The Equilibrium Effects of Information Deletion: Evidence from Consumer Credit Markets

Abstract

This paper studies the equilibrium effects of information restrictions in credit markets using a large-scale natural experiment. In 2012, Chilean credit bureaus were forced to stop reporting defaults for 2.8 million individuals (21% of the adult population). Using panel data on the universe of bank borrowers in Chile combined with the deleted registry information, we implement machine learning techniques to measure changes in the predictions lenders can make about default rates following deletion. Deletion lowers (raises) predicted default the most for poorer defaulters (non-defaulters) with limited borrowing histories. Using a difference-in-differences design, we show that individuals exposed to increases in predicted default reduce borrowing by 6.4% following deletion, while those exposed to decreases raise borrowing by 11.8%. In aggregate, deletion reduces borrowing by 3.5%. Taking the difference-in-difference estimates as inputs into a model of borrowing under adverse selection, we find that deletion reduces surplus under a variety of assumptions about lenders' pricing strategies.