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

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  • Peter Arcidiacono
  • V. Joseph Hotz
  • Arnaud Maurel
  • Teresa Romano

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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  • Peter Arcidiacono & V. Joseph Hotz & Arnaud Maurel & Teresa Romano, 2014. "Recovering Ex Ante Returns and Preferences for Occupations using Subjective Expectations Data," NBER Working Papers 20626, National Bureau of Economic Research, Inc.
  • Handle: RePEc:nbr:nberwo:20626
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    3. Hoffman, Mitchell & Burks, Stephen V., 2017. "Worker Overconfidence: Field Evidence and Implications for Employee Turnover and Returns from Training," IZA Discussion Papers 10794, Institute of Labor Economics (IZA).
    4. Vaishali Zambre, 2018. "The Gender Gap in Wage Expectations: Do Young Women Trade off Higher Wages for Lower Wage Risk?," Discussion Papers of DIW Berlin 1742, DIW Berlin, German Institute for Economic Research.
    5. Osikominu, Aderonke & Pfeifer, Gregor, 2018. "Perceived Wages and the Gender Gap in STEM Fields," IZA Discussion Papers 11321, Institute of Labor Economics (IZA).
    6. Andreas I. Mueller & Johannes Spinnewijn & Giorgio Topa, 2021. "Job Seekers' Perceptions and Employment Prospects: Heterogeneity, Duration Dependence, and Bias," American Economic Review, American Economic Association, vol. 111(1), pages 324-363, January.
    7. Xavier D'Haultfoeuille & Christophe Gaillac & Arnaud Maurel, 2018. "Rationalizing Rational Expectations? Tests and Deviations," NBER Working Papers 25274, National Bureau of Economic Research, Inc.
    8. Johannes S. Kunz & Kevin E. Staub, 2016. "Subjective completion beliefs and the demand for post-secondary education," Economics of Education Working Paper Series 0120, University of Zurich, Department of Business Administration (IBW).
    9. Orazio Attanasio & Teodora Boneva & Christopher Rauh, 2022. "Parental Beliefs about Returns to Different Types of Investments in School Children," Journal of Human Resources, University of Wisconsin Press, vol. 57(6), pages 1789-1825.
    10. Choi, Darwin & Lou, Dong & Mukherjee, Abhiroop, 2018. "The effect of superstar firms on college major choice," LSE Research Online Documents on Economics 118941, London School of Economics and Political Science, LSE Library.
    11. Justine Hastings & Christopher A. Neilson & Seth D. Zimmerman, 2015. "The Effects of Earnings Disclosure on College Enrollment Decisions," NBER Working Papers 21300, National Bureau of Economic Research, Inc.
    12. Joseph G. Altonji & Peter Arcidiacono & Arnaud Maurel, 2015. "The Analysis of Field Choice in College and Graduate School: Determinants and Wage Effects," NBER Working Papers 21655, National Bureau of Economic Research, Inc.
    13. Patnaik, Arpita & Venator, Joanna & Wiswall, Matthew & Zafar, Basit, 2022. "The role of heterogeneous risk preferences, discount rates, and earnings expectations in college major choice," Journal of Econometrics, Elsevier, vol. 231(1), pages 98-122.
    14. Xavier D'Haultfoeuille & Christophe Gaillac & Arnaud Maurel, 2021. "Rationalizing rational expectations: Characterizations and tests," Quantitative Economics, Econometric Society, vol. 12(3), pages 817-842, July.
    15. Koşar, Gizem & Ransom, Tyler & van der Klaauw, Wilbert, 2022. "Understanding migration aversion using elicited counterfactual choice probabilities," Journal of Econometrics, Elsevier, vol. 231(1), pages 123-147.
    16. Schweri, Juerg & Hartog, Joop, 2017. "Do wage expectations predict college enrollment? Evidence from healthcare," Journal of Economic Behavior & Organization, Elsevier, vol. 141(C), pages 135-150.
    17. Lars Kirkebøen & Edwin Leuven & Magne Mogstad, 2014. "Field of Study, Earnings, and Self-Selection," NBER Working Papers 20816, National Bureau of Economic Research, Inc.
    18. Matthew Wiswall & Basit Zafar, 2018. "Preference for the Workplace, Investment in Human Capital, and Gender," The Quarterly Journal of Economics, Oxford University Press, vol. 133(1), pages 457-507.
    19. Arpita Patnaik & Matthew J. Wiswall & Basit Zafar, 2020. "College Majors," NBER Working Papers 27645, National Bureau of Economic Research, Inc.
    20. Teodora Boneva & Christopher Rauh, 2017. "Socio-Economic Gaps in University Enrollment: The Role of Perceived Pecuniary and Non-Pecuniary Returns," CESifo Working Paper Series 6756, CESifo.
    21. Kelly Foley & Fane Groes, 2021. "Admissions Constraints and the Decision to Delay University," Scandinavian Journal of Economics, Wiley Blackwell, vol. 123(2), pages 478-507, April.
    22. Matthew Wiswall & Basit Zafar, 2016. "Human Capital Investments and Expectations about Career and Family," NBER Working Papers 22543, National Bureau of Economic Research, Inc.

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    More about this item

    JEL classification:

    • C31 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models; Quantile Regressions; Social Interaction Models
    • I23 - Health, Education, and Welfare - - Education - - - Higher Education; Research Institutions
    • J24 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Human Capital; Skills; Occupational Choice; Labor Productivity

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