Familiarity and Race Bias: Evidence from a Television Competition (and the Case for More Women Judges?)

Chong Bruno Z. () and Chong Marco Z. ()
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Chong Bruno Z.: Bethesda-Chevy Chase HS, Bethesda, MD 20814, USA
Chong Marco Z.: Bethesda-Chevy Chase HS, Bethesda, MD 20814, USA

The B.E. Journal of Economic Analysis & Policy, 2022, vol. 22, issue 2, 389-398

Abstract: While social interaction is claimed to help reduce racial bias, the evidence is mixed. We argue that not only interaction, but familiarity among agents may help reduce race bias. We use new data from MasterChef, a nationally syndicated television competition that cover 10 years. We find that familiarity does not help reduce race bias. When judges are all Caucasian they appear to favor Caucasian contestants and set back minority contestants in the final placements. Interestingly, we find an analogous finding with minority judges. Female judges are the only ones who show no bias.

Keywords: race bias; television; competition; judges; females; minorities (search for similar items in EconPapers)
JEL-codes: J71 J79 Z19 (search for similar items in EconPapers)
Date: 2022
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DOI: 10.1515/bejeap-2022-0058

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