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

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 p...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:Korean Economic Review 2020-01, Vol.36 (1), p.5
Hauptverfasser: Seik Kim, Hwa Ryung Lee
Format: Artikel
Sprache:kor
Schlagworte:
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
Beschreibung
Zusammenfassung: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.
ISSN:0254-3737