Community flood hazard mitigation and the Community Rating System of National Flood Insurance Program

This dissertation focuses on the Community Rating System (CRS) of the National Flood Insurance Program (NFIP), which credits local floodplain management activities and provides flood insurance premium discounts for households and businesses in a community. Programs like CRS seek to incent cooperation amongst federal, state, and local governments rather than impose top-down mandates that require particular mitigation approaches. By offering individual financial inducements for community-level flood hazard mitigation, CRS is an incentive-based, bottom-up cooperative approach to risk management that could address some of the shortcomings of other cooperative approaches to environmental management. Through an improved understanding of CRS, state governments and FEMA can better encourage participation in the CRS and similar programs in order to provide for better protection from natural hazards. It also allows for a better targeting of resources to improve hazard vulnerability.;This dissertation has three major chapters. Chapter 3, which is entitled "Participation in the Community Rating System of NFIP: An Empirical Analysis of North Carolina Counties", tests a number of hypotheses offered by previous researchers regarding factors that motivate local hazard management initiatives through an examination of patterns in CRS participation across all 100 North Carolina counties from 1991 to 2002. Specifically, we examine the influence of flood experience, hydrological risk, local capacity, and socioeconomic factors on county hazard mitigation decisions. Results indicate that flood history and physical risk factors increase likelihood of local hazard mitigation adoption. We find evidence that the probability of CRS participation is lower in counties with a greater proportion of senior citizens and greater level of education, and that flood hazard mitigation activities at the county level are more likely when a greater number of nested of municipalities participate in CRS.;Chapter 4, which is entitled "Evaluation of the Community Rating System of National Flood Insurance Program---An Application of Propensity Score Matching", develops innovative ways to assess the performance of the CRS. The true performance of CRS can be determined if one compares a meaningful outcome---like the average property damage during flooding events---for each CRS participant with their untreated selves during the same event. However, it is impossible to observe what would have happened to CRS participants in absence of their participating in the CRS (lack of counterfactual). The primary objective of chapter 4 is to use propensity score matching (PSM) methods to correct sample selection bias due to observable differences between the CRS participants and comparison groups. Although there is substantial variation in the results, the findings show that all of the effects are in the same direction, indicating CRS effectively reduces the average property damage due to flood hazard.;Chapter 5, which is entitled "Estimation of a Dynamic Model: Policy Learning in Hazard Mitigation", addresses the dynamic nature in flood hazard mitigation policy learning by examining the patterns in Community Rating System (CRS) scores across all 100 counties in North Carolina from 1995 to 2010, with controls of flood experience, hydrological risk factors, local capacity, and socioeconomic factors. It is important for local governments to maintain stability and transparency in planning and policy-making processes, so that agents and institutions can form reasonable expectations upon which to make development and investment decisions. As a result, the establishment of a new framework of hazard mitigation presents a considerable challenge, involving a change of momentum which requires commissioner meetings, public hearings, and ordinance revisions, all of which are costly. Therefore, we postulate that hazard mitigation policy evolution in response natural disasters can be described in terms of a dynamic mechanism. The dynamic panel model is characterized by the presence of a lagged dependent variable among the regressors, incorporating both dynamics and individual-specific effects. The result show that once local governments regulate their floodplains in ways that go beyond the minimum required by the NFIP, they tend to improve flood hazard mitigation incrementally despite changes in staff and shifts in local political regimes. (Abstract shortened by UMI.)...