Spatial heterogeneity of marginal willingness to pay for air quality in PM2.5: analysis of buyers’ housing price in Beijing through hedonic price, spatial regression, and quantile regression models

Abstract

Valuing air quality can help governments better evaluate the economic benefits of policies related to air pollution. However, many studies ignore heterogeneity and spatial effects within cities, which may render the results inaccurate. To fill these gaps, this study attempted to examine individuals’ marginal willingness to pay (MWTP) for air quality across locations and buyers in Beijing by utilizing hedonic price, spatial regression and quantile regression models. The results showed: (1) a concentration of PM2.5 is significantly negatively correlated with housing prices. Specifically, the value of the MWTP for a 1% improvement in PM2.5 is US$327, and this figure is US$177 after considering the spatial effects. (2) The MWTP for air quality is heterogeneous across locations. MWTP for air quality is lower the farther away the location is from the central business district (CBD) and the nearest employment center, the lower the MWTP for air quality. (3) Buyers of high-priced housing display a higher MWTP for air quality. These findings show that developing countries facing environmental issues should re-examine the traditional development model of “sacrificing the environment for economic growth” and develop a sustainable model. Moreover, further joining of air pollution control and a differential, location-specific scheme coupled with an individual-specific scheme for developing new communities is necessary.