Policy Diffusion in U.S. Hazard Mitigation Planning: An Intergovernmental Perspective

This dissertation contributes to the disaster resilience policy literature by examining the diffusion of hazard mitigation policy in the U.S. Using the three-paper model, it investigates the adoption of local hazard mitigation plans (LHMPs) from an intergovernmental perspective.

The first paper focuses on horizontal diffusion in hazard mitigation planning among local communities. Special attention is paid to the potential factors affecting the adoption of FEMA-approved LHMPs, Hazard Mitigation Grant Program (HMGP) projects and Pre-Disaster Program (PDM) projects at the county level. The Event History Analysis (EHA) Logit Model and Spatial Autocorrelation Models test the hypotheses corresponding to external factors such as the neighboring effects and internal factors, including disaster risks, neighborhood disadvantage and affluence, government capacity, local disaster resilience advocacy groups, and political support. The empirical results confirmed the significant influence of neighboring effects, indicating that counties are more likely to implement the same mitigation strategies if neighboring counties have done so. The results also revealed that disaster experience, government capacity, and strong democratic support significantly impact the likelihood of adopting LHMP and HMGP. Additionally, the results suggested that disadvantaged communities were more likely to adopt mitigation policies, while affluent communities were less likely to adopt such policies.

The second paper evaluates the effectiveness of the FEMA's Program Administration by State Pilot (PAS). By integrating the Propensity Score Matching (PSM) technique with the Difference-in-Differences (DID) analysis, the empirical evidence demonstrated a significant reduction in the approval times for both LHMP and HMGP in pilot states compared to non-pilot states, with an average reduction nearing 30%. This suggests that the PAS program has effectively streamlined administrative processes, thereby enhancing efficiency in disaster management within pilot states. The analysis also indicated that the impact of PAS on the actual funding received through HMGP was insignificant, suggesting that while administrative processes were expedited, the allocation of financial resources remained unaffected.

The third paper attempts to understand how local governments respond to top-down policy pressures in vertical diffusion by analyzing the text similarities of hazard mitigation strategies between state hazard mitigation plans and county LHMPs in Ohio using the word embedding technologies. The study employs the Word2Vec algorithm to assess the policy similarity between the hazard mitigation goals outlined in LHMPs and SHMPs. Building on this initial analysis, this research further uses the Beta Regression model to examine the textual similarities within LHMPs in Ohio, focusing on how the type of author - government versus private consultants, and the nature of the goals, whether action-based or hazard-based, affect these alignments. The regression analysis shows that LHMPs authored by government entities tend to exhibit higher textual similarity, reflecting the influence of standardized approaches driven by state and federal guidelines. This suggests a compliance-driven alignment in government-written plans. Conversely, LHMPs authored by private consultants display greater variability, suggesting that these plans are customized to the specific needs and risk assessments of local communities. Additionally, the regression results indicate that action-based and mixed-goal LHMPs are associated with higher textual similarity across counties.

To carry out the empirical analysis mentioned above, this dissertation builds a panel dataset for all counties from 2000 to 2020, which contains data on LHMPs, HMA projects, disaster risks, socioeconomic characteristics, regional economic and political indicators, etc.