to be resolved, ground rules that limit the set of permissible actions, and events that result inevitably from the interaction among characters. The story we will tell about the labor market has all of these features. Labor economists typically assign motives to the various “actors” in the labor market. We typically view workers, for instance, as trying to find the best possible job and assume that firms are trying to make money. Workers and firms, therefore, enter the labor market with different objectives—workers are trying to sell their labor at the highest price and firms are trying to buy labor at the lowest price. The types of economic exchanges that can occur between workers and firms are limited by the set of ground rules that the government has imposed to regulate transactions in the labor market. Changes in these rules and regulations would obviously lead to different outcomes. For instance, a minimum wage law prohibits exchanges that pay less than a particular amount per hour worked; occupational safety regulations forbid firms from offering working conditions that are deemed too risky to the worker’s health. The deals that are eventually struck between workers and firms determine the types of jobs that are offered, the skills that workers acquire, the extent of labor turnover, the structure of unemployment, and the observed earnings distribution. The story thus provides a theory, a framework for understanding, analyzing, and predicting a wide array of labor market outcomes. The underlying philosophy of the book is that modern economics provides a useful story of how the labor market works. The typical assumptions we make about the behavior of workers and firms, and about the ground rules under which the labor market participants make their transactions, suggest outcomes often corroborated by the facts observed in real-world labor markets. The study of labor economics, therefore, helps us understand and predict why some labor market outcomes are more likely to be observed than others. Our discussion is guided by the belief that learning the story of how labor markets work is as important as knowing basic facts about the labor market. The study of facts without theory is just as empty as the study of theory without facts. Without understanding how labor markets work—that is, without having a theory of why workers and firms pursue some employment relationships and avoid others—we would be hard-pressed to predict the impact on the labor market of changes in government policies or changes in the demographic composition of the workforce. Introduction to Labor Economics 3 A question often asked is which is more important—ideas or facts? The analysis presented throughout this book stresses that “ideas about facts” are most important. We do not study labor economics so that we can construct elegant mathematical theories of the labor market, or so that we can remember how the official unemployment rate is calculated and that the unemployment rate was 6.9 percent in 1993. Rather, we want to understand which economic and social factors generate a certain level of unemployment, and why. The main objective of this book is to survey the field of labor economics with an emphasis on both theory and facts: where the theory helps us understand how the facts are generated and where the facts can help shape our thinking about the way labor markets work. 1-2 The Actors in the Labor Market Throughout the book, we will see that there are three leading actors in the labor market: workers, firms, and the government.1 As workers, we receive top casting in the story. Without us, after all, there is no “labor” in the labor market. We decide whether to work or not, how many hours to work, how much effort to allocate to the job, which skills to acquire, when to quit a job, which occupations to enter, and whether to join a labor union. Each of these decisions is motivated by the desire to optimize, to choose the best available option from the various choices. In our story, therefore, workers will always act in ways that maximize their well-being. Adding up the decisions of millions of workers generates the economy’s labor supply not only in terms of the number of persons who enter the labor market but also in terms of the quantity and quality of skills available to employers. As we will see many times throughout the book, persons who want to maximize their well-being tend to supply more time and more effort to those activities that have a higher payoff. The labor supply curve, therefore, is often upward sloping, as illustrated in Figure 1-1. The hypothetical labor supply curve drawn in the figure gives the number of engineers that will be forthcoming at every wage. For example, 20,000 workers are willing to supply their services to engineering firms if the engineering wage is $40,000 per year. If the engineering wage rises to $50,000, then 30,000 workers will choose to be engineers. In other words, as the engineering wage rises, more persons will decide that the engineering profession is a worthwhile pursuit. More generally, the labor supply curve relates the number of person-hours supplied to the economy to the wage that is being offered. The higher the wage that is being offered, the larger the labor supplied. Firms co-star in our story. Each firm must decide how many and which types of workers to hire and fire, the length of the workweek, how much capital to employ, and whether to offer a safe or risky working environment to its workers. Like workers, firms in our story also have motives. In particular, we will assume that firms want to maximize profits. From the firm’s point of view, the consumer is king. The firm will maximize its profits by making the production decisions—and hence the hiring and firing decisions—that best 1 In some countries, a fourth actor can be added to the story: trade unions. Unions may organize a large fraction of the workforce and represent the interests of workers in their bargaining with employers as well as influence political outcomes. In the United States, however, the trade union movement has been in decline for several decades. By 2010, only 6.9 percent of private-sector workers were union members. 4 Chapter 1 FIGURE 1-1 Supply and Demand in the Engineering Labor Market The labor supply curve gives the number of persons who are willing to supply their services to engineering firms at a given wage. The labor demand curve gives the number of engineers that the firms will hire at that wage. Labor market equilibrium occurs where supply equals demand. In equilibrium, 20,000 engineers are hired at a wage of $40,000. Earnings ($) Labor Supply Curve 50,000 Equilibrium 40,000 Labor Demand Curve 30,000 Employment 10,000 20,000 30,000 serve the consumers’ needs. In effect, the firm’s demand for labor is a derived demand, a demand derived from the desires of consumers. Adding up the hiring and firing decisions of millions of employers generates the economy’s labor demand. The assumption that firms want to maximize profits implies that firms will want to hire many workers when labor is cheap but will refrain from hiring when labor is expensive. The relation between the price of labor and how many workers firms are willing to hire is summarized by the downward-sloping labor demand curve (also illustrated in Figure 1-1). As drawn, the labor demand curve tells us that firms in the engineering industry want to hire 20,000 engineers when the wage is $40,000 but will hire only 10,000 engineers if the wage rises to $50,000. Workers and firms, therefore, enter the labor market with conflicting interests. Many workers are willing to supply their services when the wage is high, but few firms are willing to hire them. Conversely, few workers are willing to supply their services when the wage is low, but many firms are looking for workers. As workers search for jobs and firms search for workers, these conflicting desires are “balanced out” and the labor market reaches an equilibrium. In a free-market economy, equilibrium is attained when supply equals demand. As drawn in Figure 1-1, the equilibrium wage is $40,000 and 20,000 engineers will be hired in the labor market. This wage–employment combination is an equilibrium because it balances out the conflicting desires of workers and firms. Suppose, for example, that the engineering wage were $50,000—above equilibrium. Firms would then want to hire only 10,000 engineers, even though 30,000 engineers are looking for work. The excess number of job applicants would bid down the wage as they compete for the few jobs available. Suppose, instead, that the wage were $30,000—below equilibrium. Because Introduction to Labor Economics 5 engineers are cheap, firms want to hire 30,000 engineers, but only 10,000 engineers are willing to work at that wage. As firms compete for the few available engineers, they bid up the wage. There is one last major player in the labor market, the government. The government can tax the worker’s earnings, subsidize the training of engineers, impose a payroll tax on firms, demand that engineering firms hire two black engineers for each white one hired, enact legislation that makes some labor market transactions illegal (such as paying engineers less than $50,000 annually), and increase the supply of engineers by encouraging their immigration from abroad. All these actions will change the equilibrium that will eventually be attained in the labor market. Government regulations, therefore, help set the ground rules that guide exchanges in the labor market. The Trans-Alaska Oil Pipeline In January 1968, oil was discovered in Prudhoe Bay in remote northern Alaska. The oil reserves were estimated to be greater than 10 billion barrels, making it the largest such discovery in North America.2 There was one problem with the discovery—the oil was located in a remote and frigid area of Alaska, far from where most consumers lived. To solve the daunting problem of transporting the oil to those consumers who wanted to buy it, the oil companies proposed building a 48-inch pipeline across the 789-mile stretch from northern Alaska to the southern (and ice-free) port of Valdez. At Valdez, the oil would be transferred to oil supertankers. These huge ships would then deliver the oil to consumers in the United States and elsewhere. The oil companies joined forces and formed the Alyeska Pipeline Project. The construction project began in the spring of 1974, after the U.S. Congress gave its approval in the wake of the 1973 oil embargo. Construction work continued for three years and the pipeline was completed in 1977. Alyeska employed about 25,000 workers during the summers of 1974 through 1977, and its subcontractors employed an additional 25,000 workers. Once the pipeline was built, Alyeska reduced its pipeline-related employment to a small maintenance crew. Many of the workers employed by Alyeska and its subcontractors were engineers who had built pipelines across the world. Very few of these engineers were resident Alaskans. The remainder of the Alyeska workforce consisted of low-skill labor such as truck drivers and excavators. Many of these low-skill workers were resident Alaskans. The theoretical framework summarized by the supply and demand curves can help us understand the shifts in the labor market that should have occurred in Alaska as a result of the Trans-Alaska Pipeline System. As Figure 1-2 shows, the Alaskan labor market was initially in an equilibrium represented by the intersection of the demand curve D0 and the supply curve S0. The labor demand curve tells us how many workers would be hired in the Alaskan labor market at a particular wage, and the labor supply curve tells us how many workers are willing to supply their services to the Alaskan labor market at a particular wage. A total of E0 Alaskans were employed at a wage of w0 in the initial equilibrium. 2 This discussion is based on the work of William J. Carrington, “The Alaskan Labor Market during the Pipeline Era,” Journal of Political Economy 104 (February 1996): 186–218. 6 Chapter 1 FIGURE 1-2 The Alaskan Labor Market and the Construction of the Oil Pipeline The construction of the oil pipeline shifted the labor demand curve in Alaska from D0 to D1, resulting in higher wages and employment. Once the pipeline was completed, the demand curve reverted back to its original level and wages and employment fell. Earnings ($) S0 w1 w0 D1 D0 E0 E1 Employment The construction project clearly led to a sizable increase in the demand for labor. Figure 1-2 illustrates this shift by showing the demand curve moving outward from D0 to D1. The outward shift in the demand curve implies that—at any given wage—Alaskan employers were looking for more workers. This theoretical framework immediately implies that the shift in demand moved the Alaskan labor market to a new equilibrium, one represented by the intersection of the new demand curve and the original supply curve. At this new equilibrium, a total of E1 persons were employed at a wage of w1. The theory, therefore, predicts that the pipeline construction project would increase both employment and wages. As soon as the project was completed, however, and the temporary need for construction workers disappeared, the demand curve would have shifted back to its original position at D0. In the end, the wage would have gone back down to w0 and E0 workers would be employed. In short, the pipeline construction project should have led to a temporary increase in both wages and employment during the construction period. Figure 1-3 illustrates what actually happened to employment and earnings in Alaska between 1968 and 1983. Because Alaska’s population grew steadily for some decades, Alaskan employment also rose steadily even before the oil discovery in Prudhoe Bay. The data clearly show, however, that employment “spiked” in 1975, 1976, and 1977 and then went back to its long-run growth trend in 1977. The earnings of Alaskan workers also rose substantially during the relevant period. After adjusting for inflation, the monthly earnings of Alaskan workers rose from an average of $2,648 in the third quarter of 1973 to $4,140 in the third quarter of 1976, an increase of 56 percent. By 1979, the real earnings of Alaskan workers were back to the level observed prior to the beginning of the pipeline construction project. Introduction to Labor Economics FIGURE 1-3 Wages and Employment in the Alaskan Labor Market, 1968–1984 Source: William J. Carrington, “The Alaskan Labor Market during the Pipeline Era,” Journal of Political Economy 104 (February 1996): 199. Employment 7 Monthly Salary ($) 4,500 250,000 230,000 4,000 210,000 190,000 3,500 170,000 3,000 150,000 130,000 2,500 110,000 Wage 90,000 2,000 Employment 70,000 50,000 1968 1,500 1970 1972 1974 1976 1978 1980 1982 1984 It is worth noting that the temporary increase in earnings and employment occurred because the supply curve of labor is upward sloping, so that an outward shift in the demand curve moves the labor market to a point further up on the supply curve. As we noted earlier, an upward-sloping supply curve implies that more workers are willing to work when the wage is higher. It turns out that the increase in labor supply experienced in the Alaskan labor market occurred for two distinct reasons. First, a larger fraction of Alaskans were willing to work when the wage increased. In the summer of 1973, about 39 percent of Alaskans were working. In the summers of 1975 and 1976, about 50 percent of Alaskans were working. Second, the rate of population growth in Alaska accelerated between 1974 and 1976—because persons living in the lower 48 states moved to Alaska to take advantage of the improved economic opportunities offered by the Alaskan labor market (despite the frigid weather conditions there). The increase in the rate of population growth, however, was temporary. Population growth reverted back to its long-run trend soon after the pipeline construction project was completed. 1-3 Why Do We Need a Theory? We have just told a simple story of how the Trans-Alaska Pipeline System affected the labor market outcomes experienced by workers in Alaska—and how each of the actors in our story played a major role. The government approved the pipeline project despite the potential environmental hazards involved; firms that saw income opportunities in building the pipeline increased their demand for labor; and workers responded to the change in demand by increasing the quantity of labor supplied to the Alaskan labor market. We have, in effect, constructed a simple theory or model of the Alaskan labor market. Our model is 8 Chapter 1 characterized by an upward-sloping labor supply curve, a downward-sloping labor demand curve, and the assumption that an equilibrium is eventually attained that resolves the conflicts between workers and firms. As we have just seen, this model predicts that the construction of the oil pipeline would temporarily increase wages and employment in the Alaskan labor market. Moreover, this prediction is testable—that is, the predictions about wages and employment can be compared with what actually happened to wages and employment. It turns out that the supply–demand model passes the test; the data are consistent with the theoretical predictions. Needless to say, the model of the labor market illustrated in Figure 1-2 does not do full justice to the complexities of the Alaskan labor market. It is easy to come up with many factors and variables that our simple model ignored and that could potentially influence the success of our predictions. For instance, it is possible that workers care about more than just the wage when they make labor supply decisions. The opportunity to participate in such a challenging or cutting-edge project as the construction of the Trans-Alaska Pipeline could have attracted engineers at wages lower than those offered by firms engaged in more mundane projects—despite the harsh working conditions in the field. The theoretical prediction that the construction of the pipeline project would increase wages would then be incorrect because the project could have attracted more workers at lower wages. If the factors that we have omitted from our theory play a crucial role in understanding how the Alaskan labor market operates, we might be wrongly predicting that wages and employment would rise. If these factors are only minor details, our model captures the essence of what goes on in the Alaskan labor market and our prediction would be valid. We could try to build a more complex model of the Alaskan labor market, a model that incorporates every single one of these omitted factors. Now that would be a tough job! A completely realistic model would have to describe how millions of workers and firms interact and how these interactions work themselves through the labor market. Even if we knew how to accomplish such a difficult task, this “everything-but-thekitchen-sink” approach would defeat the whole purpose of having a theory. A theory that mirrored the real-world labor market in Alaska down to the most minute detail might indeed be able to explain all the facts, but it would be as complex as reality itself, cumbersome and incoherent, and thus would not at all help us understand how the Alaskan labor market works. There has been a long debate over whether a theory should be judged by the realism of its assumptions or by the extent to which it finally helps us understand and predict the labor market phenomena we are interested in. We obviously have a better shot at predicting labor market outcomes if we use more realistic assumptions. At the same time, however, a theory that mirrors the world too closely is too clumsy and does not isolate what really matters. The “art” of labor economics lies in choosing which details are essential to the story and which details are not. There is a trade-off between realism and simplicity, and good economics hits the mark just right. As we will see throughout this book, the supply–demand framework illustrated in Figure 1-1 often isolates the key factors that motivate the various actors in the labor market. The model provides a useful way of organizing our thoughts about how the labor market works. The model also gives a solid foundation for building more complex and more realistic Introduction to Labor Economics 9 models of the labor market. And, most important, the model works. Its predictions are often consistent with what is observed in the real world. The supply–demand framework predicts that the construction of the Alaska oil pipeline would have temporarily increased employment and wages in the Alaskan labor market. This prediction is an example of positive economics. Positive economics addresses the relatively narrow “What is?” questions, such as, What is the impact of the discovery of oil in Prudhoe Bay, and the subsequent construction of the oil pipeline, on the Alaskan labor market? Positive economics, therefore, addresses questions that can, in principle, be answered with the tools of economics, without interjecting any value judgment as to whether the particular outcome is desirable or harmful. Much of this book is devoted to the analysis of such positive questions as, What is the impact of the minimum wage on unemployment? What is the impact of immigration on the earnings of native-born workers? What is the impact of a tuition assistance program on college enrollment rates? What is the impact of unemployment insurance on the duration of a spell of unemployment? These positive questions, however, beg a number of important issues. In fact, some would say that these positive questions beg the most important issues: Should the oil pipeline have been built? Should there be a minimum wage? Should the government subsidize college tuition? Should the United States accept more immigrants? Should the unemployment insurance system be less generous? These broader questions fall in the realm of normative economics, which addresses much broader “What should be?” questions. By their nature, the answers to these normative questions require value judgments. Because each of us probably has different values, our answers to these normative questions may differ regardless of what the theory or the facts tell us about the economic impact of the oil pipeline, the disemployment effects of the minimum wage, or the impact of immigration on the economic well-being of native workers. Normative questions force us to make value judgments about the type of society we wish to live in. Consider, for instance, the impact of immigration on a particular host country. As we will see in subsequent chapters, the supply–demand framework implies that an increase in the number of immigrants lowers the income of competing workers but raises the income of the firms that hire the immigrants by even more. On net, therefore, the receiving country gains. Moreover, because (in most cases) immigration is a voluntary supply decision, it also makes the immigrants better off. Suppose, in fact, that the evidence for a particular host country was completely consistent with the model’s predictions. In particular, the immigration of 10 million workers improved the well-being of the immigrants (relative to their well-being in the source countries); reduced the income of native workers by, say, $25 billion annually; and increased the incomes of capitalists by $40 billion. Let’s now ask a normative question: Should the host country admit 10 million more immigrants? This normative question cannot be answered solely on the basis of the theory or the facts. Even though total income in the host country has increased by $15 billion, there also has been a redistribution of wealth. Some persons are worse off and others are better off. To answer the question of whether the country should continue to admit immigrants, one has to decide whose economic welfare the country should care most about: that of immigrants, who are made better off by immigration; that of native workers, who are made worse off; 10 Chapter 1 or that of the capitalists who own the firms, who are made better off. One might even bring into the discussion the well-being of the people left behind in the source countries, who are clearly affected by the emigration of their compatriots. It is clear that any policy discussion of this issue requires clearly stated assumptions about what constitutes the “national interest,” about who matters more. In the end, therefore, normative judgments about the costs and benefits of immigration depend on our values and ideology. Many economists often take a “fall-back” position when these types of problems are encountered. Because the immigration of 10 million workers increases the total income in the host country by $15 billion, it is possible to redistribute income in the postimmigration economy so that every person in that country is made better off. A policy that can potentially improve the well-being of everyone in the economy is said to be “efficient”; it increases the size of the economic pie available to the country. The problem, however, is that this type of redistribution seldom occurs in the “real world”; the winners typically remain winners and the losers remain losers. Our answer to a normative question, therefore, will force each of us to confront the trade-off that we are willing to make between efficiency and distributional issues. In other words, normative questions force us to compare the value that we attach to an increase in the size of the economic pie with the value that we attach to a change in how the pie is split. As a second example, we will see that the supply–demand framework predicts that unionization transfers wealth from firms to workers, but that unionization also shrinks the size of the economic pie. Suppose that the facts unambiguously support these theoretical implications: unions increase the total income of workers by, say, $40 billion, but the country as a whole is poorer by $20 billion. Let’s now ask a normative question: Should the government pursue policies that discourage workers from forming labor unions? Again, our answer to this normative question depends on how we contrast the gains accruing to the unionized workers with the losses accruing to the employers who must pay higher wages and to the consumers who must pay higher prices for unionproduced goods. The lesson from this discussion should be clear. As long as there are winners and losers— and most government policies inevitably leave winners and losers in their wake—neither the theoretical implications of economic models nor the facts are sufficient to answer the normative question of whether a particular policy is desirable. Throughout this book, therefore, we will find that economic analysis is very useful for framing and answering positive questions but is much less useful for addressing normative questions. Despite the fact that economists cannot answer what many would consider to be the “big questions,” there is an important sense in which framing and answering positive questions is crucial for any policy discussion. Positive economics tells us how particular government policies affect the well-being of different segments of society. Who are the winners, and how much do they gain? Who are the losers, and how much do they lose? The adoption of a particular policy requires that these gains and losses be compared and that some choice be made as to who matters more. In the end, any informed policy discussion requires that we be fully aware of the price that has to be paid when making particular choices. The normative conclusion that one might reach may well be affected by the magnitude of the costs and benefits associated with the particular policy. For example, Introduction to Labor Economics 11 the distributional impact of immigration (that is, redistributing income from workers to firms) could easily dominate the normative discussion if immigration generated only a small increase in the size of the economic pie. The distributional impact, however, would be less relevant if it was clear that the size of the economic pie was greatly enlarged by immigration. Summary • Labor economics studies how labor markets work. Important topics addressed by labor economics include the determination of the income distribution, the economic impact of unions, the allocation of a worker’s time to the labor market, the hiring and firing decisions of firms, labor market discrimination, the determinants of unemployment, and the worker’s decision to invest in human capital. • Models in labor economics typically contain three actors: workers, firms, and the government. It is typically assumed that workers maximize their well-being and that firms maximize profits. Governments influence the decisions of workers and firms by imposing taxes, granting subsidies, and regulating the “rules of the game” in the labor market. • A good theory of the labor market should have realistic assumptions, should not be clumsy or overly complex, and should provide empirical implications that can be tested with real-world data. • The tools of economics are helpful for answering positive questions. The information thus generated may help in making policy decisions. The answer to a normative question, however, typically requires that we impose a value judgment on the desirability of particular economic outcomes. 1. What is labor economics? Which types of questions do labor economists analyze? Review 2. Who are the key actors in the labor market? What motives do economists typically Questions assign to workers and firms? 3. Why do we need a theory to understand real-world labor market problems? 4. What is the difference between positive and normative economics? Why are positive questions easier to answer than normative questions? Key Concepts derived demand, 4 equilibrium, 4 labor demand curve, 4 Web Links A number of websites publish data and research articles that are very valuable to labor economists. labor economics, 1 labor supply curve, 3 model, 7 normative economics, 9 positive economics, 9 The Bureau of Labor Statistics (BLS) is the government agency responsible for calculating the monthly unemployment rate as well as the Consumer Price Index. Their website 12 Chapter 1 contains a lot of information on many aspects of the U.S. labor market, as well as comparable international statistics: http://stats.bls.gov The Bureau of Census reports detailed demographic and labor market information: www.census.gov The Statistical Abstract of the United States is an essential book that is available online. It is published annually and contains detailed information on many aspects of the U.S. economy: www.census.gov/prod/www/statistical_abstract.html The Organization for Economic Cooperation and Development (OECD) reports statistics on labor market conditions in many advanced economies: www.oecd.org The National Bureau of Economic Research (NBER) publishes a working paper series that represents the frontier of empirical research in economics. Their website also contains a number of widely used data sets. The working papers and data can be accessed and downloaded by students and faculty at many universities: www.nber.org IZA is a Bonn-based research institute that conducts labor research. Their discussion paper series provides up-to-date research on labor issues in many countries: www.iza.org Appendix An Introduction to Regression Analysis Labor economics is an empirical science. It makes extensive use of econometrics, the application of statistical techniques to study relationships in economic data. For example, we will be addressing such questions as 1. Do higher levels of unemployment benefits lead to longer spells of unemployment? 2. Do higher levels of welfare benefits reduce work incentives? 3. Does going to school for one more year increase a worker’s earnings? The answers to these three questions ultimately depend on a correlation between pairs of variables: the level of unemployment compensation and the duration of unemployment spells; the level of welfare benefits and the labor supply; and educational attainment and wages. We also will want to know not only the sign of the correlation, but the size as well. In other words, by how many weeks does a $50 increase in unemployment compensation lengthen the duration of unemployment spells? By how many hours does an increase of $200 per month in welfare benefits reduce the labor supply of workers? And by how much our earnings increase if we get a college education? Although this book does not use econometric analysis in much of the discussion, the student can better appreciate both the usefulness and the limits of empirical research by knowing how labor economists manipulate the available data to answer the questions we are interested in. The main statistical technique used by labor economists is regression analysis. Introduction to Labor Economics 13 An Example It is well known that there are sizable differences in wages across occupations. We are interested in determining why some occupations pay more than others. One obvious factor that determines the average wage in an occupation is the level of education of workers in that occupation. It is common in labor economics to conduct empirical studies of earnings by looking at the logarithm of earnings, rather than the actual level of earnings. There are sound theoretical and empirical reasons for this practice, one of which will be described shortly. Suppose there is a linear equation relating the average log wage in an occupation (log w) to the mean years of schooling of workers in that occupation ( s). We write this line as log w = α + βs (1-1) The variable on the left-hand side—the average log wage in the occupation—is called the dependent variable. The variable on the right-hand side—average years of schooling in the occupation—is called the independent variable. The main objective of regression analysis is to obtain numerical estimates of the coefficients α and β by using actual data on the mean log wage and mean schooling in each occupation. It is useful, therefore, to spend some time interpreting these regression coefficients. Equation (1-1) traces out a line, with intercept α and slope β; this line is drawn in Figure 1-4. As drawn, the regression line makes the sensible assumption that the slope β is positive, so wages are higher in occupations where the typical worker has more schooling. FIGURE 1-4 The Regression Line The regression line gives the relationship between the average log wage rate and the average years of schooling of workers across occupations. The slope of the regression line gives the change in the log wage resulting from a one-year change in years of schooling. The intercept gives the log wage for an occupation where workers have zero years of schooling. Log Wage Change in Log Wage Slope = β α Years of Schooling Change in Schooling 14 Chapter 1 The intercept α gives the log wage that would be observed in an occupation where workers have zero years of schooling. Elementary algebra teaches us that the slope of a line is given by the change in the vertical axis divided by the corresponding change in the horizontal axis or Change in log wage β = ________________________ Change in years of schooling (1-2) Put differently, the slope β gives the change in the log wage associated with a one-year increase in average schooling. It is a mathematical fact that a small change in the log wage approximates the percent change in the wage. For example, if the difference in the mean log wage between two occupations is 0.051, we can interpret this statistic as indicating that there is approximately a 5.1 percent wage difference between the two occupations. This property is one of the reasons why labor economists typically conduct studies of salaries using the logarithm of the wage; they can then interpret changes in this quantity as a percent change in the wage. This mathematical property of logarithms implies that the coefficient β can be interpreted as giving the percent change in earnings resulting from a one-year increase in schooling. To estimate the parameters α and β, we first need to obtain data on the average log wage and average years of schooling by occupation. These data can be easily calculated using the Annual Social and Economic Supplement of the Current Population Surveys. These data, collected in March of every year by the Bureau of Labor Statistics, contain a lot of information about employment conditions and salaries for tens of thousands of workers. One can use the data to compute the average log hourly wage and the average years of schooling for men working in each of 45 different occupations. The resulting data are reported in Table 1-1. To give an example, the typical man employed as an engineer had a log wage of 3.37 and 15.8 years of schooling. In contrast, the typical man employed as a construction laborer had a log wage of 2.44 and 10.5 years of schooling. The plot of the data presented in Figure 1-5 is called a scatter diagram and describes the relation found between the average log wage and the average years of schooling in the real world. The relation between the two variables does not look anything like the regression line that we hypothesized. Instead, it is a scatter of points. Note, however, that the points are not randomly scattered on the page, but instead have a noticeable upward-sloping drift. The raw data, therefore, suggest a positive correlation between the log wage and years of schooling, but nothing as simple as an upward-sloping line. We have to recognize, however, that education is not the only factor that determines the average wage in an occupation. There is probably a great deal of error when workers report their salary to the Bureau of Labor Statistics. This measurement error disperses the points on a scatter diagram away from the line that we believe represents the “true” data. There also might be other factors that affect average earnings in any given occupation, such as the average age of the workers or perhaps a variable indicating the “female-ness” of the occupation. After all, it often is argued that jobs that are predominantly done by men (for example, welders) tend to pay more than jobs that are predominantly done by women (for example, kindergarten teachers). All of these extraneous factors would again disperse our data points away from the line. Introduction to Labor Economics 15 TABLE 1-1 Characteristics of Occupations, 2001 Source: Annual Demographic Files of the Current Population Survey, 2002. Occupation Administrators and officials, public administration Other executives, administrators, and managers Management-related occupations Engineers Mathematical and computer scientists Natural scientists Health diagnosing occupations Health assessment and treating occupations Teachers, college and university Teachers, except college and university Lawyers and judges Other professional specialty occupations Health technologists and technicians Engineering and science technicians Technicians, except health, engineering, and science Supervisors and proprietors, sales occupations Sales representatives, finance and business services Sales representatives, commodities, except retail Sales workers, retail and personal services Sales-related occupations Supervisors, administrative support Computer equipment operators Secretaries, stenographers, and typists Financial records, processing occupations Mail and message distributing Other administrative support occupations, including clerical Private household service occupations Protective service occupations Food service occupations Health service occupations Cleaning and building service occupations Personal service occupations Mechanics and repairers Construction trades Other precision production occupations Machine operators and tenders, except precision Fabricators, assemblers, inspectors, and samplers Motor vehicle operators Other transportation occupations and material moving Construction laborer Freight, stock, and material handlers Other handlers, equipment cleaners, and laborers Farm operators and managers Farm workers and related occupations Forestry and fishing occupations Mean Log Hourly Wage of Male Workers Mean Years of Schooling for Male Workers Female Share (%) 3.24 3.29 3.16 3.37 3.36 3.22 3.91 3.23 3.17 2.92 3.72 2.90 2.76 2.97 3.30 2.96 3.39 3.14 2.61 2.93 2.94 2.91 2.75 2.67 2.87 2.66 2.46 2.80 2.23 2.38 2.37 2.55 2.81 2.74 2.82 2.62 2.65 2.59 2.68 2.44 2.44 2.42 2.52 2.29 2.70 15.7 14.9 15.4 15.8 15.6 17.4 19.8 16.2 18.8 16.5 19.7 15.9 14.2 13.8 15.4 13.9 15.1 14.4 13.4 14.8 13.8 13.8 13.8 14.2 13.2 13.4 10.6 13.6 11.4 13.2 11.2 13.4 12.6 11.9 12.3 11.8 12.0 12.1 11.8 10.5 12.0 11.3 12.9 9.9 12.0 52.4 42.0 59.4 10.7 32.2 34.2 31.2 86.2 44.7 75.8 29.3 54.0 83.1 26.0 48.5 37.6 44.7 25.4 64.0 72.4 61.2 57.1 98.0 92.9 41.9 79.2 96.0 18.7 60.0 89.1 48.2 80.4 5.2 2.4 22.5 35.2 36.2 12.7 6.3 3.9 30.4 28.0 20.5 18.5 3.7 16 Chapter 1 FIGURE 1-5 The Scatter Diagram Relating Wages and Schooling by Occupation, 2001 4 Log Wage 3.5 3 2.5 2 8 10 12 14 16 18 20 Years of Schooling The objective of regression analysis is to find the best line that goes through the scatter diagram. Figure 1-6 redraws our scatter diagram and inserts a few of the many lines that we could draw through the scatter. Line A does not represent the general trend very well; after all, the raw data suggest a positive correlation between wages and education, yet line A has a negative slope. Both lines B and C are upward sloping, but they are both a bit “off”; line B lies above all of the points in the scatter diagram and line C is too far to the right. The regression line is the line that best summarizes the data.3 The formula that calculates the regression line is included in every statistics and spreadsheet software program. If we apply the formula to the data in our example, we obtain the regression line log w = 0.869 + 0.143s (1-3) This estimated regression line is superimposed on the scatter diagram in Figure 1-7. We interpret the regression line reported in equation (1-3) as follows. The estimated slope is positive, indicating that the average log wage is indeed higher in occupations where workers are more educated. The 0.143 slope implies that each one-year increase in the mean schooling of workers in an occupation raises the wage by approximately 14.3 percent. 3 More precisely, the regression line is the line that minimizes the sum of the square of the vertical differences between every point in the scatter diagram and the corresponding point on the line. As a result, this method of estimating the regression line is called least squares. Introduction to Labor Economics 17 FIGURE 1-6 Choosing among Lines Summarizing the Trend in the Data There are many lines that can be drawn through the scatter diagram. Lines A, B, and C provide three such examples. None of these lines “fit” the trend in the scatter diagram very well. 4 B Log Wage 3.5 A 3 C 2.5 2 8 10 12 14 16 18 20 Years of Schooling The intercept indicates that the log wage would be 0.869 in an occupation where the average worker had zero years of schooling. We have to be very careful when we use this result. After all, as the raw data reported in Table 1-1 show, no occupation has a workforce with zero years of schooling. In fact, the smallest value of s is 9.9 years. The intercept is obtained by extrapolating the regression line to the left until it hits the vertical axis. In other words, we are using the regression line to make an out-of-sample prediction. It is easy to get absurd results when we do this type of extrapolation: After all, what does it mean to say that the typical person in an occupation has no schooling whatsoever? An equally silly extrapolation takes the regression line and extends it to the right until, say, we wish to predict what would happen if the average worker had 25 years of schooling. Put simply, it is problematic to predict outcomes that lie outside the range of the data. “Margin of Error” and Statistical Significance If we plug the data reported in Table 1-1 into a statistics or spreadsheet program, we will find that the program reports many more numbers than just the intercept and the slope of a regression line. The program also reports what are called standard errors, or a measure of the statistical precision with which the coefficients are estimated. When poll results are reported in the media, it is said, for instance, that 52 percent of the 18 Chapter 1 FIGURE 1-7 The Scatter Diagram and the Regression Line 4 Log Wage 3.5 3 2.5 2 8 10 12 14 16 18 20 Years of Schooling population believes that tomatoes should be bigger and redder, with a margin of error of ±3 percent. We use standard errors to calculate the margin of error of our estimated regression coefficients. In our data, it turns out that the standard error for the intercept α is 0.172 and that the standard error for the slope β is 0.012. The margin of error that is used commonly in econometric work is twice the standard error. The regression thus allows us to conclude that a one-year increase in average schooling increases the log wage by 0.143 ± 0.024 (or twice the standard error of 0.012). In other words, our data suggest that a one-year increase in schooling increases the average wage in an occupation by as little as 11.9 percent or by as much as 16.7 percent. Statistical theory indicates that the true impact of the one-year increase in schooling lies within this range with a 95 percent probability. We have to allow for a margin of error because our data are imperfect. Our data are measured with error, extraneous factors are being omitted, and our data are typically based on a random sample of the population. The regression program will also report a t statistic for each regression coefficient. The t statistic helps us assess the statistical significance of the estimated coefficients. The t statistic is defined as Absolute value of regression coefficient t statistic = _________________________________ Standard error of regression coefficient (1-4) If a regression coefficient has a t statistic above the “magic” number of 2, the regression coefficient is said to be significantly different from zero. In other words, it is very likely Introduction to Labor Economics 19 that the true value of the coefficient is not zero, so there is some correlation between the two variables that we are interested in. If a t statistic is below 2, the coefficient is said to be insignificantly different from zero, so we cannot conclude that there is a correlation between the two variables of interest. Note that the t statistic associated with our estimated slope is 11.9 (or 0.143 ÷ 0.012), which is certainly above 2. Our estimate of the slope is significantly different from zero. Therefore, it is extremely likely that there is indeed a positive correlation between the average log wage in an occupation and the average schooling of workers. Finally, the statistical software program will typically report a number called the R-squared. This statistic gives the fraction of the dispersion in the dependent variable that is “explained” by the dispersion in the independent variable. The R-squared of the regression reported in equation (1-3) is 0.762. In other words, 76.2 percent of the variation in the mean log wage across occupations can be attributed to differences in educational attainment across the occupations. Put differently, our very simple regression model seems to do a very good job at explaining why engineers earn more than construction laborers—it is largely because one group of workers has a lot more education than the other. Multiple Regression Up to this point, we have focused on a regression model that contains only one independent variable, mean years of schooling. As noted above, the average log wage of men in an occupation will probably depend on many other factors. The simple correlation between wages and schooling implied by the regression model in equation (1-3) could be confounding the effect of some of these other variables. To isolate the relationship between the log wage and schooling (and avoid what is called omitted variable bias), it is important to control for differences in other characteristics that also might generate wage differentials across occupations. To provide a concrete example, suppose we believe that occupations that are predominantly held by men tend to pay more—for given schooling—than occupations that are predominantly held by women. We can then write an expanded regression model as log w = α + βs + γp (1-5) where the variable p gives the percent of workers in an occupation that are women. As before, log w and s give the log wage and mean years of schooling of men working in that occupation. We now wish to interpret the coefficients in this multiple regression model—a regression that contains more than one independent variable. Each coefficient in the multiple regression measures the impact of a particular variable on the log wage, other things being equal. For instance, the coefficient β gives the change in the log wage resulting from a one-year increase in mean schooling, holding constant the relative number of women in the occupation. Similarly, the coefficient γ gives the change in the log wage resulting from a one-percentage-point increase in the share of female workers, holding constant the average schooling of the occupation. Finally, the intercept α gives the log wage in a fictional occupation that employs only men and where the typical worker has zero years of schooling. The last column in Table 1-1 reports the values of the female share p for the various occupations in our sample. It is evident that the representation of women varies significantly across occupations: 75.8 percent of teachers below the university level are women, 20 Chapter 1 as compared to only 5.2 percent of mechanics and repairers. Because we now have two independent variables, our scatter diagram is three dimensional. The regression “line,” however, is now the plane that best fits the data in this three-dimensional space. If we plug these data into a computer program to estimate the regression model in equation (1-5), the estimated regression line is given by log w = 0.924 + 0.150s - 0.003p (0.154) (0.011) (0.001) R-squared = 0.816 (1-6) where the standard error of each of the coefficients is reported in parentheses below the coefficient. Note that a one-year increase in the occupation’s mean schooling raises weekly earnings by approximately 15.0 percent. In other words, if we compare two occupations that have the same female share but differ in years of schooling by one year, workers in the high-skill occupation earn 15 percent more than workers in the low-skill occupation. Equally important, we find that the percent female in the occupation has a statistically significant negative impact on the log wage. In other words, men who work in predominantly female occupations earn less than men who work in predominantly male occupations— even if both occupations have the same mean schooling. The regression coefficient, in fact, implies that a 10-percentage-point increase in the female share lowers the average earnings of an occupation by 3.0 percent. Of course, before we make the tempting inference that this empirical finding is proof of a “crowding effect”—the hypothesis that discriminatory behavior crowds women into relatively few occupations and lowers wages in those jobs—we need to realize that there are many other factors that determine occupational earnings. The multiple regression model can, of course, be expanded to incorporate many more independent variables. As we will see throughout this book, labor economists put a lot of effort into defining and estimating regression models that isolate the correlation between the two variables of interest after controlling for all other relevant factors. Regardless of how many independent variables are included in the regression, however, all the regression models are estimated in essentially the same way: The regression line best summarizes the trends in the underlying data. Key Concepts dependent variable, 13 econometrics, 12 independent variable, 13 multiple regression, 19 regression analysis, 12 regression coefficients, 13 regression line, 16 R-squared, 19 scatter diagram, 14 statistical significance, 18 standard errors, 17 t statistic, 18 2 Chapter Labor Supply It’s true hard work never killed anybody, but I figure, why take the chance? —Ronald Reagan Each of us must decide whether to work and, once employed, how many hours to work. At any point in time, the economywide labor supply is given by adding the work choices made by each person in the population. Total labor supply also depends on the fertility decisions made by earlier generations (which determine the size of the current population). The economic and social consequences of these decisions vary dramatically over time. In 1948, 84 percent of American men and 31 percent of American women aged 16 or over worked. By 2012, the proportion of working men had declined to 64 percent, whereas the proportion of working women had risen to 53 percent. Over the same period, the length of the average workweek in a private-sector production job fell from 40 to 34 hours.1 These labor supply trends have surely altered the nature of the American family as well as greatly affected the economy’s productive capacity. This chapter develops the framework that economists use to study labor supply decisions. In this framework, individuals seek to maximize their well-being by consuming goods (such as fancy cars and nice homes) and leisure. Goods have to be purchased in the marketplace. Because most of us are not independently wealthy, we must work in order to earn the cash required to buy the desired goods. The economic trade-off is clear: If we do not work, we can consume a lot of leisure, but we have to do without the goods and services that make life more enjoyable. If we do work, we will be able to afford many of these goods and services, but we must give up some of our valuable leisure time. The model of labor-leisure choice isolates the person’s wage rate and income as the key economic variables that guide the allocation of time between the labor market and leisure activities. In this chapter, we first use the framework to analyze “static” labor supply 1 These statistics were obtained from the U.S. Bureau of Labor Statistics website: www.bls.gov/data/home.htm. 21 22 Chapter 2 decisions, the decisions that affect a person’s labor supply at a point in time. We will also extend the basic model to explore how the timing of leisure activities changes over the life cycle. This economic framework not only helps us understand why women’s work propensities rose and hours of work declined, but also allows us to address a number of questions with important policy and social consequences. For example, do welfare programs reduce incentives to work? Does a cut in the income tax rate increase hours of work? And what factors explain the rapid growth in the number of women who choose to participate in the labor market? 2-1 Measuring the Labor Force On the first Friday of every month, the Bureau of Labor Statistics (BLS) releases its estimate of the unemployment rate for the previous month. The unemployment rate statistic is widely regarded as a measure of the overall health of the U.S. economy. In fact, the media often interpret the minor month-to-month blips in the unemployment rate as a sign of either a precipitous decline in economic activity or a surging recovery. The unemployment rate is tabulated from the responses to a monthly BLS survey called the Current Population Survey (CPS). In this survey, nearly 60,000 households are questioned about their work activities during a particular week of the month (that week is called the reference week). Almost everything we know about the trends in the U.S. labor force comes from tabulations of CPS data. The survey instrument used by the CPS also has influenced the development of surveys in many other countries. In view of the importance of this survey in the calculation of labor force statistics both in the United States and abroad, it is useful to review the various definitions of labor force activities that are routinely used by the BLS to generate its statistics. The CPS classifies all persons aged 16 or older into one of three categories: the employed, the unemployed, and the residual group that is said to be out of the labor force. To be employed, a worker must have been at a job with pay for at least 1 hour or worked at least 15 hours on a nonpaid job (such as the family farm). To be unemployed, a worker must either be on a temporary layoff from a job or have no job but be actively looking for work in the four-week period prior to the reference week. Let E be the number of persons employed and U the number of persons unemployed. A person participates in the labor force if he or she is either employed or unemployed. The size of the labor force (LF) is given by LF = E + U (2-1) Note that the vast majority of employed persons (those who work at a job with pay) are counted as being in the labor force regardless of how many hours they work. The size of the labor force, therefore, does not say anything about the “intensity” of work. The labor force participation rate gives the fraction of the population (P) that is in the labor force and is defined by LF Labor force participation rate = ___ P (2-2) Labor Supply 23 The employment rate (also called the “employment–population ratio”) gives the fraction of the population that is employed, or E Employment rate = __ P (2-3) Finally, the unemployment rate gives the fraction of labor force participants who are unemployed: U Unemployment rate = ___ (2-4) LF The Hidden Unemployed The BLS calculates an unemployment rate based on a subjective measure of what it means to be unemployed. To be considered unemployed, a pers...
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The U.S Labor Market

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THE US LABOR MARKET

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The cases of undocumented workers have increased in the United States over the years.
The changes in the number of the undocumented employees has direct implication on their wages,
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more active enforcement of employers, undocumented workers' wage and employment levels are
highly affected in many ways. Needless to acknowledge that the U.S. has the highest number of
undocumented immigrants in the world and that the majority of these undocumented immigrants
have little skills in the U.S. job markets. The government has enacted policies that guide the
employment structures in the country. However, most employers tend t...


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