Estimation and Evaluation of Loan Discrimination: An Informational Approach

Publisher Website
Google Scholar
Abstract
Many recent studies have analyzed whether lending discrimination exists. In all previous studies, the researcher faces constraints with the available data or modeling problems. In this article, we use a new informational-based approach for evaluating loan discrimination. Given limited and noisy data, we develop a framework for estimating and evaluating discrimination in mortgage lending. This new informational-based approach performs well even when the data are limited or ill conditioned, or when the covariates are highly correlated. Because most data sets collected by bank examiners or banks suffer from some or all of these data problems, the more traditional estimation methods may fail to provide stable and efficient estimates. This new estimator can be viewed as a generalized maximum likelihood estimator.We provide inference and diagnostic properties of this estimator, presenting both sampling experiments and empirical analyses. For two of the three banks analyzed, we observe some evidence of potential racial discrimination.

This publication has 8 references indexed in Scilit: