Carbon-pricing programs

Using survey-based choice experiments, we assess demand for alternative state-level carbon cap-and-trade programs. Household willingness to pay (WTP) depends upon…changes in the numbers of carbon-intensive versus green jobs…and whether there will be additional regulations to limit non-global co-pollutant emissions from firms that buy permits. …[Our survey was fielded in a single state, but we] estimate a model suitable for out-of-sample forecasting of WTP in other regions nationally, where systematic heterogeneity is captured by …(1) predicted county-level climate-change attitudes from the Yale Climate Map project, and (2) county-level COVID-19 case rates in prior months [of 2021]…. For selected carbon cap-and-trade programs, we conduct ``benefits-function transfer’’ exercises that reveal…the county-population-weighted marginal size distribution of predicted WTP across the lower-48 U.S. states, along with selected maps conveying the spatial distributions of predicted WTP across these 3,107 counties. […]

Several universities have implemented, and numerous others are considering, internal carbon fee or pricing programs intended to reduce greenhouse gas emissions, finance carbon reduction programs, signal sustainability and/or prepare for future mandatory carbon reductions. To learn about preferences over potential program designs, we employ survey-based choice experiments concerning potential internal carbon-pricing programs at a flagship public university. More than 1,000 stakeholders each consider several hypothetical programs which vary in their costs, emission reductions, the initial incidence of their costs, and uses of the resulting revenue. With corrections for systematic sample selection, we estimate a random-utility model with systematic preference heterogeneity which permits us to simulate, for different constituencies, the distribution of willingness to pay for different types of programs. Median individual willlingness-to-pay amounts predict the highest cost for any given program that would be approved in a campus referendum. Mean individual willingness-to-pay amounts can be used for benefit-cost assessments.

Stated preference researchers have previously demonstrated that a good’s placement among a sequence of goods in a set of valuation questions (i.e. proximal order effects) can have a substantial impact on people’s valuations of these different goods. However, the economic consequences of potential order effects stemming from other questions in a survey, prior to the valuation tasks, have received surprisingly little attention. Using an online climate change survey, we identify order effects created by prior attitude-elicitation questions, and we assess the potential impact of these distal order effects on willingness to pay (WTP) estimates for stylized climate change policies. We find that the order used in prior questions may change people’s opinions toward various attributes of the good to be valued, and thereby change WTP by a substantial amount. This paper emphasizes the significance of order effects stemming from preliminary survey questions, and supports a call for diligence in the random ordering of all potentially influential preliminary information in stated preference surveys to minimize inadvertent effects from any single arbitrary ordering.