Date of Award:

5-2014

Document Type:

Thesis

Degree Name:

Master of Science (MS)

Department:

Applied Economics

Committee Chair(s)

Arthur J. Caplan

Committee

Arthur J. Caplan

Committee

Ryan Bosworth

Committee

Man-Keun Kim

Committee

Roger Coulombe

Abstract

Cache County, Utah boasts an abundance of awe-inspiring natural beauty. However, at times, its air quality rivals the worst in the United States. During the winter months of December through February, particulate matter measuring two and a half micrometers or less, commonly known as PM2.5, often concentrates to dangerously high levels causing extensive harm to public health. Lawmakers have scrambled to pass legislation aimed at mitigating the risks posed by poor air quality, recently adopting a county-wide vehicle emissions testing program designed to reduce exhaust emissions from on-road mobile sources. However, its efficacy has been hotly debated and many similar programs around the country have failed to produce significant results.

Using ten years of daily data on PM2.5 concentrations, vehicle use, and meteorological variables to control for the climactic determinants of inversions in Cache County, we construct an econometric model which attempts to explain the variation in PM2.5 levels caused by motor vehicles. Next, employing similar methodology using historical Cache County gas price data, we model how drivers in the county respond to substantial changes in the price of gasoline. Ultimately, these two models together enable us to estimate how increases in gas price might lower vehicle use, thereby reducing public health costs through concomitant decreases in PM2.5 concentrations. In fact, empirical analysis indicates that a winter-time (seasonal) tax on gasoline may be a more effective control mechanism for PM2.5 than the recently adopted vehicle emissions testing program in Cache County. Moreover, we show that the benefits of clean air in the county outweigh the costs of such a tax under the right conditions

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