Testing for Asymmetric Employer Learning and Statistical Discrimination

Suqin Ge, Andrea Moro and Beibei Zhu

No 569, GLO Discussion Paper Series from Global Labor Organization (GLO)

Abstract: We test if firms statistically discriminate workers based on race when employer learning is asymmetric. Using data from the NLSY79, we find evidence of asymmetric employer learning. In addition, employers statistically discriminate against non-college educated black workers at time of hiring. We also find that employers directly observe most of the productivity of college graduates at hiring and learn very little over time about these workers.

Keywords: statistical discrimination; employer learning; asymmetric learning (search for similar items in EconPapers)
JEL-codes: D82 J31 J71 (search for similar items in EconPapers)
Date: 2020
New Economics Papers: this item is included in nep-bec and nep-lma
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https://www.econstor.eu/bitstream/10419/218947/1/GLO-DP-0569.pdf (application/pdf)

Related works:
Journal Article: Testing for asymmetric employer learning and statistical discrimination (2021)
Working Paper: Testing for Asymmetric Employer Learning and Statistical Discrimination (2018)
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Persistent link: https://EconPapers.repec.org/RePEc:zbw:glodps:569

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