Statistical discrimination, employer learning, and employment gap by race and education

Seik Kim, Hwa Ryung Lee

    Research output: Contribution to journalArticlepeer-review

    1 Citation (Scopus)

    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.

    Original languageEnglish
    Pages (from-to)5-27
    Number of pages23
    JournalKorean Economic Review
    Volume36
    Issue number1
    Publication statusPublished - 2020

    Bibliographical note

    Publisher Copyright:
    © 2020, Korean Economic Association. All rights reserved.

    Keywords

    • Employer Learning
    • Statistical Discrimination
    • Unemployment Rate

    ASJC Scopus subject areas

    • General Economics,Econometrics and Finance

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