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Assessing a pay-for-performance conservation program using an agent-based modeling framework
Citation:
Lee, E., Matthew Heberling, C. Nietch, AND A. Safwat. Assessing a pay-for-performance conservation program using an agent-based modeling framework. 2022 AAEA Annual Meeting, Anaheim, CA, July 31 - August 02, 2022.
Impact/Purpose:
The purpose of this paper is to compare the cost-effectiveness of pay-for-performance (PFP) to pay-for-practice to reduce nonpoint source pollution and consider farmers’ social interactions (networking) and transaction costs given a program budget constraint. An agent-based model is developed and linked to the soil and water assessment tool (hydrology model) in order to assess the changes in crop yield and water quality. Results show that PFP program has about 30% lower costs to reduce 1lb/acre total phosphorous compared to a pay-for-practice program. This research will be helpful to regional policymakers and agricultural extension agents to increase the effectiveness of cost-share programs.
Description:
Agricultural best management practices (BMPs) play an important role in reducing nonpoint source pollution. A variety of programs exist to encourage the use of BMPs, each with a specific set of objectives. For example, some pay-for-practice programs provide funds for specific BMPs without consideration of the baseline conditions of those requesting the support. A different approach, that adds flexibility into the farmer’s decision process, is called pay-for-performance (PFP). Unlike pay-for-practice, PFP uses baseline conditions of the fields and modeling to identify cost-effective scenarios for the farmers. Payment is based on the nutrient reduction, which allows farmers to choose the best set of BMPs for their situation rather than a specific practice that may or may not be best for reducing nutrients (Talberth et al. 2015). The purpose of this paper is to compare the cost-effectiveness of PFP to pay-for-practice and consider farmers’ social interactions (networking) and transaction costs to a new policy given a program budget constraint. An agent-based model (ABM) is developed and linked to the soil and water assessment tool (SWAT) in order to assess the changes in crop yield and water quality.
