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Estimation of the Effects of Statistical Discrimination on the Gender Wage Gap

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  • Atsuko Tanaka

    (University of Calgary)

Abstract

How much of the gender wage gap can be attributed to statistical discrimination? Applying an employer learning model and Instrumental Variable (IV) estimation strategy to Japanese panel data, I examine how women's generally weak labor force attachment affects wages when employers cannot easily observe an individual's labor force intentions. To overcome endogeneity issues, I use survey information on individual workers' intentions to continue working after having children and Japanese panel data with exogenous variation in average quit rates for female workers. I find that the extent of statistical discrimination is greatest for young age cohorts, ages 24 to 35, and that it diminishes for older cohorts. I also find that if employers could observe an individual's labor force intentions, the gender wage gap could be reduced from 17% to 5% for workers aged 24 to 29.

Suggested Citation

  • Atsuko Tanaka, "undated". "Estimation of the Effects of Statistical Discrimination on the Gender Wage Gap," Working Papers 2015-22, Department of Economics, University of Calgary, revised 21 Dec 2015.
  • Handle: RePEc:clg:wpaper:2015-22
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    File URL: https://econ.ucalgary.ca/sites/econ.ucalgary.ca.manageprofile/files/unitis/publications/1-6640286/atanaka_evidence.pdf
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    References listed on IDEAS

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    1. Sumru Altu─č & Robert A. Miller, 1998. "The Effect of Work Experience on Female Wages and Labour Supply," Review of Economic Studies, Oxford University Press, vol. 65(1), pages 45-85.
    2. John M. Barron & Dan A. Black & Mark A. Loewenstein, 1993. "Gender Differences in Training, Capital, and Wages," Journal of Human Resources, University of Wisconsin Press, vol. 28(2), pages 343-364.
    3. Andrea Moro, 2003. "The Effect Of Statistical Discrimination On Black-White Wage Inequality: Estimating A Model With Multiple Equilibria," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 44(2), pages 467-500, May.
    4. Heckman, James, 2013. "Sample selection bias as a specification error," Applied Econometrics, Publishing House "SINERGIA PRESS", vol. 31(3), pages 129-137.
    5. Oaxaca, Ronald, 1973. "Male-Female Wage Differentials in Urban Labor Markets," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 14(3), pages 693-709, October.
    6. Oxoby, Robert J., 2014. "Social inference and occupational choice: Type-based beliefs in a Bayesian model of class formation," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 51(C), pages 30-37.
    7. David Bjerk, 2008. "Glass Ceilings or Sticky Floors? Statistical Discrimination in a Dynamic Model of Hiring and Promotion," Economic Journal, Royal Economic Society, vol. 118(530), pages 961-982, July.
    8. Juhn, Chinhui & Murphy, Kevin M & Pierce, Brooks, 1993. "Wage Inequality and the Rise in Returns to Skill," Journal of Political Economy, University of Chicago Press, vol. 101(3), pages 410-442, June.
    9. Henry S. Farber & Robert Gibbons, 1996. "Learning and Wage Dynamics," The Quarterly Journal of Economics, Oxford University Press, vol. 111(4), pages 1007-1047.
    10. Lundberg, Shelly J & Startz, Richard, 1983. "Private Discrimination and Social Intervention in Competitive Labor Markets," American Economic Review, American Economic Association, vol. 73(3), pages 340-347, June.
    11. Marianne Bertrand & Sendhil Mullainathan, 2004. "Are Emily and Greg More Employable Than Lakisha and Jamal? A Field Experiment on Labor Market Discrimination," American Economic Review, American Economic Association, vol. 94(4), pages 991-1013, September.
    12. Zvi Eckstein & Kenneth I. Wolpin, 1989. "The Specification and Estimation of Dynamic Stochastic Discrete Choice Models: A Survey," Journal of Human Resources, University of Wisconsin Press, vol. 24(4), pages 562-598.
    13. 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.
    14. Joseph G. Altonji & Charles R. Pierret, 2001. "Employer Learning and Statistical Discrimination," The Quarterly Journal of Economics, Oxford University Press, vol. 116(1), pages 313-350.
    15. Schwab, Stewart, 1986. "Is Statistical Discrimination Efficient?," American Economic Review, American Economic Association, vol. 76(1), pages 228-234, March.
    16. Fabian Lange, 2007. "The Speed of Employer Learning," Journal of Labor Economics, University of Chicago Press, vol. 25, pages 1-35.
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