Measuring social equity in flood recovery funding

Abstract

Deconstructing causal linkages between place attributes and disaster outcomes at coarse scales like zip codes and counties is difficult because heterogeneous socioeconomic characteristics operating at finer scales are masked. However, capturing detailed disaster outcomes about individuals and households for large areas can be equally complicated. This dichotomy highlights the need for a more nuanced and empirically-driven approach to understanding financial disaster recovery support. This study assessed how social characteristics influenced federal disaster recovery support following the 2015 South Carolina floods. Ordinary linear and spatial regression models provided a mechanism for pinpointing statistically significant links between individual/compound vulnerabilities and resource distribution from four federal disaster response and recovery programmes. The study makes two unique contributions. First, exploration of how social characteristics influence recovery support is a critical, yet understudied path toward fair and equitable disaster recovery. Second, finer scale inquiry across a large impact area is rare in quantitative case studies of US disasters. While we found flood recovery assistance to be strongly associated with physical damage overall the relationship was more tenuous in places with higher social vulnerability. Results indicate that future disaster recovery programs focusing on both physical damage and social vulnerable would lead to a more equitable disaster recoveries. Findings provide new understanding of equity at the intersection of social vulnerability, impacts, and disaster recovery and showcase both best-practices and areas for programme improvements for future disasters.

Methodological challenges to confirmatory latent variable models of social vulnerability

“…One approach is to normalize indicators that are in absolute scales in order to standardize their meaning across regions. While past studies have used Z -scores as an attempt to address this issue (Emrich et al 2020 ), Z -scores computed relative to the overall population still reflect regional heterogeneity. Future studies may consider the use of multilevel models, which would account for effects relative to the group mean (e.g., household income relative to others in Central Florida rather than the country overall).…”

“…Social vulnerability measures can tell us about differential recovery. SoVI and its input variables are highly utilized in emergency management (Tierney and Oliver-Smith 2012 ) and have proven useful in linking outcomes to underlying sociodemographic in several disaster specific case studies (Cutter and Finch 2008 ; Domingue and Emrich 2019 ; Emrich et al 2020 ), demonstrating how baseline conditions are influential across the emergency management cycle. From this perspective, we can identify interventions and pathways toward hazard mitigation by setting aside the theoretically wobbly ideal of a single vulnerability model—one that can be broadly applied to different types of disasters at different geographic scales—and instead focusing on the links between variables and outcomes.…”

Swimming alone? Why linking flood risk perception and behavior requires more than “it's the individual, stupid”

“…Such an approach encourages differing protection levels across society (Hartmann & Spit, 2015), and thereby result in unequal patterns of exposure and protection (Thaler et al, 2019). Different financial flood recovery schemes deal differently with issues of equity and justice, as recent studies from the USA and Europe illustrate (Emrich, Tate, Larson, & Zhou, 2019;Slavíková et al, 2019). Assuming individuals must take responsibility to protect themselves and increase their own resilience, there are likely to be significant downstream consequences with respect to the privatization of DRR (Kuhlicke, 2019).…”

Compound Risks of Hurricane Evacuation Amid the COVID‐19 Pandemic in the United States

“…Centuries of systemic racism in the United States have left Black, Native American, Latinx, and other non‐White people with both higher exposure to and fewer resources to cope with environmental or health‐related stressors compared with White populations (Bell & Ebisu, 2012; Singh et al, 2017). For example, recent research suggests that federal financial aid after disasters is not equitably distributed among communities and may even exacerbate income inequality (Emrich et al, 2020; Howell & Elliott, 2019). Low‐income communities and communities of color consequently struggle to prepare in advance of and recover in the wake of disasters (Baker, 2011; Cleetus et al, 2015).…”