Post‐Ike economic resilience along the Texas coast

Abstract

The economic devastation resulting from recent natural disasters has spawned intense interest in programmes that promote regional resilience. The economic impacts of Hurricane Ike (September 2008) endured long beyond the storm's landfall, compounded by a national recession. This study analyses the pattern of post-Ike industrial growth in eight coastal counties of Texas, United States, and identifies sources of resilience and potential drivers of recovery. The results indicate that post-disaster growth patterns differ from established growth patterns. Levels of resilience vary across industrial sectors, and service sectors tend to lead a recovery. The resilience of the hotel and restaurant sector, for instance, suggests that the presence of relief workers might immunise certain sectors against a post-disaster economic downturn. Besides the sectors that are generally resilient, each county has its own distinct sectors that, depending on the extent of the damage suffered, tend to perform strongly after a disaster, owing to the characteristics of the respective county's economy.

A quantitative method for measuring regional economic resilience to the great recession

“…Kahsai, Yu, Middleton, Schaeffer, and Jackson () create a county economic resilience index based on industrial diversity, entrepreneurial activity and business dynamics, human and social capital, scale and proximity, and physical capital. Lu and Dudensing () create also a county economic resilience index using changes in sales by industrial sector. An advantage of using an index of regional characteristics is that it captures the unique and complex nature of each region.…”

Business recovery: an assessment framework

“… to identify the characteristics, actions, or external assistance that enhance or hinder an organisation's ability to survive a disaster or to re‐establish viability in the aftermath of an event (see, for example, Dahlhamer and Tierney, , ; Alesch et al, ; Webb, Tierney, and Dahlhamer, ; Runyan, ; Graham, ; Green et al, ; Lam et al, ; Zhang, Lindell, and Prater, ; Corey and Deitch, ; Dietch and Corey, ; Pearson, Hickman, and Lawrence, ; de Mel, McKenzie, and Woodruff, 2012; Kachali et al, ; Orchiston, Vargo, and Seville, ; Neef, Panyakotkaew, and Elstner, ); to explore in‐depth, using case studies of businesses, the processes that shape the recovery outcomes of organisations (see, for example, Chang, ; Stewart, ; Stevenson et al, ); and to analyse businesses as part of the context influencing economic or community recovery (see, for example, Waugh and Smith, ; Liu and Plyer, ; Pearson, Hickman, and Lawrence, ; Xiao and Nilawar, ; Lu and Dudensing, ). …”

“…While there is a body of literature on the factors that influence organisational recovery (see, for example, Corey and Dietch, 2011;Schrank et al, 2013;Xiao and Peacock, 2014) researchers measure progress and outcomes using indicators and methods that are often difficult to compare across space and time. This is true both for businesses that experienced the same disaster (Lu and Dudensing, 2015) and those that experienced different disasters at different times and in different places (Bhattacharya-Mis and Lamond, 2014). In an evaluation of businesses in New Orleans, Louisiana, United States, for instance, LeSage et al (2011) used a large dataset amassed over several years to examine spatial interdependencies in recovery following Hurricane Katrina in August 2005.…”

Post-earthquake economic resilience and recovery efficiency in the border areas of the Tibetan Plateau: A case study of areas affected by the Wenchuan Ms 8.0 Earthquake in Sichuan, China in 2008

“…(2) With the concept of economic resilience, the econometric model and index system are used to evaluate the resilience of the post-disaster economy on the basis of discussing the growth model of the regional economy following the disaster (Zheng, 2008;Simmie and Martin, 2010;Rose and Krausmann, 2013). Moreover, effective strategies for improving the resilience of the post-disaster economy have been studied to reveal the long-term evolution trajectory of the economy in the disaster area (Rose and Lim, 2002;Rose and Liao, 2005;Lu and Dudensing, 2015). In addition, through empirical analysis of Hurricane Katrina in the USA in 2005 (Baade, 2007;Wu et al, 2013, the Wenchuan Earthquake in 2008(Wu et al, 2013, and the Great East Japan Earthquake and Tsunami in 2011 (Leelawat et al, 2015), the differences in post-disaster economic recovery of different types of industries and different regional development conditions are discussed.…”