4.6 Article

Field of Study, Earnings, and Self-Selection*

Journal

QUARTERLY JOURNAL OF ECONOMICS
Volume 131, Issue 3, Pages 1057-1111

Publisher

OXFORD UNIV PRESS INC
DOI: 10.1093/qje/qjw019

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Funding

  1. Norwegian Research Council's Programme for Research and Innovation in the Education Sector (FINNUT) [237840]

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This article examines the labor market payoffs to different types of postsecondary education, including field and institution of study. Instrumental variables (IV) estimation of the payoff to choosing one type of education compared to another is made particularly challenging by individuals choosing between several types of education. Not only does identification require one instrument per alternative, but it is also necessary to deal with the issue that individuals who choose the same education may have different next-best alternatives. We address these difficulties using rich administrative data for Norway's postsecondary education system. A centralized admission process creates credible instruments from discontinuities that effectively randomize applicants near unpredictable admission cutoffs into different institutions and fields of study. The admission process also provides information on preferred and next-best alternatives from strategy-proof measures of individuals' ranking of institutions and fields. The results from our IV approach may be summarized with three broad conclusions. First, different fields of study have substantially different labor market payoffs, even after accounting for institution and peer quality. Second, the effect on earnings from attending a more selective institution tends to be relatively small compared to payoffs to field of study. Third, the estimated payoffs to field of study are consistent with individuals choosing fields in which they have a comparative advantage. Comparing our estimates to those obtained from other approaches highlights the importance of using instruments to correct for selection bias and information on individuals' ranking of institutions and fields to measure their preferred and next-best alternatives.

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