Interactions, neighborhood selection and housing demand

This paper contributes to the growing literature that aims at identifying and measuring the impact of social context on individual economic behavior. We develop a model of housing structure demand with neighborhood effects and neighborhood choice. Modeling neighborhood choice is of fundamental importance in estimating and understanding endogenous and contextual neighborhood effects. Controlling for non-random sorting into neighborhoods allows for unbiased estimates and provides a means for identifying endogenous neighborhood effects. Estimation of the model exploits a household-level data set that has been augmented with contextual information at two different levels ("scales") of aggregation. One is at the neighborhood level, consisting of about ten neighbors, with the data coming from the neighborhood clusters sub-sample of the American Housing Survey. A second level is the census tract to which these dwelling units belong. These data were geocoded by means of privileged access to confidential US Census data. Our results for the neighborhood choice model indicate that individuals prefer to live near others like themselves. Our estimates of the housing structure demand equation confirm that neighborhood effects are important. In particular, one's demand for housing depends on the mean of neighbors' demand for housing.