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Predatory lending and abusive practices arose as a serious danger by increasing the threat of foreclosure and bankruptcy and decreasing the equity accumulated in a housing unit, reducing many of the economic benefits of homeownership. This article describes the characteristics of areas who likely suffered from abusive mortgage lending using Census data, Home Mortgage Disclosure Act data, and publicly recorded mortgage data. A proxy measure of predatory lending is developed based on the loan-to-value (LTV) ratio and state anti-predatory lending regulations, and represents excessively leveraged properties. Discriminant analysis is used to distinguish between areas with these highly leveraged properties and other parts of the City of Philadelphia. The residuals are mapped to evaluate the spatial dimension of the discriminant models across the city. This examination of demographic and socioeconomic characteristics informs efforts to mitigate the consequences and prevent future occurrences of both predatory lending and other manifestations of inequality by viewing it as a spatial and neighborhood phenomenon. [ABSTRACT FROM AUTHOR]

Abstract: Theory suggests that perception of neighborhood quality is influenced by crime, blight, and other outdoor characteristics, by respondent perception of the quality of their housing, and by attributes of the local jurisdiction. It also suggests that these geographical attributes should be confounded by respondent demographic characteristics. Using 48,000 sample responses collected by the American Housing Survey in 2002, ordinary least squares, factor analysis, and hierarchical linear modeling, we connected these strands of theory and found strong associations between neighborhood quality, detrimental conditions, housing quality, socioeconomic status, and age. We also measured a small anti-big city effect, and a few weaker relationships with growing/healthy and demographic homogeneity effect. The application of complex statistical tools, in short, enabled us to obtain insight about how people build mental models of their neighborhoods. [Copyright &y& Elsevier]