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Estimation and interpretation of a Heckman selection model with endogenous covariates

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    21 Citations (Scopus)

    Abstract

    In this paper, we develop a Heckman selection model with endogenous covariates. Estimation of this model is easy and can be done within any econometrics software which supports maximum likelihood estimation of the Heckman selection model. The most important benefit of our model is that it provides an easy-to-interpret measure of the composition of the fully observed sample with respect to unobservables. As an example, we apply our model to the study of the composition of the female full time full year workforce, as has been done by Mulligan and Rubinstein (Q J Econ 123:1061–1110, 2008). We find that their conclusion that the female workforce was negatively selected in the late 1970s is robust to accounting for the potential endogeneity of education in a Heckman selection model. However, we find that accounting for endogeneity leads to a huge increase in the estimated returns to education.

    Original languageEnglish
    JournalEmpirical Economics
    Volume49
    Issue number2
    Pages (from-to)675-703
    Number of pages29
    ISSN0377-7332
    DOIs
    Publication statusPublished - 05.09.2015

    UN SDGs

    This output contributes to the following UN Sustainable Development Goals (SDGs)

    1. SDG 5 - Gender Equality
      SDG 5 Gender Equality

    Research areas and keywords

    • Economics
    • Composition of the female workforce
    • Endogenous covariates
    • Female labor force participation
    • Gender wage gap
    • Sample selection model

    ASJC Scopus Subject Areas

    • Economics and Econometrics
    • Social Sciences (miscellaneous)
    • Mathematics (miscellaneous)
    • Statistics and Probability

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