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Business Return in New Orleans: Decision Making Amid Post-Katrina Uncertainty

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  • Nina S N Lam
  • Kelley Pace
  • Richard Campanella
  • James LeSage
  • Helbert Arenas

Abstract

Background: Empirical observations on how businesses respond after a major catastrophe are rare, especially for a catastrophe as great as Hurricane Katrina, which hit New Orleans, Louisiana on August 29, 2005. We analyzed repeated telephone surveys of New Orleans businesses conducted in December 2005, June 2006, and October 2007 to understand factors that influenced decisions to re-open amid post-disaster uncertainty. Methodology/Principal Findings: Businesses in the group of professional, scientific, and technical services reopened the fastest in the near term, but differences in the rate of reopening for businesses stratified by type became indistinguishable in the longer term (around two years later). A reopening rate of 65% was found for all businesses by October 2007. Discriminant analysis showed significant differences in responses reflecting their attitudes about important factors between businesses that reopened and those that did not. Businesses that remained closed at the time of our third survey (two years after Katrina) ranked levee protection as the top concern immediately after Katrina, but damage to their premises and financing became major concerns in subsequent months reflected in the later surveys. For businesses that had opened (at the time of our third survey), infrastructure protection including levee, utility, and communications were the main concerns mentioned in surveys up to the third survey, when the issue of crime became their top concern. Conclusions/Significance: These findings underscore the need to have public policy and emergency plans in place prior to the actual disaster, such as infrastructure protection, so that the policy can be applied in a timely manner before business decisions to return or close are made. Our survey results, which include responses from both open and closed businesses, overcome the “survivorship bias” problem and provide empirical observations that should be useful to improve micro-level spatial economic modeling of factors that influence business return decisions.

Suggested Citation

  • Nina S N Lam & Kelley Pace & Richard Campanella & James LeSage & Helbert Arenas, 2009. "Business Return in New Orleans: Decision Making Amid Post-Katrina Uncertainty," PLOS ONE, Public Library of Science, vol. 4(8), pages 1-10, August.
  • Handle: RePEc:plo:pone00:0006765
    DOI: 10.1371/journal.pone.0006765
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    References listed on IDEAS

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    1. Mark Skidmore & Hideki Toya, 2002. "Do Natural Disasters Promote Long-Run Growth?," Economic Inquiry, Western Economic Association International, vol. 40(4), pages 664-687, October.
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    Cited by:

    1. De Alwis, Diana, 2018. "Distributional impacts of disaster recovery: Sri Lankan households a decade after the 2004 Indian Ocean tsunami," Working Paper Series 20321, Victoria University of Wellington, School of Economics and Finance.
    2. Sandra Sydnor & Linda Niehm & Yoon Lee & Maria Marshall & Holly Schrank, 2017. "Analysis of post-disaster damage and disruptive impacts on the operating status of small businesses after Hurricane Katrina," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 85(3), pages 1637-1663, February.
    3. Michal Biron & Hilla Peretz & Keren Turgeman-Lupo, 2020. "Trait Optimism and Work from Home Adjustment in the COVID-19 Pandemic: Considering the Mediating Role of Situational Optimism and the Moderating Role of Cultural Optimism," Sustainability, MDPI, vol. 12(22), pages 1-21, November.
    4. Diana Alwis, 2020. "Distributional Impacts of Disaster Recovery: Sri Lankan Households a Decade after the 2004 Indian Ocean Tsunami," Economics of Disasters and Climate Change, Springer, vol. 4(1), pages 195-222, April.
    5. Fredrik Kopsch, 2015. "Winners, Losers and Optimal Re-location of a Mining Town: An Approach Using Alonso Bid-Rent Functions," European Planning Studies, Taylor & Francis Journals, vol. 23(12), pages 2483-2496, December.
    6. César Andrés Mendoza & Giulio Breglia & Benjamín Jara, 2020. "Regional labor markets after an earthquake. Short-term emergency reactions in a cross-country perspective. Cases from Chile, Ecuador, Italy [Regionale Arbeitsmärkte nach einem Erdbeben. Kurzfristig," Review of Regional Research: Jahrbuch für Regionalwissenschaft, Springer;Gesellschaft für Regionalforschung (GfR), vol. 40(2), pages 189-221, October.
    7. Maria I. Marshall & Holly L. Schrank, 2020. "Sink or Swim? Impacts of Management Strategies on Small Business Survival and Recovery," Sustainability, MDPI, vol. 12(15), pages 1-21, August.
    8. Shuang Zhu & R. Pace, 2012. "Distressed Properties: Valuation Bias and Accuracy," The Journal of Real Estate Finance and Economics, Springer, vol. 44(1), pages 153-166, January.
    9. Balaei, Behrooz & Noy, Ilan & Wilkinson, Suzanne & Potangaroa, Regan, 2021. "Economic factors affecting water supply resilience to disasters," Socio-Economic Planning Sciences, Elsevier, vol. 76(C).
    10. Nina S N Lam & Helbert Arenas & Kelley Pace & James LeSage & Richard Campanella, 2012. "Predictors of Business Return in New Orleans after Hurricane Katrina," PLOS ONE, Public Library of Science, vol. 7(10), pages 1-8, October.
    11. De Alwis, Diana, 2018. "Distributional impacts of disaster recovery: Sri Lankan households a decade after the 2004 Indian Ocean tsunami," Working Paper Series 6980, Victoria University of Wellington, School of Economics and Finance.

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