Estimating environment impacts on housing prices

Housing is understood to be a necessity good, whereas the environment is still viewed as a luxury good, which implies that environmental factors significantly impact on housing prices. This impact is usually measured via aspatial linear hedonic models, but this article goes further, extending those traditional analyses to incorporate spatial autocorrelation, spatial heterogeneity, and nonlinearity. A set of competing parametric and semiparametric spatial models, some of which are new proposals, are estimated in order to measure the impact of the environment on such prices. The percentage of residents who declare that the neighborhood has serious pollution problems is used as a (subjective) environmental factor. One of the reasons why this measure was chosen is because the hedonic method only captures people's willingness to pay for perceived rather than measured differences in environmental attributes. We use a massive database containing the price and characteristics of 10,512 homes in Madrid (Q1 2010). The results obtained suggest that the environment has a significant impact on housing prices; however, when the model includes a drift and/or areal variables, these components absorb a substantial part of the environmental impact.