Skin Tone Penalties: Quasi-Experimental Evidence on Colorism in Football

Luis Guillermo Woo-Mora and Donia Kamel ()
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Luis Guillermo Woo-Mora: PSE - Paris School of Economics - UP1 - Université Paris 1 Panthéon-Sorbonne - ENS-PSL - École normale supérieure - Paris - PSL - Université Paris Sciences et Lettres - EHESS - École des hautes études en sciences sociales - CNRS - Centre National de la Recherche Scientifique - INRAE - Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement - ENPC - École nationale des ponts et chaussées - IP Paris - Institut Polytechnique de Paris
Donia Kamel: PSE - Paris School of Economics - UP1 - Université Paris 1 Panthéon-Sorbonne - ENS-PSL - École normale supérieure - Paris - PSL - Université Paris Sciences et Lettres - EHESS - École des hautes études en sciences sociales - CNRS - Centre National de la Recherche Scientifique - INRAE - Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement - ENPC - École nationale des ponts et chaussées - IP Paris - Institut Polytechnique de Paris

World Inequality Lab Working Papers from HAL

Abstract: We provide causal evidence of skin tone discrimination using professional football (soccer) as a natural laboratory. Leveraging a computer-vision measure of skin tone and quasi-random variation in shot outcomes near the goal frame, we implement a Difference-in-Discontinuities design comparing narrowly scored goals to narrowly missed attempts. We find that Light-skinned players receive significantly larger boosts in post-match ratings than Tan-and Dark-skinned peers for identical actions. These disparities appear in both algorithmic and human-assigned evaluations and are concentrated in the subjective component of ratings. Season-level analyses reveal that biased evaluations translate into lower market valuations for darker-skinned players, despite equivalent performance. Evaluative bias, rather than differential treatment in contracts, emerges as a key driver of economic inequality in this high-information labor market. Our findings show how skin color discrimination can persist even in environments with transparent outcomes and extensive performance data.

Keywords: Algorithms; Football; Discrimination; Colorism; Race (search for similar items in EconPapers)
Date: 2026-02
Note: View the original document on HAL open archive server: https://shs.hal.science/halshs-05626376v1
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