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Revisiting the Composition of the Female Workforce - A Heckman Selection Model with Endogeneity

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  • Schwiebert, Jörg

Abstract

In this paper, we revisit the Mulligan and Rubinstein (2008: Selection, investment and women's relative wages over time. The Quarterly Journal of Economics, 123(3):1061-1110) analysis about the composition of the female workforce in the United States. Using a Heckman selection model, these authors found that the selection of women into the female workforce changed from negative to positive over time. However, the authors assumed the exogeneity of covariates, which is sometimes appropriate but not for a variable like education. We revisit the issue of the Mulligan and Rubinstein (2008) paper by developing and applying a Heckman selection model which also controls for the potential endogeneity of education. Applying this estimator to U.S. Census and American Community Survey data, we find that selection has become more positive over time (like in Mulligan and Rubinstein), but that selection has never been negative. We rather find an interesting puzzle concerning the correlation pattern of the unobservables in our model which requires further investigation.

Suggested Citation

  • Schwiebert, Jörg, 2012. "Revisiting the Composition of the Female Workforce - A Heckman Selection Model with Endogeneity," Hannover Economic Papers (HEP) dp-502, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.
    • Handle: RePEc:han:dpaper:dp-502
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    1. Ahn, Hyungtaik & Powell, James L., 1993. "Semiparametric estimation of censored selection models with a nonparametric selection mechanism," Journal of Econometrics, Elsevier, vol. 58(1-2), pages 3-29, July.
    2. Davidson, Russell & MacKinnon, James G., 1993. "Estimation and Inference in Econometrics," OUP Catalogue, Oxford University Press, number 9780195060119.
    3. Newey, Whitney K., 1987. "Efficient estimation of limited dependent variable models with endogenous explanatory variables," Journal of Econometrics, Elsevier, vol. 36(3), pages 231-250, November.
    4. Smith, Richard J & Blundell, Richard W, 1986. "An Exogeneity Test for a Simultaneous Equation Tobit Model with an Application to Labor Supply," Econometrica, Econometric Society, vol. 54(3), pages 679-685, May.
    5. Mroz, Thomas A, 1987. "The Sensitivity of an Empirical Model of Married Women's Hours of Work to Economic and Statistical Assumptions," Econometrica, Econometric Society, vol. 55(4), pages 765-799, July.
    6. O. Ashenfelter & D. Card (ed.), 1999. "Handbook of Labor Economics," Handbook of Labor Economics, Elsevier, edition 1, volume 3, number 3.
    7. Whitney K. Newey, 2009. "Two-step series estimation of sample selection models," Econometrics Journal, Royal Economic Society, vol. 12(s1), pages 217-229, January.
    8. Gallant, A Ronald & Nychka, Douglas W, 1987. "Semi-nonparametric Maximum Likelihood Estimation," Econometrica, Econometric Society, vol. 55(2), pages 363-390, March.
    9. Semykina, Anastasia & Wooldridge, Jeffrey M., 2010. "Estimating panel data models in the presence of endogeneity and selection," Journal of Econometrics, Elsevier, vol. 157(2), pages 375-380, August.
    10. Mitali Das & Whitney K. Newey & Francis Vella, 2003. "Nonparametric Estimation of Sample Selection Models," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 70(1), pages 33-58.
    11. Alan S. Blinder, 1973. "Wage Discrimination: Reduced Form and Structural Estimates," Journal of Human Resources, University of Wisconsin Press, vol. 8(4), pages 436-455.
    12. Rivers, Douglas & Vuong, Quang H., 1988. "Limited information estimators and exogeneity tests for simultaneous probit models," Journal of Econometrics, Elsevier, vol. 39(3), pages 347-366, November.
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    More about this item

    Keywords

    Sample selection model; endogenous covariates; gender wage gap; composition of the female workforce; female labor force participation;
    All these keywords.

    JEL classification:

    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
    • C24 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Truncated and Censored Models; Switching Regression Models; Threshold Regression Models
    • C26 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Instrumental Variables (IV) Estimation
    • J21 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Labor Force and Employment, Size, and Structure
    • J31 - Labor and Demographic Economics - - Wages, Compensation, and Labor Costs - - - Wage Level and Structure; Wage Differentials

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