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Additive Kernel Estimates of Returns to Schooling

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  • Ozabaci, Deniz

    (University of Connecticut)

  • Henderson, Daniel J.

    (University of Alabama)

Abstract

In this paper, we employ a partially linear nonparametric additive regression estimator, with recent U.S. Current Population Survey data, to analyze returns to schooling. Similar to previous research, we find that blacks and Hispanics have higher rates of return on average. However, for married males, while non-Hispanic whites have lower returns on average, they typically possess the highest returns in the sample. For females, we are able to show that Hispanics have uniformly higher returns over non-Hispanic whites for the full sample. When we restrict our analysis to females whose highest level of education is a high-school diploma, we find average, but no longer uniformly higher returns. However, these uniformly higher returns resurface for college graduates.

Suggested Citation

  • Ozabaci, Deniz & Henderson, Daniel J., 2014. "Additive Kernel Estimates of Returns to Schooling," IZA Discussion Papers 8736, Institute of Labor Economics (IZA).
    • Handle: RePEc:iza:izadps:dp8736
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    1. Daniel J. Henderson & Anne-Charlotte Souto & Le Wang, 2020. "Higher-Order Risk–Returns to Education," JRFM, MDPI, vol. 13(11), pages 1-25, October.

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    More about this item

    Keywords

    additive; Mincer regressions; rate of return to education; nonparametric;
    All these keywords.

    JEL classification:

    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • J24 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Human Capital; Skills; Occupational Choice; Labor Productivity

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