Essays on the Industrial Organization of Mortgage Markets

Abstract

This dissertation consists of two chapters on the industrial organization of mortgage markets in the United States.In the first chapter, titled “Consumer Search Costs in U.S. Mortgage Markets”, I focus on estimating the distribution of consumer search costs in the market for government-backed mortgages in the US during the period from September 2013 to March 2015. I adapt the Hortaçsu and Syverson (2004) search model to mortgage markets. I estimate the distribution of consumer search costs in each U.S. state using recent data on government-insured mortgages. I find that estimated search costs are large; a median borrower would face a search cost equivalent to about $40 in monthly repayment. At the state-level, search cost magnitude is related positively to household income and age and negatively to years of education. I solve counterfactual scenarios in order to study the relationship between search costs and welfare. Compared to the full information scenario, the presence of costly consumer search decreases social welfare by about $600 in monthly repayment per borrower. This decrease in welfare occurs because under costly search borrowers are matched with lower quality lenders and spend resources on searching. At the national level, this decrease corresponds to approximately $35 million per-month. Reductions in search costs would raise social welfare monotonically. A 10% reduction in search cost may raise social welfare by as much as $130 per borrower per month. These findings support recent policies that aim to reduce search costs of mortgage borrowers. In the second chapter, titled “Price Discrimination in U.S. Mortgage Markets”, I examine the existence of price discrimination generated by costly consumer search in the market for mortgages. I develop a stylized model of consumer search in mortgage markets where firms charge optimal prices that depend on borrowers' search cost level. The model produces testable restrictions on the conditional quantile function of observed transacted rates. Using the data on insured Federal Housing Agency loans where price variation is not driven by default risk, I run a quantile regression of transacted interest rates on a set of loan observables, including borrower's credit score, original principal balance, and loan-to-value ratio, among others. I find that predictions of the theoretical model are satisfied for all loan observables under consideration, and price discrimination created by costly consumer search is likely to exist in U.S. mortgage markets.