This report examines the effects of certain socially sensitive variables on urban mortgage loan flow patterns. In particular, the effects of racial and age - of - structure characteristics on neighborhoods are examined to ascertain whether they have a significant impact on lending patterns and whether they provide any insights concerning the mortgage redlining controversy. The study used an intraurban loan flow model estimated for nine midwestern standard metropolitan statistical areas. Several different forms of the model are estimated: the total flow of owner - occupant mortgage loans is analyzed for the nine cities, and the mix of conventional and insured mortgage loans is examined. Home improvement loan flows are also examined, since they represent a major means of maintaining and upgrading the housing stock in urban neighborhoods. The methodology is a cross section regression analysis of the census tracts of the nine cities. The loan volume generated in each census tract is treated as the outcome of market demand and supply forces. The models are estimated individually for each city, and the data are pooled across cities and treated as one sample. The nine cities analyzed include Cincinnati, Cleveland, Dayton, Toledo, Canton, and Lima, Ohio; and Indianapolis, Fort Wayne, and South Bend, Ind. Results indicate that racial composition is a significant determinant of loan flows. Results support the notion of a tipping point phenomenon in which lenders may view racially mixed neighborhoods as being riskier areas in which to lend because of the possibility of rapid white flight and its resultant destabilizing effect on property values. Lenders may favor less risky government - insured loans to conventional loans in these areas. Moreover, the number of home improvement loans in a tract increases as the proportion of blacks increases. The effects of age - of - structures were usually insignificant. Data tables, 54 references, and footnotes are supplied.
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