Measuring the value of air quality: Application of the spatial hedonic model

Seung Gyu Kim, Seong Hoon Cho, Dayton M. Lambert, Roland K. Roberts

Research output: Contribution to journalArticlepeer-review

32 Scopus citations

Abstract

This study applies a hedonic model to assess the economic benefits of air quality improvement following the 1990 Clean Air Act Amendment at the county level in the lower 48 United States. An instrumental variable approach that combines geographically weighted regression and spatial autoregression methods (GWR-SEM) is adopted to simultaneously account for spatial heterogeneity and spatial autocorrelation. SEM mitigates spatial dependency while GWR addresses spatial heterogeneity by allowing response coefficients to vary across observations. Positive amenity values of improved air quality are found in four major clusters: (1) in East Kentucky and most of Georgia around the Southern Appalachian area; (2) in a few counties in Illinois; (3) on the border of Oklahoma and Kansas, on the border of Kansas and Nebraska, and in east Texas; and (4) in a few counties in Montana. Clusters of significant positive amenity values may exist because of a combination of intense air pollution and consumer awareness of diminishing air quality.

Original languageEnglish
Pages (from-to)41-51
Number of pages11
JournalAir Quality, Atmosphere and Health
Volume3
Issue number1
DOIs
StatePublished - Jan 2010

Keywords

  • Air quality
  • Hedonic model
  • Spatial autocorrelation
  • Spatial heterogeneity
  • Total suspended particulates

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