Camilo de los Ríos - Sanford School of Public Policy
Farmer's Preferences for Natrual Grasslands Conservation
Date: 09/26/2025 (Fri)
Time: 2:00pm- 3:00pm
Location: This seminar will be held both on-site and remotely. The on-site location will be: Sanford Rubenstien Hall 151. It will also be held remotely via Zoom. (Please sign in to see the link.)
Organizer: Alejandro and Xingchen
Meeting Schedule: (Not currently open for scheduling. Please contact the seminar organizer listed above.)
All meetings will be held in the same location as the seminar unless otherwise noted.
2:00pm - Seminar Presentation (2:00pm to 3:00pm)
Additional Comments: Stage: Post Data Collection Estimation-Writing Type of Feedback: Framing, other estimations? Abstract: Natural grasslands (NG) are vital ecosystems that provide carbon storage, biodiversity, soil health, and livestock fodder. In Uruguay, NG remain the dominant biome but now cover just over half of the territory, having declined by 15% in the past two decades due to agricultural intensification, afforestation, and non-native pastures. Because private returns from pasture improvement often exceed the perceived value of conservation, opportunity costs discourage sustainable management. Payments for Ecosystem Services (PES) can realign incentives. This paper contributes to designing PES schemes for NG conservation in Uruguay, and a long standing question on results or action based PES using a survey that integrates a Discrete Choice Experiment (DCE). This elicits farmer preferences for alternative contract designs and willingness to accept compensation. The DCE evaluates choices among contracts with ecological attributes—minimum pasture height, indicator plant species, and restrictions on fertilization and overseeding—selected as indicators of grassland quality and adjusted by soil type. We compare results-based and activity-based contracts, including hybrids, and test whether risk-averse farmers prefer activity-based schemes. Farmers also indicate the land area they would enroll, allowing estimation of both intensive and extensive margins.