Identifying Robust, Parsimonious Neighborhood Indicators

Abstract

Identifying a few indicators that summarily tracked key dimensions of neighborhoods would be invaluable for neighborhood monitoring and measuring impacts of interventions. The goal of this article is to search empirically for such robust, parsimonious indicators. In five cities, the authors analyze the interrelationships among a broad set of census tract indicators related to mortgage market activity; home prices; jobs and firms; demographic, socioeconomic, and housing stock characteristics; crime; and public assistance and health. Through factor analysis, they identify four to six neighborhood dimensions among these indicators that are common across cities. Using regression, the authors identify a parsimonious number of indicators that are inexpensive, annually updated, and available for all U.S. communities yet robustly capture significant variation in these neighborhood dimensions. Home Mortgage Disclosure Act (HMDA) data on mortgage approval rates, loan amounts, and loan applications and Dunn and Bradstreet data on businesses comprise such a set for four of the dimensions.