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Field of Study, Earnings, and Self-Selection

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  • Lars Kirkebøen
  • Edwin Leuven
  • Magne Mogstad

Abstract

Why do individuals choose different types of post-secondary education, and what are the labor market consequences of those choices? We show that answering these questions is difficult because individuals choose between several unordered alternatives. Even with a valid instrument for every type of education, instrumental variables estimation of the payoffs require information about individuals’ ranking of education types or strong additional assumptions, like constant effects or restrictive preferences. These identification results motivate and guide our empirical analysis of the choice of and payoff to field of study. Our context is Norway’s post-secondary education system where a centralized admission process covers almost all universities and colleges. This process creates credible instruments from discontinuities which effectively randomize applicants near unpredictable admission cutoffs into different fields of study. At the same time, it provides us with strategy-proof measures of individuals’ ranking of fields. Taken together, this allows us to estimate the payoffs to different fields while correcting for selection bias and keeping the next-best alternatives as measured at the time of application fixed. We find that different fields have widely different payoffs, even after accounting for institutional differences and quality of peer groups. For many fields the payoffs rival the college wage premiums, suggesting the choice of field is potentially as important as the decision to enroll in college. The estimated payoffs are consistent with individuals choosing fields in which they have comparative advantage. We also test and reject assumptions of constant effects or restrictive preferences, suggesting that information on next-best alternatives is essential to identify payoffs to field of study.

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  • Lars Kirkebøen & Edwin Leuven & Magne Mogstad, 2014. "Field of Study, Earnings, and Self-Selection," NBER Working Papers 20816, National Bureau of Economic Research, Inc.
  • Handle: RePEc:nbr:nberwo:20816
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    Cited by:

    1. Massimo Anelli, 2016. "The Returns to Elite College Education: A Quasi-Experimental Analysis," CESifo Working Paper Series 6076, CESifo Group Munich.
    2. Di Paolo, Antonio & Tansel, Aysit, 2017. "Analyzing Wage Differentials by Fields of Study: Evidence from Turkey," GLO Discussion Paper Series 91, Global Labor Organization (GLO).
    3. Nordin , Martin & Heckley , Gawain & Gerdtham , Ulf-G, 2017. "Impact of a Tertiary Eligibility Threshold on Tertiary Education and Earnings: A Discontinuity Approach," Working Papers 2017:12, Lund University, Department of Economics.
    4. Thomas Breda & Julien Grenet & Marion Monnet & Clémentine Van Effenterre, 2018. "Can female role models reduce the gender gap in science? Evidence from classroom interventions in French high schools," PSE Working Papers halshs-01713068, HAL.
    5. Yusuki Narita, 2016. "(Non)Randomization: A Theory of Quasi-Experimental Evaluation of School Quality," Cowles Foundation Discussion Papers 2056R, Cowles Foundation for Research in Economics, Yale University, revised Aug 2017.
    6. Patrick Kline & Christopher R. Walters, 2016. "Evaluating Public Programs with Close Substitutes: The Case of HeadStart," The Quarterly Journal of Economics, Oxford University Press, vol. 131(4), pages 1795-1848.
    7. Vishal Kamat, 2017. "Identification with Latent Choice Sets: The Case of the Head Start Impact Study," Papers 1711.02048, arXiv.org.
    8. Ana Maria Montoya & Carlos Noton & Alex Solis, 2017. "Returns to Higher Education: Vocational Education vs College," Documentos de Trabajo 334, Centro de Economía Aplicada, Universidad de Chile.
    9. Joshua Goodman, 2017. "The Labor of Division: Returns to Compulsory High School Math Coursework," NBER Working Papers 23063, National Bureau of Economic Research, Inc.
    10. Fricke, Hans & Grogger, Jeff & Steinmayr, Andreas, 2015. "Does Exposure to Economics Bring New Majors to the Field? Evidence from a Natural Experiment," IZA Discussion Papers 9003, Institute for the Study of Labor (IZA).
    11. Adriana D. Kugler & Catherine H. Tinsley & Olga Ukhaneva, 2017. "Choice of Majors: Are Women Really Different from Men?," NBER Working Papers 23735, National Bureau of Economic Research, Inc.
    12. Frank Neffke, 2017. "Coworker Complementarity," SPRU Working Paper Series 2017-05, SPRU - Science and Technology Policy Research, University of Sussex.
    13. Hastings, Justine S. & Neilson, Christopher A. & Ramirez, Anely & Zimmerman, Seth D., 2016. "(Un)informed college and major choice: Evidence from linked survey and administrative data," Economics of Education Review, Elsevier, vol. 51(C), pages 136-151.
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    16. Yusuki Narita, 2016. "(Non)Randomization: A Theory of Quasi-Experimental Evaluation of School Quality," Cowles Foundation Discussion Papers 2056, Cowles Foundation for Research in Economics, Yale University.
    17. Christina Felfe & Larissa Zierow, 2017. "From Dawn till Dusk: Implications of Full-Day Care for Children's Development," CESifo Working Paper Series 6490, CESifo Group Munich.
    18. 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.
    19. Atila Abdulkadiroglu & Joshua D. Angrist & Yusuke Narita & Parag A. Pathak, 2017. "Impact Evaluation in Matching Markets with General Tie-Breaking," NBER Working Papers 24172, National Bureau of Economic Research, Inc.
    20. Peter Arcidiacono & Michael Lovenheim, 2016. "Affirmative Action and the Quality-Fit Trade-Off," Journal of Economic Literature, American Economic Association, vol. 54(1), pages 3-51, March.
    21. Christopher R. Walters, 2014. "The Demand for Effective Charter Schools," NBER Working Papers 20640, National Bureau of Economic Research, Inc.
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    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
    • J24 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Human Capital; Skills; Occupational Choice; Labor Productivity
    • J31 - Labor and Demographic Economics - - Wages, Compensation, and Labor Costs - - - Wage Level and Structure; Wage Differentials

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