Recovering Ex Ante Returns and Preferences for Occupations Using Subjective Expectations Data

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2014-10-01

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Abstract

We show that data on subjective expectations, especially on outcomes from counterfactual choices and choice probabilities, are a powerful tool in recovering ex ante treatment effects as well as preferences for different treatments. In this paper we focus on the choice of occupation, and use elicited beliefs from a sample of male undergraduates at Duke University. By asking individuals about potential earnings associated with counterfactual choices of college majors and occupations, we can recover the distribution of the ex ante monetary returns to particular occupations, and how these returns vary across majors. We then propose a model of occupational choice which allows us to link subjective data on earnings and choice probabilities with the non-pecuniary preferences for each occupation. We find large differences in expected earnings across occupations, and substantial heterogeneity across individuals in the corresponding ex ante returns. However, while sorting across occupations is partly driven by the ex ante monetary returns, non-monetary factors play a key role in this decision. Finally, our results point to the existence of sizable complementarities between college major and occupations, both in terms of earnings and non-monetary benefits.

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Scholars@Duke

Hotz

V. Joseph Hotz

Arts and Sciences Distinguished Professor Emeritus of Economics

Professor Hotz specializes in the subjects of applied econometrics, labor economics, economic demography, and economics of the family. His studies have investigated the impacts of social programs, such as welfare-to-work training; the relationship between childbearing patterns and labor force participation of U.S. women; the effects of teenage pregnancy; the child care market; the Earned Income Tax Credit; and other such subjects. He began conducting his studies in 1977, and has since published his work extensively in books and leading academic journals. Many of his projects have been funded by grants awarded by the National Institute of Health and the National Science Foundation. He is currently completing a project with Duncan Thomas on, “Preference and Economic Decision-Making” under a grant from the National Institute of Child Health and Human Development. His recent works also include, “Tax Policy and Low-Wage Labor Markets: New Work on Employment, Effectiveness and Administration” with John Karl Scholz and Charles Mullin; and “Designing New Models to Explain Family Change and Variation” with S. Philip Morgan. Along with his duties as an independent researcher, Professor Hotz has also held positions as a research associate of the National Bureau of Economic Research, the National Poverty Center, the Institute for the Study of Labor, and the Institute for Research on Poverty. He is presently a member of the Committee on National Statistics for the National Academy of Sciences’ Research Council.

Maurel

Arnaud Maurel

Associate Professor of Economics

Professor Maurel’s research focuses on labor economics/education and microeconometrics. Most of his non-methodological work lies at the intersection between the economics of education and labor economics, with a focus on post-secondary education demand and occupational choices. On the methodological side, his research is concerned with the identification and estimation of selection and treatment effect models, as well as models of occupational choice and job search, and on data combination issues applied in particular to subjective expectations data. His most recent work has been published in such journals as the Journal of Political Economy, Journal of Labor Economics, Quantitative Economics, Journal of Econometrics and the Review of Economics and Statistics. He has received several research awards, notably the 2015 Dennis J. Aigner Award for the most significant contribution in empirical econometrics published by the Journal of Econometrics in 2013-2014. He is also a Research Associate at the NBER (Labor Studies) and IZA, a Co-Editor of Annals of Economics and Statistics, and Associate Editor at Quantitative Economics and the Journal of Business and Economic Statistics. 


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