贷款
拒绝
小企业
精算学
统计鉴别
测量数据收集
经济
业务
人口经济学
心理学
财务
统计
精神分析
数学
作者
Atanu Rakshit,Jonathan Peterson
标识
DOI:10.1080/00472778.2022.2108824
摘要
We investigate patterns of racial bias in small business loans denial rates in the US across different credit risk scores. Using data constructed from the 1998 Survey of Small Business Finances and Kauffman Firm Survey, we find disparities in loan approval ratings between Black and White entrepreneurs in intermediate risk categories, but not for the best and worst categories. We explain these findings with a simple and generalizable statistical discrimination model where banks hold prior beliefs of repayment probability based on the applicant’s group and observe noisy signals of creditworthiness. Our model predicts that differences in loan denial rates across groups are more pronounced at middle range values and disappear at very high and very low credit scores. Identifying the likely cause of differential treatment in the market is an important first step in improving representation of minority groups as entrepreneurs. Our findings contribute to this critical effort by delineating the nature of racial bias in the credit market and informing remediation policies.
科研通智能强力驱动
Strongly Powered by AbleSci AI