Measuring the benefits of air quality improvement: A spatial hedonic approach

Chong Won Kim; Tim T. Phipps; Luc Anselin

doi:10.1016/S0095-0696(02)00013-X

Measuring the benefits of air quality improvement: A spatial hedonic approach

Chong Won Kim, Tim T. Phipps, Luc Anselin

Arizona State University

Research output: Contribution to journal › Article › peer-review

376 Scopus citations

Abstract

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 (NO_x) 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 NO_x 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 NO_x pollution. Marginal WTP for a 4% improvement in mean SO₂ concentrations is about $2333 or 1.4% of mean housing price.

Original language	English (US)
Pages (from-to)	24-39
Number of pages	16
Journal	Journal of Environmental Economics and Management
Volume	45
Issue number	1
DOIs	https://doi.org/10.1016/S0095-0696(02)00013-X
State	Published - Jan 2003

ASJC Scopus subject areas

Economics and Econometrics
Management, Monitoring, Policy and Law

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title = "Measuring the benefits of air quality improvement: A spatial hedonic approach",

abstract = "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.",

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