Spatial Patterns of Carbon Emissions in the U.S.: A Geographically Weighted Regression Approach

Posted: 11 Mar 2012  

Julio Videras

Hamilton College - Economics Department

Date Written: March 9, 2012

Abstract

This paper uses U.S. county-level data to examine the extent of geographical variability in the process liking total emissions of carbon dioxide to measures of population, affluence, and technology. Results from geographically-weighted regression models show that there is strong evidence of geographical heterogeneity and that the magnitude, and in some cases, the direction, of the effects vary within and across the 48 contiguous states in the U.S. These results suggest that we ought to be cautious of policy recommendations based on global models that ignore or account imperfectly for spatial dependence.

Keywords: Carbon emissions, Spatial dependence, STIRPAT model, EKC hypothesis, Geographically-weighted regression

JEL Classification: Q38, Q40

Suggested Citation

Videras, Julio, Spatial Patterns of Carbon Emissions in the U.S.: A Geographically Weighted Regression Approach (March 9, 2012). Available at SSRN: https://ssrn.com/abstract=2018930

Julio Videras (Contact Author)

Hamilton College - Economics Department ( email )

198 College Hill Road
Clinton, NY 13323
United States

Paper statistics

Abstract Views
279