House Price Impacts of Racial, Income, Education, and Age Neighborhood Spatial Concentration
We compare hedonic price models estimated with spatial statistics in order to examine the impacts of four different types of neighborhood spatial association: age, education, income and racial clustering. Using Getis and Ord’s (1995) Z(Gi*) as an indicator of spatial clustering, we estimate the impact of segregation on housing prices in seven metropolitan areas in Ohio, USA. In addition, we examine second order clustering impacts by interacting Z(Gi*) variables. Results of price simulations indicate that a 1 standard deviation increase in spatial concentration of African-Americans decreases property prices, while increases in the spatial concentration of people of similar income, age and education level have a mostly positive impact on housing prices across metropolitan areas. Further, we find that increasing both income and black clustering or educational and black clustering does not necessarily increase house prices above the baseline, while increasing both age and black clustering has a decidedly negative effect.
|Date of creation:||2009|
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