Credit Building or Credit Crumbling? A Credit Builder Loan’s Effects on Consumer Behavior and Market Efficiency in the United States
通过随机鼓励实验发现，信用建设贷款对消费者信用评分的平均效果为零，但机器学习揭示其效果因消费者已有分期贷款活动而异，对部分消费者产生负面外部性。
Abstract A randomized encouragement design yields null average effects of a credit builder loan (CBL) on consumer credit scores. But machine learning algorithms indicate the nulls are due to stark, offsetting treatment effects depending on baseline installment credit activity. Delinquency on preexisting loan obligations drives the negative effects, suggesting that adding a CBL overextends some consumers and generates negative externalities on other lenders. More favorably for the market, CBL take-up generates positive selection on score improvements. Simple changes to CBL practice, particularly to provider screening and credit bureau reporting, could ameliorate the negative effects for consumers and the market. Authors have furnished an Internet Appendix, which is available on the Oxford University Press Web site next to the link to the final published paper online.