Innovations in Information Technology and the Mortgage Market,” University of Texas at Austin mimeo

In this paper, I study the effects of innovations in information technology on the housing market. Specifically, I focus on the improved ability of lenders to assess the credit risk of home buyers, which has become possible with the emergence of automated underwriting systems in the United States in the mid-1990s. I develop a standard life-cycle model with incomplete mar-kets and idiosyncratic income uncertainty. I explicitly model the housing tenure choice of the households: rent/purchase decision for renters and stay/sell/default decision for homeowners. Risk-free lenders offer mortgage contracts to prospective home buyers and the terms of these contracts depend on the observable characteristics of households. Households are born as ei-ther good credit risk types—having a high time discount factor—or bad types—having a low time discount factor. The type of the household is the only source of asymmetric information between households and lenders. I find that as lenders have better information about the type of households, the average downpayment fraction decreases together with an increase in the average mortgage premium, the foreclosure rate, and the dispersions of mortgage interest rates and downpayment fractions, which are consistent with the trends in the housing market in the last 15 years. From a welfare perspective, I find that better information, on average, makes households better off