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.

Other Things Being Equal: A Paired Testing Study of Discrimination in Mortgage Lending

This article summarizes a recently completed study, funded by the U.S. Department of Housing and Urban Development (HUD) and conducted by the Urban Institute, of discrimination against black 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 disclosed significant levels of adverse treatment on the basis of race and ethnicity, with African Americans and Hispanics receiving less information and assistance than comparable whites, even at this very early stage in the application process.

Capital Accumulation in the Presence of Informal Credit Contracts: Does the Incentive Mechanism Work Better than Credit Rationing Under Asymmetric Information?

Credit markets with asymmetric information often prefer credit rationing as a profit maximizing device. This paper asks whether the presence of informal credit markets reduces the cost of credit rationing, that is, whether it can alleviate the impact of asymmetric information based on the available information. We used a dynamic general equilibrium model with heterogenous agents to assess this. Using Indian credit market data our study shows that the presence of informal credit market can reduce the cost of credit rationing by separating high risk firms from the low risk firms in the informal market. But even after this improvement, the steady state capital accumulation is still much lower as compared to incentive based market clearing rates. Through self revelation of each firm's type, based on the incentive mechanism, banks can diversify their risk by achieving a separating equilibrium in the loan market. The incentive mechanism helps banks to increase capital accumulation in the long run by charging lower rates and lending relatively higher amount to the less risky firms. Another important finding of this study is that self-revelation leads to very significant welfare improvement, as measured by consumptiuon equivalence.

Empirical Analysis of Credit Risk Regime Switching and Temporal Conditional Default Correlation in Credit Default Swap Valuation: The Market liquidity effect

In this paper, we extend the debate concerning Credit Default Swap valuation to include time varying correlation and co-variances. Traditional multi-variate techniques treat the correlations between covariates as constant over time; however, this view is not supported by the data. Secondly, since financial data does not follow a normal distribution because of its heavy tails, modeling the data using a Generalized Linear model (GLM) incorporating copulas emerge as a more robust technique over traditional approaches. This paper also includes an empirical analysis of the regime switching dynamics of credit risk in the presence of liquidity by following the general practice of assuming that credit and market risk follow a Markov process. The study was based on Credit Default Swap data obtained from Bloomberg that spanned the period January 1st 2004 to August 08th 2006. The empirical examination of the regime switching tendencies provided quantitative support to the anecdotal view that liquidity decreases as credit quality deteriorates. The analysis also examined the joint probability distribution of the credit risk determinants across credit quality through the use of a copula function which disaggregates the behavior embedded in the marginal gamma distributions, so as to isolate the level of dependence which is captured in the copula function. The results suggest that the time varying joint correlation matrix performed far superior as compared to the constant correlation matrix; the centerpiece of linear regression models.

US Corporate Default Swap Valuation: The Market Liquidity Hypothesis and Autonomous Credit Risk

This paper develops a reduced form three-factor model which includes a liquidity proxy of market conditions which is then used to provide implicit prices. The model prices are then compared with observed market prices of credit default swaps to determine if swap rates adequately reflect market risks. The findings of the analysis illustrate the importance of liquidity in the valuation process. Moreover, market liquidity, a measure of investors. willingness to commit resources in the credit default swap (CDS) market, was also found to improve the valuation of investors. autonomous credit risk. Thus a failure to include a liquidity proxy could underestimate the implied autonomous credit risk. Autonomous credit risk is defined as the fractional credit risk which does not vary with changes in market risk and liquidity conditions.