Essays in industrial organization of Peer-to-Peer online credit markets

This dissertation consists of three separate essays on Peer-to-Peer (P2P) online credit markets. The first essay presents new empirical evidence of decreases in loan demand and repayment when prices in the market are determined by competing lenders in auctions as compared to the case in which a platform directly controls all prices. The paper develops an econometric model of loan demand and repayment which is then used to predict borrower choices when they are offered prices set by lenders in a market. I find that when lenders set prices, borrowers are more likely to pick loans of shorter maturity and smaller sizes, and repay less. Aggregated at the market level, demand and repayment of credit fall by 10% and 2%, respectively. In the second paper, I quantify the effects of implementation of finer credit scoring on credit demand, defaults and repayment in the context of a large P2P online credit platform. I exploit an exogenous change in the platform's credit scoring policy where the centralized price setting rules ensure that the one-to-one relationship between credit scores and prices remains intact unlike in a traditional credit market where it is broken. The results show that a 1% increase in interest rate due to the implementation of finer credit scoring results in an average decrease of 0.29% in the requested loan amount, an average increase of 0.01 in the fraction of borrowers who default and an average increase of 0.02 in the fraction of loan repaid. These findings contribute to a better understanding of how a reduction in information asymmetry affects borrower choices in a credit market. The third paper explores the main drivers behind the geographic expansion in demand for credit from P2P online platforms. It uses data from the two largest platforms in the United States to conduct an empirical analysis. By exploiting heterogeneity in local credit markets before the entry of P2P online platforms, the paper estimates the effect of local credit market conditions on demand for credit from P2P platforms. The paper uses a spatial autoregressive model for the main specification. We find that P2P consumer credit expanded more in counties with poor branch networks, lower concentration of banks, and lower leverage ratios