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Inequities in Long-Term Housing Recovery After Disasters

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  • Walter Gillis Peacock
  • Shannon Van Zandt
  • Yang Zhang
  • Wesley E. Highfield

Abstract

Problem, research strategy, and findings: Disaster impacts result from interactions between hazard exposure, physical vulnerability, and social vulnerability. We report empirical work from 1992′s Hurricane Andrew in Miami-Dade (FL) and 2008′s Hurricane Ike in Galveston (TX) to assess long-term trends in housing recovery. Longitudinal, parcel-level data on housing units along with neighborhood sociodemographic data permit analysis of the pace of recovery for different neighborhoods, populations, and housing types. Housing recovery is highly uneven for different population groups. Unsurprisingly, damage has major consequences; even after four years, the effects of damage are evident in the rebuilding process. Social vulnerability factors play differently in different settings. In Miami, income and race and ethnicity were critical determinants of higher losses and slower recovery rates, while in Galveston income was the more critical factor, with housing in lower-income areas suffering more damage and lagging significantly in the recovery process. Takeaway for practice: Effective land use policy and building codes can reduce physical vulnerability and ultimately damage, thus enhancing resilience for all. Differentials in impact and recovery trajectories suggest that assessment and the monitoring of recovery is critical to target resources to areas that are lagging. Perhaps most important is having an effective plan in place that addresses housing recovery issues to help reduce long-term consequences. Pre-event planning for housing and social change can help support community vision and overcome inequities.

Suggested Citation

  • Walter Gillis Peacock & Shannon Van Zandt & Yang Zhang & Wesley E. Highfield, 2014. "Inequities in Long-Term Housing Recovery After Disasters," Journal of the American Planning Association, Taylor & Francis Journals, vol. 80(4), pages 356-371, October.
  • Handle: RePEc:taf:rjpaxx:v:80:y:2014:i:4:p:356-371
    DOI: 10.1080/01944363.2014.980440
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    1. Jeffrey M Wooldridge, 2010. "Econometric Analysis of Cross Section and Panel Data," MIT Press Books, The MIT Press, edition 2, volume 1, number 0262232588, April.
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    9. Cristina E. Muñoz & Eric Tate, 2016. "Unequal Recovery? Federal Resource Distribution after a Midwest Flood Disaster," IJERPH, MDPI, vol. 13(5), pages 1-17, May.
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    16. Ying Wang & Yingqi Zhu & Qi Sui, 2017. "Ethnic Groups Differences in Domestic Recovery after the Catastrophe: A Case Study of the 2008 Magnitude 7.9 Earthquake in China," IJERPH, MDPI, vol. 14(6), pages 1-13, June.
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    19. Qingfang Wang & Wei Kang, 2023. "Small businesses and government assistance during COVID-19: Evidence from the paycheck protection program in the U.S," Environment and Planning A, , vol. 55(8), pages 2147-2165, November.
    20. Cheng-Chun Lee & Mikel Maron & Ali Mostafavi, 2022. "Community-scale big data reveals disparate impacts of the Texas winter storm of 2021 and its managed power outage," Palgrave Communications, Palgrave Macmillan, vol. 9(1), pages 1-12, December.
    21. Leah A. Dundon & Janey S. Camp, 2021. "Climate justice and home-buyout programs: renters as a forgotten population in managed retreat actions," Journal of Environmental Studies and Sciences, Springer;Association of Environmental Studies and Sciences, vol. 11(3), pages 420-433, September.
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    23. Sahar Zavareh Hofmann, 2022. "Build Back Better and Long-Term Housing Recovery: Assessing Community Housing Resilience and the Role of Insurance Post Disaster," Sustainability, MDPI, vol. 14(9), pages 1-23, May.

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