David Greene (University of Tennessee, Knoxville), Anushah Hossain (University of California, Berkeley), Julia Hofmann (RTI International), Gloria Helfand (U.S. Environmental Protection Agency), Robert Beach (RTI International)
As standards for vehicle greenhouse gas emissions and fuel economy have become more stringent, concerns have arisen that the incorporation of fuel-saving technologies may entail tradeoffs with other vehicle attributes important to consumers such as safety, comfort, or performance. Assessing the effects of these tradeoffs on consumer welfare requires estimates of both the degree of the tradeoffs, and consumer willingness to pay (WTP) for the foregone benefits. This paper focuses on WTP estimates. We first conduct a detailed review and synthesis of literature that presents or can be used to calculate WTP for vehicle attributes. We identified 52 U.S.-focused papers published between 1995 and 2015 (with one exception) with sufficient data to calculate WTP values. We identify 146 individual characteristics valued by the literature, which we consolidate into the 15 general categories of comfort, fuel availability, fuel costs, fuel type, incentives, model availability, non-fuel operating costs, performance, pollution, prestige, range, reliability, safety, size, and vehicle type. We next calculate WTP values for those characteristics based on the coefficients and data reported in the papers. In addition to mean WTP estimates, we present uncertainty estimates around each WTP value, based either on standard errors of the estimated coefficients or the standard deviations in random coefficient models. Our findings suggest large variation in WTP values for vehicle characteristics, both within and across studies. We further analyze factors that may contribute to this large variation via analysis of variance (ANOVA) and meta-analysis of the fuel economy and acceleration WTP values. This variation results in part because of methodological choices involved in estimating how attributes affect consumer vehicle choices, such as the kind of data used, the choice of statistical method, or whether instruments are used in the regressions. Nevertheless, most of the variation in results remains unexplained. These results have implications not only for the use of WTP estimates in policy analysis, but also for assessing the validity of vehicle demand models.