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Statistical Discrimination, Employer Learning, and Employment Gap by Race and Education

Author

Listed:
  • Seik Kim

    (Korea University)

  • Hwa Ryung Lee

    (Korea Development Institute)

Abstract

Tests of statistical discrimination require evaluation records provided by employers or variables that employers do not observe directly but are observed by researchers. As such variables are difficult to obtain, this paper develops a strategy that uses variables available in usual data sets. This paper derives testable implications for statistical discrimination by exploiting the heterogeneity in employer learning processes. Evidence from analysis using the March Current Population Survey for 1971-2016 is consistent with the theoretical predictions. The empirical findings are not explained by alternative hypotheses, such as human capital theory, taste-based discrimination, or search and matching models.

Suggested Citation

  • Seik Kim & Hwa Ryung Lee, 2020. "Statistical Discrimination, Employer Learning, and Employment Gap by Race and Education," Korean Economic Review, Korean Economic Association, vol. 36, pages 5-27.
  • Handle: RePEc:kea:keappr:ker-20200101-36-1-01
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    More about this item

    Keywords

    Employer Learning; Statistical Discrimination; Unemployment Rate;
    All these keywords.

    JEL classification:

    • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness
    • J64 - Labor and Demographic Economics - - Mobility, Unemployment, Vacancies, and Immigrant Workers - - - Unemployment: Models, Duration, Incidence, and Job Search
    • J71 - Labor and Demographic Economics - - Labor Discrimination - - - Hiring and Firing

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