Measuring Gender and Religious Bias in the Indian Judiciary

Elliott Ash, Sam Asher (), Aditi Bhowmick, Sandeep Bhupatiraju, Daniel L. Chen, Tatanya Devi, Christoph Goessmann, Paul Novosad and Bilal Siddiqi
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Daniel L. Chen: TSE-R - Toulouse School of Economics - UT Capitole - Université Toulouse Capitole - UT - Université de Toulouse - 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, CNRS - Centre National de la Recherche Scientifique

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Abstract: We study judicial in-group bias in Indian criminal courts, collecting data onover 80 million legal case records from 2010–2018. We exploit quasi-random assignment of judges and changes in judge cohorts to examine whether defendant outcomes are affected by being assigned to a judge with a similar religious or gender identity. We estimate tight zero effects of in-group bias. The upper end of our 95% confidence interval rejects effect sizes that are one-fifth of those in most of the prior literature.

Date: 2023-01-04
New Economics Papers: this item is included in nep-law
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Working Paper: Measuring Gender and Religious Bias in the Indian Judiciary (2022)
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