Essays on household finance and credit market regulation

Abstract

This thesis consists of three chapters on household finance and regulatory policy in consumer credit markets. The first chapter studies the efficiency and distributional effects of credit card pricing restrictions in the 2009 Credit CARD Act. I document how two forces drive these restrictions' effects: first, the Act constrains lenders from adjusting interest rates in response to new information about default risk, which exacerbates adverse retention of risky borrowers and induces partial market unraveling on new accounts; second, the Act constrains lenders from pricing private information about demand, which reduces markups on inelastic borrowers. I develop a structural model of the US credit card market to study how heightened information problems and lower markups interact in equilibrium to determine the Act's effects. I find that equilibrium market unraveling is most severe for subprime consumers, but the reduction in markups is substantial throughout the market, so that on net, the Act's restrictions allow consumers of all credit scores to capture higher surplus on average. Total surplus inclusive of firm profits rises among prime consumers, whereas gains in subprime consumer surplus are greatest among borrowers who were recently prime. The second chapter (co-authored with Alexander Bartik) also studies the regulation of credit market information, focusing on the use of such information in labor markets. In particular we study recent bans on employers' use of credit reports to screen job applicants. This practice has been popular among employers but controversial for its perceived disparate impact on racial minorities. Exploiting geographic, temporal, and job-level variation in which workers are covered by these bans, we analyze these bans' effects in two datasets: the panel dimension of the Current Population Survey (CPS); and data aggregated from state unemployment insurance records. We find that the bans reduced job-finding rates for blacks by 7 to 16 percent, and increased subsequent separation rates for black new hires by 3 percentage points. Results for Hispanics and whites are less conclusive. We interpret these findings in a statistical discrimination model in which credit report data, more for blacks than for other groups, send a high-precision signal relative to the precision of employers' priors. The third chapter (co-authored with Sydnee Caldwell and Daniel Waldinger) returns to consumer credit markets and studies determinants of household borrowing behavior. Many economic models predict that consumption and borrowing decisions today depend on beliefs about risky future income. We quantify one contributor to income uncertainty and study its effects: uncertainty about annual tax refunds. In a low-income sample for whom tax refunds can be a substantial portion of income, we collect novel survey evidence on tax filers' expectations of and uncertainty about their tax refunds; we then link these data with administrative tax data, a panel of credit reports, and survey-based consumption measures. We find that while many households have correct mean expectations about their refunds, there is substantial, and accurately reported, subjective uncertainty. Households borrow moderate amounts out of expected tax refunds: for each dollar of expected refund, roughly 15 cents in revolving debt is repaid after refund receipt. This borrowing and repayment is less pronounced for more uncertain households, consistent with precautionary behavior. The unexpected component of tax refunds is not used to pay down debt, but rather induces higher debt levels. Credit report and survey evidence both suggest that these higher debt levels are driven by newly financed durable purchases such as vehicles.