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Testing for Statistical Discrimination Based on Gender

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  • Rune V. Lesner

Abstract

Gender wage gaps are a prevailing feature of the labour market. Statistical discrimination has been highlighted as a potential source. However, the evidence is scarce. The employer learning literature provides a testable framework. This paper develops an employer learning model which incorporates screening discrimination, stereotyping and prejudiced beliefs. Implications of screening discrimination are found not to be consistent with wage dynamics in the Danish labour market. Stereotyping with prejudiced beliefs is argued to be a more plausible candidate. Workplace characteristics, such as the fraction of women in high†ranking positions, do not affect the level of screening discrimination by gender.

Suggested Citation

  • Rune V. Lesner, 2018. "Testing for Statistical Discrimination Based on Gender," LABOUR, CEIS, vol. 32(2), pages 141-181, June.
    • Handle: RePEc:bla:labour:v:32:y:2018:i:2:p:141-181
    DOI: 10.1111/labr.12120
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    Citations

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    Cited by:

    1. Lepage, Louis Pierre, 2021. "Endogenous learning, persistent employer biases, and discrimination," CLEF Working Paper Series 34, Canadian Labour Economics Forum (CLEF), University of Waterloo.
    2. Babin, J. Jobu & Hussey, Andrew, 2023. "Gender penalties and solidarity — Teaching evaluation differentials in and out of STEM," Economics Letters, Elsevier, vol. 226(C).
    3. Moeeni, Safoura & Wei, Feng, 2022. "The labor market returns to unobserved skills: Evidence from a gender quota," CLEF Working Paper Series 53, Canadian Labour Economics Forum (CLEF), University of Waterloo.
    4. Nan L. Maxwell & Nathan Wozny, 2021. "Gender Gaps in Time Use and Labor Market Outcomes: What’s Norms Got to Do with it?," Journal of Labor Research, Springer, vol. 42(1), pages 56-77, March.
    5. Andrea Moro & Peter Norman, 2019. "Endogenous Comparative Advantage," Scandinavian Journal of Economics, Wiley Blackwell, vol. 121(3), pages 1088-1124, July.
    6. Wang, Jun & Li, Bo, 2020. "Does employer learning with statistical discrimination exist in China? Evidence from Chinese Micro Survey Data," International Review of Economics & Finance, Elsevier, vol. 69(C), pages 319-333.
    7. Keng, Shao-Hsun, 2020. "Gender bias and statistical discrimination against female instructors in student evaluations of teaching," Labour Economics, Elsevier, vol. 66(C).
    8. Conde-Ruiz, J. Ignacio & Ganuza, Juan José & Profeta, Paola, 2022. "Statistical discrimination and committees," European Economic Review, Elsevier, vol. 141(C).
    9. Islam, Asad & Pakrashi, Debayan & Sahoo, Soubhagya & Wang, Liang Choon & Zenou, Yves, 2021. "Gender inequality and caste: Field experimental evidence from India," Journal of Economic Behavior & Organization, Elsevier, vol. 190(C), pages 111-124.
    10. Lepage, Louis Pierre, 2020. "Endogenous learning and the persistence of employer biases in the labor market," CLEF Working Paper Series 24, Canadian Labour Economics Forum (CLEF), University of Waterloo.
    11. Chen, Yutong, 2024. "Does the gig economy discriminate against women? Evidence from physicians in China," Journal of Development Economics, Elsevier, vol. 169(C).

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