Hedonic models have been widely used in the literature for valuation of non- market goods such as air quality. While the inclusion of air quality variables in hedonic models is common in applied work, there is not theoretical basis for defining the functional relation between air quality and house prices. Estimation of semiparametric models that allow the data to determine the functional form may provide more insight on the real relationships suggested by the data rather than imposing the constraints of fully parametric models. Using an instrumental variable estimator, I explore the advantages of using semiparametric models in the estimation of spatial hedonic models by comparing the economic estimates from a parametric spatial lag model with those of a semiparametric specification, where the environmental variable is introduced nonparametrically.
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Paper provided by GeoDa Center for Geospatial Analysis and Computation in its series GeoDa Center Working Papers with number
2008-10.