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How Accurate are Disaster Loss Data? The Case of U.S. Flood Damage

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  • MARY DOWNTON

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  • ROGER PIELKE

    ()

Abstract

Policy makers need accurate disaster loss data for decisions about disaster assistance, policy evaluation, and scientific research priorities. But loss estimation is difficult in a disaster situation, and initial loss estimates are seldom evaluated in comparison with actual costs. This paper uses the example of historical flood damage data in the U.S. to evaluate disaster loss data. It evaluates the accuracy of historical flood damage estimates from two federal agencies. The U.S. National Weather Service (NWS) has compiled annual flood loss estimates for each state since 1955. Comparison of the NWS data with similar estimates from five state emergency management agencies reveals substantial disagreement between estimates from different sources. The Federal Emergency Management Agency (FEMA) began in the 1990s to systematically collect damage estimates and cost data associated with its disaster assistance programs. Comparison of early damage estimates with actual expenditures in a California flood disaster reveals large errors in some estimates for individual counties, but no statistically significant tendency to underestimate or overestimate. Positive and negative errors tend to average out and the total damage estimate for the state approximates the final expenditures. Both comparisons indicate that damage estimates for small events or local jurisdictions often are extremely inaccurate. On the other hand, estimates aggregated over large areas or long time periods appear to be reasonably reliable; that is, this study finds that independent estimates for events with losses greater than $500 million disagree by less than 40. The paper suggests ways of interpreting and using such loss estimates to reduce the likelihood of misinterpretation. Copyright Springer 2005

Suggested Citation

  • Mary Downton & Roger Pielke, 2005. "How Accurate are Disaster Loss Data? The Case of U.S. Flood Damage," 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. 35(2), pages 211-228, June.
  • Handle: RePEc:spr:nathaz:v:35:y:2005:i:2:p:211-228
    DOI: 10.1007/s11069-004-4808-4
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    References listed on IDEAS

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    1. Paulo Guimaraes & Frank L. Hefner & Douglas P. Woodward, 1993. "Wealth And Income Effects Of Natural Disasters: An Econometric Analysis Of Hurricane Hugo," The Review of Regional Studies, Southern Regional Science Association, vol. 23(2), pages 97-114, Fall.
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    Cited by:

    1. Adam Smith & Jessica Matthews, 2015. "Quantifying uncertainty and variable sensitivity within the US billion-dollar weather and climate disaster cost estimates," 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. 77(3), pages 1829-1851, July.
    2. repec:gam:jsusta:v:10:y:2018:i:9:p:3103-:d:166824 is not listed on IDEAS
    3. Silvio Schmidt & Claudia Kemfert & Peter Höppe, 2008. "Bereinigung sozioökonomischer Effekte bei Schäden tropischer Wirbelstürme für eine Analyse zum Einfluss des Klimawandels," Vierteljahrshefte zur Wirtschaftsforschung / Quarterly Journal of Economic Research, DIW Berlin, German Institute for Economic Research, vol. 77(4), pages 116-139.
    4. Stefano Balbi & Carlo Giupponi & Roland Olschewski & Vahid Mojtahed, 2013. "The economics of hydro-meteorological disasters: approaching the estimation of the total costs," Working Papers 2013-12, BC3.
    5. Bourdeau-Brien, Michael & Kryzanowski, Lawrence, 2017. "The impact of natural disasters on the stock returns and volatilities of local firms," The Quarterly Review of Economics and Finance, Elsevier, vol. 63(C), pages 259-270.
    6. Dapeng Huang & Renhe Zhang & Zhiguo Huo & Fei Mao & Youhao E & Wei Zheng, 2012. "An assessment of multidimensional flood vulnerability at the provincial scale in China based on the DEA method," 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. 64(2), pages 1575-1586, November.
    7. Balbi Stefano & Giupponi Carlo & Mojtahed Vahid & Olschewski Roland, 2015. "The Total Cost of Water-Related Disasters," Review of Economics, De Gruyter, vol. 66(2), pages 225-252, August.
    8. Vu Chau & Sue Cassells & John Holland, 2015. "Economic impact upon agricultural production from extreme flood events in Quang Nam, central Vietnam," 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. 75(2), pages 1747-1765, January.
    9. Ramón E. López & Vinod Thomas & Pablo Troncoso, 2015. "Climate Change and Natural Disasters," Working Papers wp414, University of Chile, Department of Economics.
    10. H. Apel & G. Aronica & H. Kreibich & A. Thieken, 2009. "Flood risk analyses—how detailed do we need to be?," 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. 49(1), pages 79-98, April.
    11. Brookhuis, B.J. & Hein, L.G., 2016. "The value of the flood control service of tropical forests: A case study for Trinidad," Forest Policy and Economics, Elsevier, vol. 62(C), pages 118-124.
    12. Agnes Soto, 2015. "Deriving information on disasters caused by natural hazards from limited data: a Guatemalan case study," 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. 75(1), pages 71-94, January.
    13. repec:eee:jeeman:v:92:y:2018:i:c:p:677-706 is not listed on IDEAS

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