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
∗The authors would like to thank Francisco Alpizar, Ariana Salas, Tabare Capitan,and Priscilla Rigg-Aguilar for their substantial support in the data collection andformation of this article. The authors would like to acknowledge Jesse Hendersonand Tugba Kaya for their useful feedback during the manuscript review process.The authors would also like to acknowledge financial support from the LaarmanInternational Gift Fund and Environment for Development. Finally, it is importantto note this work is only possible because of the excellent records and transparencyof Fondo Nacional de Financiamiento Forestal (FONAFIFO).