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Prejudice and Gender Differentials in the U.S. Labor Market in the Last Twenty Years

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  • Luca Flabbi

Abstract

Earnings differentials between men and women have experienced a stable convergence during the 1980s, following a process started in the late 1970s. However, in the 1990s the convergence has almost stopped. The first objective of the paper is to evaluate if discrimination, defined as explicit prejudice, may have a role in explaining this slowdown in the converge. The second objective is to assess whether the prediction of a de- crease in the proportion of prejudiced employers implied by the Becker's model of taste discrimination is taking place and if so at what speed. These objectives are achieved by developing and estimating a search model of the labor market with matching, bargaining, employer's prejudice and worker's participation decisions. The results show that the proportion of prejudiced employers is estimated to be decreasing at an increasing speed, going from about 69% in 1985 to about 32% in 2005. Therefore prejudice does not seem a relevant factor in explaining the slower convergence be- tween male and female earnings in the 1990s. The results are consistent with the Becker's model of taste discrimination if one is willing to assume a very slow adjustment process.

Suggested Citation

  • Luca Flabbi, 2007. "Prejudice and Gender Differentials in the U.S. Labor Market in the Last Twenty Years," Carlo Alberto Notebooks 57, Collegio Carlo Alberto.
    • Handle: RePEc:cca:wpaper:57
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    References listed on IDEAS

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    Cited by:

    1. Leonardo Felli & Leeat Yariv & Allan Collard-Wexler & Mariagiovanna Baccara, 2010. "Gender and Racial Biases: Evidence from Child Adoption," 2010 Meeting Papers 273, Society for Economic Dynamics.
    2. Giovanni Sulis, 2012. "Gender wage differentials in Italy: a structural estimation approach," Journal of Population Economics, Springer;European Society for Population Economics, vol. 25(1), pages 53-87, January.
    3. Thanos Mergoupis & Shasi Nandeibam, 2011. "Wage Discrimination and Population Composition," Department of Economics Working Papers 9/11, University of Bath, Department of Economics.
    4. Luca Flabbi & Mario Macis & Andrea Moro & Fabiano Schivardi, 2019. "Do Female Executives Make a Difference? The Impact of Female Leadership on Gender Gaps and Firm Performance," The Economic Journal, Royal Economic Society, vol. 129(622), pages 2390-2423.
    5. Flinn, C. & Todd, P. & Zhang, W., 2020. "Personality Traits, Job Search and the Gender Wage Gap," Cambridge Working Papers in Economics 2053, Faculty of Economics, University of Cambridge.
    6. Shirai, Daichi & Nagamachi, Kohei & Eguchi, Naotaka, 2012. "The Impacts of Firms' Technology Choice on the Gender Differences in Wage and Time Allocation: A Cross-Country Analysis," MPRA Paper 56666, University Library of Munich, Germany, revised 13 Jun 2014.
    7. Marcela Perticará & Mauricio Tejada, 2022. "Sources of gender wage gaps for skilled workers in Latin American countries," The Journal of Economic Inequality, Springer;Society for the Study of Economic Inequality, vol. 20(2), pages 439-463, June.
    8. Lucas Navarro & Mauricio Tejada, 2022. "Does Public Sector Employment Buffer the Minimum Wage Effects?," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 43, pages 168-196, January.

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    More about this item

    Keywords

    Gender Differentials; Discrimination; Search Models; Maximum Likelihood Estimation; Structural Estimation.;
    All these keywords.

    JEL classification:

    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • J7 - Labor and Demographic Economics - - Labor Discrimination
    • J64 - Labor and Demographic Economics - - Mobility, Unemployment, Vacancies, and Immigrant Workers - - - Unemployment: Models, Duration, Incidence, and Job Search

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