Hedonic estimation with unobserved characteristics : an application to the housing market in Santiago, Chile

Abstract

We estimate a hedonic price function for the characteristics of housing units in Santiago, Chile, with the aim to capture unobserved utility-generating attributes for each unit. We used for this purpose two different semiparametric regression methods: a local linear kernel regression with a single unobservable index variable, similar to what has been implemented by Bajari and Kahn (2005), and a partially linear in the parameters, partially nonparametric method as first proposed by Robinson (1988). The data used comes from a cross-sectional sample of housing units in Santiago, Chile in 2006. Interestingly, the results obtained for the unobservable components are similar to each other and to ordinary least squares.