Designing cost-efficient payments for forest-based carbon sequestration: An auction-based modeling approach

Abstract

Conservation auctions can reveal information about the opportunity costs of afforestation, which can be combined with the carbon sequestration benefits of land-use changes to design cost-efficient payment systems. Furthermore, the impact of integrating cost-benefit information to ensure efficiency gains or to ensure minimal efficiency losses in multi-round conservation auctions, where landowners learn to extract information rents, depends on the level of correlation between costs and benefits. Incorporating discriminatory-price auction theory, and an agent-based model, simulated data are used to examine the cost-efficiency of cost-ranked and cost-benefit-ranked auction-based payment designs for forest-based carbon storage for alternative levels of correlation between afforestation opportunity costs and carbon sequestration capacities in static and dynamic settings. Results show that the cost-benefit-ranked design is more cost-efficient than the cost-ranked design in a static setting even though the relative spatial heterogeneities of costs and benefits are identical. More importantly, the cost-efficiency of the cost-benefit-ranked design is generally robust to deterioration as bidders learn over repeated auction rounds, compared with the cost-ranked design, and more resistant to deterioration for some levels of correlation.