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Heterogeneous Returns to Education Over Wage Distribution: Who Profits the Most?

Author

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  • Simone Balestra

    (Center for Education Policy Analysis, Stanford University and Department of Business Administration, University of Zurich)

  • Uschi Backes-Gellner

    (Department of Business Administration, University of Zurich)

Abstract

This study presents evidence of heterogeneous returns to education over the wage distribution. The authors use instrumental variable quantile regression and data from the Swiss Labor Force Survey to identify the causal link between education and wages at different quantiles of the conditional distribution of wages. The results provide evidence that there is no unique causal effect of schooling and that for each individual the effect may deviate from those extensively documented by ordinary least squares or two-stage least squares. In particular, while ordinary quantile regression estimates increasing returns in the quantile index, once the endogeneity of schooling is taken into account the authors instead observe higher returns at lower quantiles of the wage distribution. Interpreting the quantile index as a measure of unobserved ability, the results suggest that higher-ability individuals have higher wages, but the slope of their wage-education profile is flatter than that for lower ability individuals.

Suggested Citation

  • Simone Balestra & Uschi Backes-Gellner, 2013. "Heterogeneous Returns to Education Over Wage Distribution: Who Profits the Most?," Economics of Education Working Paper Series 0091, University of Zurich, Department of Business Administration (IBW), revised Dec 2013.
  • Handle: RePEc:iso:educat:0091
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    More about this item

    Keywords

    Returns to education; Instrumental variable quantile regression.;

    JEL classification:

    • I21 - Health, Education, and Welfare - - Education - - - Analysis of Education
    • J24 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Human Capital; Skills; Occupational Choice; Labor Productivity
    • 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
    • C36 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Instrumental Variables (IV) Estimation

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