Statistical analyses of mortgage redlining at the neighborhood level have fueled the debate over the existence of racial redlining in mortgage lending, both "proving" and "disproving" that redlining exists, depending upon the type of model used. In this paper, we compare results of different statistical models using data for the Washington, DC metropolitan area to determine their usefulness in providing statistical evidence on this issue. After demonstrating the sensitivity of single-equation models to specification error, we estimate a simultaneous equations model of mortgage credit flows. This model makes it possible to analyze differences in the supply and demand for mortgage credit by the racial composition of the community. We conclude that most, if not all, statistical evidence of racial redlining based on aggregate loan data is at best inconclusive, and more likely, misleading.
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