The primary objective of this paper is to improve the methodology for estimating hedonic price functions when the data are inherently spatial. A spatial-econometric hedonic housing price model is developed and estimated for the Seoul metropolitan area to measure the marginal value of improvements in sulfur dioxide (SO2) and nitrogen dioxide (NOx) concentrations. Diagnostic testing favored the spatial-lag model over the spatial error model. Results showed that SO2 pollution levels had a significant impact on housing prices while NOx pollution did not. The authors attribute this differential impact to the relatively higher levels of SO2 pollution when compared with pollution standards and the relative recency of the NOx pollution. Marginal WTP for a 4% improvement in mean SO2 concentrations is about $2333 or 1.4% of mean housing price.
ASJC Scopus subject areas
- Economics and Econometrics
- Management, Monitoring, Policy and Law