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The relationship between air pollution emissions and income: US Data

Published online by Cambridge University Press:  30 March 2001

RICHARd T. CARSON
Affiliation:
Department of Economics, University of California, San Diego, La Jolla, CA 92093, USA
YONGIL JEON
Affiliation:
Department of Economics, University of California, San Diego, La Jolla, CA 92093, USA
DONALD R. McCUBBIN
Affiliation:
Department of Economics, University of California, San Diego, La Jolla, CA 92093, USA
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Abstract

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Considerable interest has focused on the possible existence of an environmental Kuznets curve, whereby pollution first increases but later falls with increasing income. Empirical studies have concentrated on a wide spectrum of countries and run into inevitable problems of data comparability and quality. We avoid these problems by looking at seven types of air emissions across the 50 US states and find all seven pollutants decrease with increasing per capita income. We also find strong evidence of heteroscedasticity with respect to the income–emissions relationship: lower-income states display much greater variability in per capita emission levels than higher-income states. Additionally, we look at the best measured of these emissions, air toxics, for the period 1988–94. Using a simple sign test, we find support for the notion that an increase in income is associated with a decrease in per capita emissions. However, the change in emissions appears to be unrelated to the magnitude of the change in income. We do find, though, that the reduction in per capita emissions is increasing both in terms of the 1988 level of per capita emissions and income. Possible implications of these results for the development process are discussed.

Type
Research Article
Copyright
© 1997 Cambridge University Press

Footnotes

The authors thank Clive Granger, James E. Rauch, Steven Raphael, and the journal referees and the special issue editor for helpful comments. Adam Browning, US Environmental Protection Agency Region IX, provided considerable assistance in obtaining data.