Valuing urban air quality: a hedonic price analysis in Beijing, China.

Abstract

Although Chinese government has implemented a series of laws, regulations, and policies to deal with air pollutants, air pollution is still one of the biggest concerns in China. Most of the cities in China suffered from extremely high air pollution levels and cannot meet the national air quality standards. In this study, we attempt to measure individuals' average marginal willingness to pay (MWTP) in Beijing with the hedonic price model. We combine an extensive housing transaction dataset with emission data of six air pollutants from 2013 to 2016 in Beijing, China. When estimating the hedonic price function, we apply both ordinary least squares (OLS) and panel model with various fixed effects to better control for unobservables. The empirical results reveal that the concentrations of CO, NO2, PM2.5, and PM10 are significantly negatively correlated with housing prices. However, we found an insignificant relationship with the concentration of SO2 and the concentration of O3 appears to positively increase the housing values. Policy implications based on these results were also discussed.