CAREER: Information Frictions in Consumer Credit Markets: Evidence on Policy, Practice, and Beliefs

摘要本项目发展数据和实证方法来量化信息摩擦如何扭曲消费信贷市场的运作。这项研究促进了对美国破产制度的意外后果的理解，如何加强贷款筛选以改善弱势群体的信贷获取，以及家庭如何形成对未来价格的预期。这三个主题领域对信贷市场的基本经济学以及一些信贷产品、政策问题和消费者决策至关重要。本项目提供了工具来衡量三个领域的市场失灵的程度、原因和影响：(1)检验个人破产申请人债务积累中的道德风险，(2)解释信贷配给的普遍性，(3)理解外推预期的形成。本项目利用新收集的数据，详细说明了破产申请人所招致的债务的构成和时间，制定了一项基于工资补偿政策的识别策略，以测试战略借贷效应。为了研究贷款拒绝，该项目收集了数百家贷款机构和数百万贷款申请人的丰富数据，其中申请经常被拒绝，而且没有提供任何条款。将企业和信贷员贷款政策中看似外生的变化与半参数选择模型相结合，可以表征导致如此高比例贷款在均衡状态下被拒绝的信息摩擦。该项目进一步探讨，在这些摩擦的条件下，当前的贷款筛选做法是否最佳。最后，利用房价预期的调查微观数据和分位数回归技术，研究了外推预期的异质性以及乐观信念与行为之间的联系。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

AbstractThis project develops data and empirical methods to quantify how information frictions distort the functioning of consumer credit markets. The research advances understanding of the unintended consequences of the U.S. bankruptcy system, how loan screening can be enhanced to improve credit access across disadvantaged groups, and how households form expectations about future prices. These three topic areas are critical to the fundamental economics of credit markets, as well as to several credit products, policy questions, and consumer decisions. This project provides tools to measure the extent, causes and impact of market failures in three domains: (1) testing for moral hazard in debt accumulation among personal bankruptcy filers, (2) explaining the prevalence of credit rationing, (3) understanding extrapolative expectation formation. Using newly collected data detailing the composition and timing of liabilities incurred by bankruptcy filers, this project develops an identification strategy based on wage garnishing policies to test for strategic borrowing effects. To study loan rejections, this project assembles rich data on hundreds of lenders and millions of loan applicants in a setting where applications are frequently rejected with credit not offered on any terms. Combining plausibly exogenous variation in firm and loan-officer lending policies with a semi-parametric selection model allows the characterization of information frictions that lead to such a high percentage of loans being rejected in equilibrium. The project further explores whether, conditional on those frictions, current loan screening practices are optimal. Finally, the project uses survey micro data of house price expectations and quantile-regression techniques to study heterogeneity in extrapolative expectations and the linkage between optimistic beliefs and behavior.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.