Targeting Payments for Ecosystem Services Given Ecological and Economic Objectives
Soh, Moonwon, S. Cho, C. Boyer, and B. C. English.  2018.  2018 Sputhern Agricultural Economics Association Annual Meeting, Jacksonville, FL, February 2-6 access at https://ageconsearch.umn.edu/record/266502/files/Manuscript_SAEA_1-14-2018.pdf.

Abstract:
The purpose of this research is to identify optimal spatial targets for payments for ecosystem services under the multiple objectives of maximizing cost efficiencies of ecological services and maximizing economic benefits, and analyzing the tradeoff between them. These objectives are taken as targeting criteria in our case study of the Central and Southern Appalachian Region of the United States using Multi-Objective Linear Programming as the optimization tool. We identify optimal county-level targets, with payment budgets optimally distributed among counties, under 27 combinations of nine weighting scenarios between the two objectives and three budget scenarios, and the resulting changes in forest carbon and economic benefits. Using this information, we develop three Pareto optimal frontiers between the two objectives to evaluate the tradeoff between the objectives for each assumed payment budget. Maps of the county-level payment budget distributions, given the objective weighting scenarios between the two objectives, provide evidence that the greater the weight assigned to maximizing forest carbon benefits relative to maximizing economic impacts, the more widespread the optimal budget is allocated among the counties. The concave shape of each Pareto optimal frontier provides evidence that (1) an increase in the weight assigned to economic impacts and a decrease in the weight assigned to forest carbon benefits increases economic impacts that requires a sacrifice of forest carbon benefits and vice versa, and (2) the increase in economic impacts is relatively higher than the sacrifice in forest carbon benefits when the initial weight assigned to economic impacts is relatively lower than the initial weight assigned to forest carbon benefits and vice versa. Because of the concavity of the Pareto optimal relationship, assigning greater weight to an objective, which is of minimal concern at the initial policy-making stage, makes sense if conservation agencies add that objective to a multiple-objective targeting framework. For example, assigning a positive weight to economic impacts yields higher economic impacts for a smaller sacrifice of forest carbon benefits when the initial optimal spatial target focuses on promoting cost-efficient forest carbon benefits without concern for providing positive economic impacts.