The Effect of California’s Carbon Cap and Trade Program on Co-pollutants and Environmental Justice: Evidence from the Electricity Sector [PDF] (Submitted)
Carbon dioxide emissions are globally uniformly mixing pollutants, but the same industrial processes that produce carbon emissions typically also produce co-pollutants, such as NOx and SOx. Environmental Justice (EJ) advocates have expressed concern that California's cap-and-trade program may cause low-income and minority communities to experience greater exposures to these co-pollutants. I use emissions data from almost all power plants in the United States, and a variety of strategies for constructing counterfactual emissions for plants covered by the California program (including a semi-parametric matching estimator and a synthetic control design). None of these methods suggests that California's carbon cap-and-trade program has increased average co-pollutant emissions. If anything, average co-pollutant emissions may have decreased. From the EJ perspective, average co-pollutant emissions at plants located in low-income or minority communities covered by the program have not gone up relative to co-pollutant emissions at plants in similar communities outside of California.
Non-governmental entities such as businesses and a small number of U.S. universities have adopted voluntary internal carbon pricing to reduce greenhouse gas emissions, to finance carbon reduction programs, to signal sustainability and to prepare for future mandatory carbon reductions. Little is known, however, about individual preferences for the introduction of these programs, or how preferences for these programs vary across potential program designs. We conduct a stated preference survey in the form of an advisory referendum on potential internal carbon-pricing programs at a large public university. Roughly 1,000 individuals each consider unique sets of several hypothetical programs which vary in their costs, emission reductions, types of fees charged, and uses of revenue. We use these data to estimate a structural random-utility model to explain program preferences. This model permits us to infer, for different constituencies within the campus community, willingness to pay for internal carbon pricing programs that vary in their attributes. Our model is flexible enough to allow for benefit transfer exercises to campuses with populations that differ in their political attitudes, income levels and other characteristics. Individual administrative data on both respondents and non-respondents, plus permanent-address neighborhood data at the zip code level, allow us to adjust our estimates for systematic differences in response rates that may be correlated with willingness to pay.
Works in Progress
“Willingness to Pay for Co-Benefits and Distribution in Carbon Pricing: Evidence from a General Population Survey of Oregon” (With Trudy Ann Cameron)
“Assessing Support for University Internal Carbon Pricing Using Benefit Transfer” (With Trudy Ann Cameron)