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This paper tests for bias in consumer lending using administrative data from a high-cost lender in the United Kingdom. We motivate our analysis using a new principal-agent model of bias, which predicts that profits should be higher for the most illiquid loan applicants at the margin if loan examiners are biased. We identify the profitability of marginal applicants using the quasi-random assignment of loan examiners. Consistent with our model, we find significant bias against immigrant and older applicants when using the firm’s preferred measure of long-run profits, but not when using the short-run measure used to evaluate examiner performance. Keywords: Discrimination, Consumer Credit


Dobbie, Will, Andres Liberman, Daniel Paravisini, and Vikram Pathania. "Measuring Bias in Consumer Lending." HKS Faculty Research Working Paper Series RWP19-029, 2019.