Igor Livshits is an Economic Advisor and Economist at the Federal Reserve Bank of Philadelphia.
Abstract: This paper examines a novel mechanism of credit-history building as a way of aggregating information across multiple lenders. We build a dynamic model with multiple competing lenders, who have heterogeneous private information about a consumer’s creditworthiness, and extend credit over multiple stages. Acquiring a loan at an early stage serves as a positive signal—it allows the borrower to convey to other lenders the existence of a positively informed lender (advancing that early loan)—thereby convincing other lenders to extend further credit in future stages. This signaling is costly to the least risky borrowers for two reasons. First, taking on an early loan may involve cross subsidization from the least risky borrowers to more risky borrowers. Second, the least risky borrowers may take inefficiently large loans relative to the symmetric-information benchmark. We demonstrate that, despite these two possible costs, the least risky borrowers actually prefer these equilibria to those without information aggregation. Our analysis offers an interesting and novel insight into debt dilution. Contrary to the conventional wisdom, we show that in our model, the original lender is more likely to be repaid if his loan is diluted by more (i.e., borrowers who take on larger additional loans are more likely to repay than ones with smaller additional loans). The reason is that a larger additional loan implies that other lenders have positive signals about the borrower. In other words, while a borrower of a given riskiness is more likely to default on a larger loan, in our model, due to information aggregation, larger loans are only given to the least risky borrowers.