Mortgage Lending in Chicago and Los Angeles: A Paired Testing Study of the Pre-Application Process

This paper analyzes data from a recently completed study of discrimination against African-American and Hispanic homebuyers when they visit mortgage lending institutions in two major metropolitan markets to make pre-application inquiries. It represents the first application of paired testing to rigorously measure discrimination in the mortgage lending process. The paired tests isolated significant levels of differential treatment on the basis of race and ethnicity in Chicago with African Americans and Hispanics receiving less information and assistance than comparable whites. Adverse treatment of African-Americans and Hispanics is also observed in Los Angeles for specific treatments, but the overall pattern of treatment observed did not differ statistically from equal treatment. Multivariate analyses for Chicago indicate that large lenders treat minorities more favorably than small lenders and that lenders with substantial numbers of applications from African-Americans treat African Americans more favorably than lenders with predominantly white application pools.

"Ripple Effects" and Forecasting Home Prices in Los Angeles, Las Vegas, and Phoenix

We examine the time-series relationship between housing prices in Los Angeles, Las Vegas, and Phoenix. First, temporal Granger causality tests reveal that Los Angeles housing prices cause housing prices in Las Vegas (directly) and Phoenix (indirectly). In addition, Las Vegas housing prices cause housing prices in Phoenix. Los Angeles housing prices prove exogenous in a temporal sense and Phoenix housing prices do not cause prices in the other two markets. Second, we calculate out-of-sample forecasts in each market, using various vector autoregessive (VAR) and vector error-correction (VEC) models, as well as Bayesian, spatial, and causality versions of these models with various priors. Different specifications provide superior forecasts in the different cities. Finally, we consider the ability of theses time-series models to provide accurate out-of-sample predictions of turning points in housing prices that occurred in 2006:Q4. Recursive forecasts, where the sample is updated each quarter, provide reasonably good forecasts of turning points.