Designing cost-effective incentives for farmers to engage in conservation is difficult, as farmers optimize their actions based on private, heterogeneous cost structures unknown to program designers. To support better program design, I build a principal-agent screening model that incorporates both farmers’ strategic behavior and the ecological and equity goals of program sponsors. I find that optimal contracts should balance upfront and outcome-based payments to simultaneously support liquidity and provide incentives. Upfront transfers should depend only on observable traits, while outcome-based payments should adjust for unobserved heterogeneity in costs and preferences. In addition to detailed analytical characterizations of the optimal contract, I also develop numerical frameworks to solve large-scale optimization for practical deployment and calibrate my model with field experiment data, demonstrating the validity and effectiveness of my insights, and enabling practitioners to easily access my incentive design methodology.

Many service systems manage demand uncertainty by combining capacity options that differ in cost and responsiveness. A common approach is to maintain a lower-cost base capacity that is committed to in advance and supplement it with more flexible but expensive surge capacity once demand information becomes available. A rich operations management literature has been devoted to studying such systems, under the assumption that the supply of base and surge capacity is non-strategic and exogenously given. However, in many real systems the supply is indeed strategic. In this paper, we bridge this gap by developing a model of capacity planning with strategic labor supply, in which workers endogenously choose between base employment, surge employment, and outside opportunities. We show that these labor market responses fundamentally reshape optimal staffing policies and the resulting balance between base and surge capacity.