Strategic Behavior and the Environment > Vol 9 > Issue 1-2

The Implications of Learning on Bidding Behavior in a Repeated First Price Conservation Auction with Targeting

Natasha James, Southern Research Station, USDA Forest Service, Research Triangle Park, USA, natasha.a.james@usda.gov , Liv Lundberg, RISE, Research Institutes of Sweden, Sweden, liv.lundberg@ri.se , Erin Sills, Department of Forestry and Environmental Resources, North Carolina State University, USA, sills@ncsu.edu
 
Suggested Citation
Natasha James, Liv Lundberg and Erin Sills (2021), "The Implications of Learning on Bidding Behavior in a Repeated First Price Conservation Auction with Targeting", Strategic Behavior and the Environment: Vol. 9: No. 1-2, pp 69-101. http://dx.doi.org/10.1561/102.00000101

Publication Date: 19 Jul 2021
© 2021 N. James et al.
 
Subjects
Environmental Economics
 
Keywords
JEL Codes: Q23D3D44
Tendersauction efficiencyforest conservationecosystem service marketslearningdistribution of participation
 

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In this article:
Introduction 
Repeated Auctions 
Model Description 
Results and Discussion 
Conclusion 
Appendix A: Landowner Initial Bidding Strategy 
Appendix B: Initial conditions for each time step, where time t0 = 2005 
References 

Abstract

Conservation auctions have been advocated as a way to increase the cost-effectiveness of payment for ecosystem services (PES) programs by reducing the informational rents captured by participating landowners. Most PES programs have continual or periodic (rather than one-time) enrollment. In repeated auctions, it is possible for participants to learn the winning bids from previous auctions and use this information to strategically set their bids, thereby capturing more informational rents. We develop an agent-based model, using data from Costa Rica's Pago de Servicios Ambientales (PSA) program, to examine how strategic behavior, specifically through learning about previous winning bids, affects program participation and cost-effectiveness. When learning and strategic behavior occur among landowner agents in the model, informational rents increase and environmental benefits captured per dollar decrease over time. However, we also show that the distribution of participation can be adjusted by targeting for social as well as environmental benefits.

DOI:10.1561/102.00000101