Three essays on envrionmental economics

This dissertation is a collection of three studies that investigate welfare measurement, causation of addition emission, and effectiveness of policy in environmental economics. The first study focuses on the discrepancy from different data sources in nonmarket valuation. This study suggests a new valuation method to solve one common problem shown frequently in combining RP and SP data. The second study examines the significance of the relation between two critical concerns, obesity and vehicle emission. This study shows, even though the impact of obesity on gasoline consumption seems to be significantly large in either one side or aggregate data level, the significance is ambiguous or the magnitude of impact is not sufficiently large study after removing unobserved household characteristics using household-level data. The third study investigates the rebound effect in vehicle use, a critical parameter in cost-benefit analyses of increases in the corporate average fuel economy (CAFE) standards. The following illustrates the ideas and findings of three chapters contained within this dissertation.The first study, "Combining Revealed and Stated Preference Data: A Latent Class Ap- proach," proposes a new framework to combine revealed and stated preference data when the convergent validity assumption is not hold.A substantial literature exists combining data from revealed preference (RP) and stated preference (SP) sources, aimed either at testing for the convergent validity of the two approaches used in nonmarket valuation or as a means of drawing on their relative strengths to improve the ultimate estimates of value. In doing so, it is assumed that convergence of the two elicitation approaches is an "all or nothing" proposition; i.e., the RP and SP data are either consistent with each other or they are not. The purpose of this paper is to propose an alternative framework that allows for possible divergence among individuals in terms of the consistency between their RP and SP responses. In particular, we suggest the use of the latent class approach to segment the population into two groups. The first group has RP and SP responses that are internally consistent, while the remaining group exhibits some form of inconsistent preferences. An EM algorithm is employed in an empirical application that draws on the moose hunting data set used in earlier combined RP and SP exercises. The empirical results suggest that somewhat less than half the sample exhibits inconsistent preferences. We also examine differences in welfare estimates drawn from the two classes.The second study, "Does Obesity Matter for the Environment? Evidence from Vehicle Choices and Usage" studies the interesting link between obesity and vehicle emission, using unique household-level data.The rising rate of obesity has become a prominent social concern in the U.S. and through- out the world. Several recent studies examine how obesity influences households' driving or vehicle choice behavior. While the results in prior studies are compelling, the studies suffer from two shortcomings. First, prior studies rely on aggregate data (national or county level), rather than individual or household level observations, potentially masking important factors determining individual choices for vehicles and driving. Second, while previous works able to establish a link between obesity and vehicle choice or driving, linking vehicle choice, in turn, to overall emissions requires information regarding vehicle miles driven. The objective of this study is to address these two limitations, using household observations from the Panel Study of Income Dynamics (PSID), jointly modeling the impact of obesity on the vehicle choice and vehicle miles traveled (VMT). In particular, we investigate the impact of obesity and overweight by employing both reduced-form (linear panel model) and structural model (joint discrete and continuous choice model). Our study shows that the prevalence of obesity in 2005 has remained at the 1981 level, and gasoline consumption would be 3% saved in the reduced-form approach. While the rate of overweight people in 2005 has remained at the 1981 level, only 1.6% less gasoline would be demanded using the structural-approach. Our empirical findings suggest that the comprehensive impact of obesity and overweight on gasoline consumptions is little or ambiguous in contrast to the results of prior studies considering either driving or vehicle choices.The third study, "Vehicle Fuel Efficiency and the Rebound Effect: Evidence from U.S. Panel Data" examines the rebound effect of vehicle usage. This study revisits one of the classical issues in energy economics using U.S. panel data which have never used in this area.The Corporate Average Fuel Economy (CAFE) standards are a centerpiece of the United States' efforts to control mobile source air pollution. In addition to being politically expedient relative to a more direct gasoline or carbon tax, they may also be more effective as a pol- icy instrument, if, as the literature suggests, consumers are subject to the so-called "energy paradox," undervaluing the fuel cost savings from more fuel efficient vehicles. However, at the same time, there are also risks associated with CAFE standards. In particular, to the extent that individuals respond to increased fuel efficiency by driving more, a response known as the "rebound effect," the impact of the standards may be significantly diminished. A number of papers have sought to quantify the rebound effect, but the results have varied substantially. A key concern with this literature is that it is largely based on cross-sectional data sources, mak- ing it more difficult to control for the endogeneity of fuel economy. The purpose of this paper is to address these endogeneity concerns through the use of panel data techniques, drawing on data from the Panel Study of Income Dynamics (PSID). In contrast to prior studies using only cross-sectional data, we find the elasticity of vehicle miles traveled (VMT) with respect to both fuel economy and fuel price to be statistically significant. Our results show that a 1% increase in fuel prices or fuel economy (MPG) leads to a 0.41 to 0.67% increase in driving miles. We also examine heterogeneity of these elasticities across the income deciles. We find evidence that low income households are more responsive to changes in gasoline prices, but less sensitive to changes in fuel economy.