title: Price-based vs. quantity-based environmental regulation under Knightian uncertainty: an info-gap robust satisficing perspective.
abstract: Conventional wisdom among environmental economists is that the relative slopes of the marginal social benefit and marginal social cost functions determine whether a price-based or quantity-based environmental regulation leads to higher expected social welfare. We revisit the choice between price-based vs. quantity-based environmental regulation under Knightian uncertainty; that is, when uncertainty cannot be modeled with known moments of probability distributions. Under these circumstances, the policy objective cannot be to maximize the expected net benefits of emissions control. Instead, we evaluate an emissions tax and an aggregate abatement standard in terms of maximizing the range of uncertainty under which the welfare loss from error in the estimates of the marginal benefits and costs of emissions control can be limited. The main result of our work is that the same criterion involving the relative slopes of the marginal benefit and cost functions determines whether price-based or quantity-based control is more robust to unstructured uncertainty. Hence, not only does the relative slopes criterion lead to the policy that maximizes the expected net benefits of control under structured uncertainty, it also leads to the policy that maximizes robustness to unstructured uncertainty.
authors.affiliation: Department of Resource Economics, University of Massachusetts-Amherst, 214 Stockbridge Hall, Amherst, MA 01003, USA. stranlund@resecon.umass.edu
authors.forename: John K
authors.initials: JK
authors.lastname: Stranlund
authors.forename: Yakov
authors.initials: Y
authors.lastname: Ben-Haim
mesh_terms: D003247:Conservation of Natural Resources / Q000191:economics* / Q000331:legislation & jurisprudence* / Q000379:methods; D003362:Cost-Benefit Analysis; D004777:Environment; D033161:Government Regulation; D006801:Humans; D008954:Models, Biological; D011640:Public Policy; D035501:Uncertainty