Prelims

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50th Celebratory Volume

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Research in Labor Economics

Series Editor: Solomon W. Polachek

IZA Co-Editor: Konstantinos Tatsiramos

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Research in Labor Economics Volume 50

50th Celebratory Volume

Edited by

Solomon W. Polachek

State University of New York at Binghamton, USA

And

Konstantinos Tatsiramos

University of Luxembourg and Luxembourg Institute of Socio-Economic Research (LISER), Luxembourg

United Kingdom – North America – Japan – India – Malaysia – China

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Emerald Publishing Limited

Howard House, Wagon Lane, Bingley BD16 1WA, UK

First edition 2023

Editorial matter and selection © 2023 Solomon W. Polachek and Konstantinos Tatsiramos.

Published under exclusive licence by Emerald Publishing Limited.

Individual chapters © 2023 by Emerald Publishing Limited.

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British Library Cataloguing in Publication Data

A catalogue record for this book is available from the British Library

ISBN: 978-1-80455-126-4 (Print)

ISBN: 978-1-80455-125-7 (Online)

ISBN: 978-1-80455-127-1 (Epub)

ISSN: 0147-9121 (Series)

List of Contributors

Foreword

Preface

This marks the 50th volume of Research in Labor Economics. The volume contains 10 original articles each written by stellar senior scholars in labor economics. One is a Nobel Laureate. Each article deals with an aspect of worker well-being, a hallmark subject of concern especially to labor economists. Of these, five deal directly with human capital and potential earnings, four with institutional impediments to time allocation including work, and one important article shows how economics-based search and matching theory should be applied elsewhere, particularly in epidemiological modeling with regard to pandemics, such as the recent COVID-19 pandemic.

Search and matching models are fundamental to economics. Based on search's costs and benefits, these models delineate how individuals sort into a variety of activities including marriage, jobs, schools, fields of study, and numerous other pursuits. More broadly, search and matching models explain unemployment and unemployment duration which have important macroeconomic implications. Independent of economists, epidemiologists use matching to model the propagation of disease. Here individuals meet others, but now potentially become infected with illness, rather than obtaining an economic benefit. In the first article, according to Pietro Garibaldi, Espen Moen, and Christopher Pissarides, these latter epidemiological models in many ways have similarities to search and matching models, but are distinctly different mostly because they neglect individual cost and benefit incentives. As an example, rising infection rates make social interactions more expensive inducing individuals to shift away from interpersonal interactions, what we now call social distancing. As a result, meeting probabilities are reduced. Incorporating these costs affect equilibrium disease evolution, and hence appropriate national policies to combat disease spread. As such, there is much epidemiologists can learn from economists.

It is well known that human capital is the backbone of economic success. Countries with a more educated populace are richer and individuals with more schooling earn more. Yet it is difficult to measure the benefits of school because of endogeneity issues related to sorting. If smarter students stay in school longer, for example because they benefit more than the less able, simply computed rates of return are overstated. And, of course, the opposite is true if the more able have higher returns in the labor market than in the classroom. However, other sorting issues arise if individuals vary in their types of ability. In this case heterogeneity in learning can manifest itself both in the levels and types of education a person receives. If so, how individuals sort into fields of study is in part dependent on the distribution of innate attributes including ability. As a result, there are several relevant technical econometric issues that need to be addressed to take account of the resulting endogeneity. In the next article, Joseph Altonji, John Humphries, and Ling Zhong address these issues and estimate returns to advanced postgraduate degrees for men and women. To do this they adopt what they call a “fixed-effects combination of group (FEcg)” estimator that gets at endogeneity related to an individual's choice of graduate study based on ability and preferences. They make four contributions. First, they estimate earnings premia by gender associated with 19 advanced degrees. Second, they decompose these earnings premia into portions based on wages and hours. Third, they compute internal rates of return. Finally, they examine job satisfaction.

Higher wages resulting from human capital acquisition, particularly from advanced postgraduate schooling, is an example of compensating wage differentials, as it reflects recompense for time and money spent investing. But other job attributes including both amenities and unpleasant characteristics can affect wages, as well. To get at these, one can apply hedonic estimation models in a Mincer-type earnings equation. Doing so, paying particular attention to the risk of death or injury on the job, enables one to back out the value of a statistical life (VSL), the value of a statistical injury (VSI), and the value of a statistical life year (VSLY). In the next article, Thomas Kniesner and W. Kip Viscusi describe this process and then survey existing studies. They compare the value of life estimates in the United States to other countries and they compare the value of life estimates between men and women. They also examine other possible applications and show how the approach can be used to evaluate welfare policies. Finally, they apply the approach to evaluate the cost of COVID-19 in the United States and worldwide.

Whereas some wage variation arises because of compensating wage differentials, some variation can also come about because of market imperfections. One such imperfection is discrimination, whereby equally competent and equally productive workers receive disparate wages despite desiring exactly the same job. This is often stated to be the case by race, as (full-time) black men earn approximately 78 cents on the dollar compared to (full-time) white men, and (full-time) females now earn about 83 cents on the dollar compared to (full-time) males. However, how much of these wage differences are due to compensating differences, and how much due to discrimination, is tricky to ascertain. Men and women earn roughly equal wages upon entering the labor force at the beginning of their respective work lives, but wages diverge over the life cycle as men and women move through their careers. In the next article, David Neumark and Giannina Vaccaro note that some view this as prima facie evidence against gender discrimination, otherwise why would men and women be paid equally well when they first get employed. To counter this argument, they point out a fallacy to this assertion. Given that observed earnings net out human capital investments (i.e., observed earnings equal potential earnings minus the cost of on-the-job human capital investments), they argue that women should be paid more than men because women's on average lower lifetime work leads them to obtain less human capital early on. Thus, in the absence of discrimination, women should be earning more than men at career onset. Thus, they claim initial wage parity can still imply discrimination.

Clearly there still remain a number of other ambiguous and unanswered questions regarding gender differences. In the next chapter, Shelly Lundberg argues that much of the gender discrimination literature decomposes gender gaps into “discrimination” and “choice.” However, choice is difficult to define since what many believe to be choice can really result from discrimination, and what many deem to be discrimination may actually be choice from a perspective “that views the default agent as male” if men and women are motivated differently. Further gender is difficult to define especially now that we realize the very many gender identities psychologists and others study. As such, the article argues for more complex modeling.

Whereas inequality between men and women narrowed, and more quickly in the last 40 years, inequality between the rich and poor has risen dramatically, at least in a number of the most developed countries during the same time period. Interestingly, a 2020 UN Report found inequality (based on the Gini coefficient) rising and falling in roughly equal proportions out of 119 countries between 1990 and 2016. But more developed countries constituted the preponderance of countries where earnings inequality rose. Two-thirds of these (26 out of 39) experienced a widening earnings disparity between top and bottom earners. From the mid-1980s until 2011, the Gini coefficient increased in 16 out of the 21 OECD countries for which long time series were available. Why these increases prevail in developed countries is yet an unanswered question. In the next article, Edward P. Lazear, Kathryn Shaw, Grant Hayes, and James Jedras explore why. Predicated on their unique education-specific industry-based index, they argue in favor of skilled-biased technical change probably stemming from the AI revolution by which productivity and wages rose more for the well educated than the less educated.

Technical change is not the only factor that affects labor market outcomes. Governments do so directly via laws explicitly regulating the market. In the next article, Robert Topel deals with potential legislative overreach. Here bureaucrats stretch their agency's regulatory powers beyond government's original intent. Examples cited include the Equal Employment Opportunity Commission's use of criminal background checks in hiring decisions. Part of this may occur because of imprecise statutory language (Congress in the case of the United States). Often governments do not define precisely the social problems in all its detail and complexity. In Topel's words, part of the problem may be that “bureaucrats attracted to work in the agency … have a disproportionate belief in its mission.” Even so, there is at least one other important factor enabling the propagation of fervorous bureaucrats. Topel shows this can come about if “the evaluation of agency recommendations and punishment of the agency for poor performance are in different hands.” One reason is that costs and benefits differ between the two. In any event, overregulation is greatest “when the social problem is least harmful” and “the oversight agency” is weakest.

Laws still matter independent of whether government bureaucrats over- or underregulate. Right to Work (RTW) legislation is one set of laws that potentially have powerful implications for labor. As is well known, RTW states cannot compel workers to join a union and pay dues even if represented under a collective bargaining agreement. Such laws were prevalent in the South, but of late have been passed in such states as Oklahoma, Indiana, Michigan, Wisconsin, West Virginia, and Kentucky. Clearly such legislation diminishes the power of unions, and thus has implications for unionization rates and worker wages. Given their staggered implementation across states and their varied effect across industries, Nicole Fortin, Thomas Lemieux, and Neil Lloyd adopt several identification strategies to measure their effect on unionization and wages in the next article. They find RTW laws lower wages and unionization rates. Further, they find unions increase wages about 35% when using RTW as an instrument in a wage equation.

Regulation isn't the only aspect that affects human behavior. The last two years witnessed one of the biggest unanticipated shocks felt world-wide in over a century. It is now well known that the COVID-19 pandemic dramatically reduced employment. In April 2020, just after the pandemic hit, the United States lost over 20 million jobs. Unemployment soared from 3.5% to 14.7%. Also well known, women were more dramatically affected than men. Their unemployment shot up from 3.6% in January 2020 to 16.1% in April 2020. Less well known is how immigrants, especially undocumented immigrants, fared during the pandemic. In the next article, George Borjas and Hugh Cassidy show a much more precipitous drop in employment for immigrants, but at the same time, a far faster recovery, especially for the undocumented immigrants. Interestingly, Borjas and Cassidy find the type of immigrants' jobs are most responsible for their bigger job losses, as these jobs had O*NET characteristics less inducive to working at home. But even more interestingly, undocumented workers rebounded more quickly than either natives or other immigrants, mostly because they did not qualify for generous pandemic instigated unemployment insurance benefits.

Costs and benefits are affected by world-wide shocks, but personal trauma can do the same, at least at the household level. In the final article, Daniel S. Hamermesh, Michał Myck, and Monika Oczkowska examine the effect of a specific, in some cases expected, and in some cases unexpected, familial shock, namely the death of a husband on a widow's time allocation. Given higher women's life expectancy, widows constitute an important yet understudied demographic group. Though there are slight variations across countries, roughly 50% of women over 70 were widowed compared to about 15% for similarly aged men. Using high-quality time-diary data, the authors analyze time usage for widows in a number of European countries and in the United States. They find newly widowed women spend less time in home production and personal care than married women, but more time sleeping and in other leisure activities. Longer-term widowed women spend even less time in home production but more time watching television.

The success of Research in Labor Economics depends on its authors and the quality of their articles. As this volume attests all authors have stellar reputations and have written significant state of the art articles with important policy implications. For this volume we especially thank Daniel Hamermesh who supported us in the initial stages of its planning. We also congratulate Simon Jäger on becoming the new IZA Director. He is a noteworthy labor economist whom we are eager to work with as we produce future RLE volumes in conjunction with IZA. In this regard, readers who have prepared manuscripts that meet RLE's stringent standards are encouraged to submit them via the IZA website (http://rle.iza.org).

Solomon W. Polachek

Konstantinos Tatsiramos

Volume Editors