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Marginal College Wage Premiums under Selection into Employment

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  • Matthias Westphal

    (TU Dortmund, RWI Essen, Leibniz Science Campus Ruhr)

  • Daniel A. Kamhöfer

    (University of Düsseldorf, IZA)

  • Hendrik Schmitz

    (Paderborn University, RWI Essen, Leibniz Science Campus Ruhr)

Abstract

In this paper, we identify female long-term wage returns to college education using the educational expansion between 1960-1990 in West Germany as exogenous variation for college enrollment. We estimate marginal treatment effects to learn about the underlying behavioral structure of women who decide for or against going to college (e.g., whether there is selection into gains). We propose a simple partial identification technique using an adjusted version of the Lee bounds to account for women who select into employment due to having a college education, which we call college-induced selection into employment (CISE). We find that women are, on average, more than 17 percentage points more likely to be employed due to having a college education than without. Taking this CISE into account, we find wage returns of 6-12 percent per year of education completed (average treatment effects on the treated).

Suggested Citation

  • Matthias Westphal & Daniel A. Kamhöfer & Hendrik Schmitz, 2020. "Marginal College Wage Premiums under Selection into Employment," Working Papers CIE 133, Paderborn University, CIE Center for International Economics.
  • Handle: RePEc:pdn:ciepap:133
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    Cited by:

    1. Laura Schmitz, 2022. "Heterogeneous Effects of After-School Care on Child Development," Discussion Papers of DIW Berlin 2006, DIW Berlin, German Institute for Economic Research.
    2. Jessica Ordemann & Friedhelm Pfeiffer, 2022. "The evolution of educational wage differentials for women and men in Germany, from 1996 to 2019," Journal for Labour Market Research, Springer;Institute for Employment Research/ Institut für Arbeitsmarkt- und Berufsforschung (IAB), vol. 56(1), pages 1-12, December.
    3. Zhewen Pan & Zhengxin Wang & Junsen Zhang & Yahong Zhou, 2024. "Marginal treatment effects in the absence of instrumental variables," Papers 2401.17595, arXiv.org.

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    More about this item

    Keywords

    Marginal treatment effect; Partial identification; Returns to higher education; Female labor force participation;
    All these keywords.

    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
    • I26 - Health, Education, and Welfare - - Education - - - Returns to Education
    • J24 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Human Capital; Skills; Occupational Choice; Labor Productivity

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