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Working Paper

Self-Selection and Discrimination in Credit Markets

In this paper we make two contributions toward a better understanding of the causes and consequences of discrimination in credit markets. First, we develop an explicit theoretical model of the underwriting process in which lenders use a simple Bayesian updating process to evaluate applicant creditworthiness. Using a signal correlated with an applicant’s true creditworthiness and their prior beliefs about the distribution of credit risk in the applicant pool, lenders are able to evaluate an applicant’s expected or “inferred” creditworthiness to determine which loans to approve and which ones to deny. Second, we explicitly model the self-selection behavior of individuals to show how market frictions like bigotry can affect application decisions. Because these decisions shape banks’ prior beliefs about the distribution of credit risk, they also affect the Bayesian posterior from which banks compute an applicant’s inferred creditworthiness, implying that statistical discrimination can arise endogenously. In a market in which only some lenders have “tastes for discrimination,” we show that there are conditions under which lenders without racial animus will also discriminate.

Working Papers of the Federal Reserve Bank of Cleveland are preliminary materials circulated to stimulate discussion and critical comment on research in progress. They may not have been subject to the formal editorial review accorded official Federal Reserve Bank of Cleveland publications. The views expressed in this paper are those of the authors and do not represent the views of the Federal Reserve Bank of Cleveland or the Federal Reserve System.

Suggested Citation

Longhofer, Stanley, and Stephen R. Peters. 1998. “Self-Selection and Discrimination in Credit Markets.” Federal Reserve Bank of Cleveland, Working Paper No. 98-09.