Nonlinear Incentives, Plan Design, and Flood Mitigation: The Case of the Federal Emergency Management Agency’s Community Rating System

A basic proposition of agency theory is that output-based performance incentives encourage greater effort. However, studies find that incentive schemes can distort effort if rewards for performance are discrete or nonlinear. The Federal Emergency Management Agency's (FEMA) Community Rating System (CRS) is a flood mitigation program with a nonlinear incentive design. Under this program, localities are incentivized to implement a mix of 18 flood mitigation activities. Each activity is performance scored, with accumulated scores corresponding to a percent discount on flood insurance premiums for residents that hold National Flood Insurance policies. Discounts range from 0 to 45 percent and increase discretely in increments of 5 percent. With multivariate statistical and Geographic Information Systems analytic techniques, we test whether observed changes in annual CRS scores for participating localities in Florida are explained by nonlinear incentives, adjusting for hydrologic conditions, flood disaster histories, socioeconomic and human capital controls that can plausibly account for local mitigation activity scores over time. Results indicate that local jurisdictions are discount-seeking, with mitigation efforts partially driven by the nonlinear incentive design of CRS program. We end with recommendations to improve the operation FEMA's flood mitigation program.