Abstract

I explored the hypothesis that economic activity has a significant impact on exposure to air pollution and ultimately human health. I used county-level employment statistics in California (1980-2000), along with major regulatory periods and other controlling factors, to estimate local concentrations of the coefficient of haze, carbon monoxide, and nitrogen dioxide using a mixed regression model approach. The model explained between 33% and 48% of the variability in air pollution levels as estimated by the overall R(2) values. The relationship between employment measures and air pollution was statistically significant, suggesting that air quality improves during economic downturns. Additionally, major air quality regulations played a significant role in reducing air pollution levels over the study period. This study provides important evidence of a role for the economy in understanding human exposure to environmental pollution. The evidence further suggests that the impact of environmental regulations are likely to be overstated when they occur during recessionary periods, and understated when they play out during periods of economic growth.

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