Abstract: How do inaccurate priors about the distribution of interest rates affect search and outcomes in consumer credit markets? In collaboration with Chile's financial regulator, we conducted a randomized controlled trial with 112,063 loan seekers where we showed treated participants a price comparison tool that we built using administrative data on the universe of consumer loans merged with borrower characteristics. The tool shows loan seekers a conditional distribution of interest rates based on similar loans obtained recently by similar borrowers. We find that consumers thought interest rates were lower than they actually were, and the price comparison tool caused them to increase their expectations about the interest rate they would obtain by 56%. Consumers also underestimated price dispersion, and our price comparison tool caused them to increase their estimates of dispersion by 69%. The price comparison tool did not cause people to search or apply at more institutions, but it did cause them to be 28% more likely to negotiate with their lender, to receive 13% more offers and 11% lower interest rates, and to be 5% more likely to take out a loan. We also cross-randomized whether we asked participants their priors about the distribution of interest rates, and find that merely asking these questions led them to search at 4% more institutions and obtain 9% lower interest rates.
Discussant: Bronson Argyle, Brigham Young University
Tianyu Han, Hong Kong University of Science & Technology
Xiao Yin, University College London
Abstract: This paper investigates consumer misperceptions of credit card debt interest costs using administrative data, surveys, and randomized controlled trials. Our findings indicate that borrowers exhibit inaccurate perceptions of the interest costs of unsecured debt, resulting in substantial debt accumulation. A one percentage point lower perceived interest rate leads to 5% higher credit card debt relative to the pre-treatment average. These misperceptions are likely to stem from mistakes driven by financial literacy, particularly in luxury spending decisions, rather than imperfect knowledge of current debt levels or liquidity constraints.
