Racial Screening on the Big Screen? Evidence from the Motion Picture Industry

Liang Zhong, Angela Crema and M. Paserman

No 26190, RFBerlin Discussion Paper Series from ROCKWOOL Foundation Berlin (RFBerlin)

Abstract: We develop a model of discrimination that allows us to interpret observed differences in outcomes across groups, conditional on passing a screening test, as taste-based (employer), statistical, or customer discrimination. We apply this framework to investigate the nature of non-white underrepresentation in the US motion picture industry. Leveraging a novel data set with racial identifiers for the cast of 7,000 motion pictures, we show that, conditional on production, non-white movies exhibit higher average revenues and a smaller variance. Our findings can be rationalized in the context of our model if non-white movies are held to higher standards for production.

Keywords: Discrimination; Identification; Motion Picture Industry; Machine Learning (search for similar items in EconPapers)
JEL-codes: J15 L82 (search for similar items in EconPapers)
Date: 2026-07
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Persistent link: https://EconPapers.repec.org/RePEc:crm:wpaper:26190

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