Non-linear 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 non-linear. The Federal Emergency Management Agency's (FEMA) Community Rating System (CRS) is a flood mitigation programme with a non-linear incentive design. Under this programme, localities are incentivised 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% and increase discretely in increments of 5%. With multivariate statistical and Geographic Information Systems analytic techniques, tests are made to find whether observed changes in annual CRS scores for participating localities in Florida are explained by non-linear incentives, adjusting for hydrologic conditions, flood disaster histories, socio-economic 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 non-linear incentive design of the CRS programme. The paper ends with recommendations to improve the operation FEMA's flood mitigation programme.
Volume (Year): 53 (2010)
Issue (Month): 2 ()
|Contact details of provider:|| Web page: http://www.tandfonline.com/CJEP20|
|Order Information:||Web: http://www.tandfonline.com/pricing/journal/CJEP20|
When requesting a correction, please mention this item's handle: RePEc:taf:jenpmg:v:53:y:2010:i:2:p:219-239. See general information about how to correct material in RePEc.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Michael McNulty)
If references are entirely missing, you can add them using this form.