Association for Public Policy Analysis & Management

As we increasingly consider adaptation as a central strategy for addressing climate change, recovery emerges as an important dimension that is often the focus of public policy. The progression of climate change will cause an increase in disaster scale and magnitude, so it is important to understand how we can not only prevent impacts, but also recover from them. Recovery can be very non-uniform; communities struck by similar damages may have very different outcomes. As a result, it is important to identify the factors that make the recovery process more efficient and effective for some communities than for others.

This project considers the impact of socio-economic status on post-hurricane recovery at the regional level, using power restoration as a metric by which to better understand short-term recovery of a specific infrastructure system on a relatively broad spatial scale. Although the restoration process is, to an extent, standardized so as to maximize efficiency and restore power to vital services as quickly as possible, this research hypothesizes that there is a level of subjectivity inherent to the decision making process that guides power restoration efforts. This could cause deviations in recovery outcomes along socio-economic lines.

The relationship between power restoration time and socio-economic inequality is examined using a cross-sectional analysis that compares the duration and nature of recovery processes at the zip code level following Hurricane Matthew in the southeastern United States. The primary data used for this analysis is outage data that was scraped from utility websites in real time after the storm. The analysis uses income, employment and demographic data to capture the socio-economic characteristics of the areas under study, and hazard and spatial variables are included to control for other characteristics that are expected to impact the restoration process.

The literature suggests that there is a general relationship between socio-economics and disaster recovery wherein wealthier individuals recovery more quickly (Aldrich, 2012; Elliott et al., 2010). Although this relationship has not been previously tested in the specific context of infrastructure-level power restoration, I nonetheless hypothesize that communities with higher levels of socio-economic vulnerability will recover from shocks more slowly than their less vulnerable counterparts. This will manifest through slower power restoration times. Preliminary results support the hypothesized relationship between income and recovery.

There is currently very little acknowledgment in the literature of the possibility that power restoration could be influenced by considerations other than the prioritization of vital services, the extent of the damage, and the goal of restoring power to the most households as quickly as possible. Therefore, positive results from this study would be of great relevance to policy makers and utilities alike. Further, by establishing power restoration as a valid proxy for short-term infrastructural recovery, this research will set the groundwork for future studies of this nature.