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Assessing socioeconomic resilience to floods in 90 countries

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  • Hallegatte,Stephane
  • Bangalore,Mook
  • Vogt-Schilb,Adrien Camille

Abstract

This paper presents a model to assess the socioeconomic resilience to natural disasters of an economy, defined as its capacity to mitigate the impact of disaster-related asset losses on welfare, and a tool to help decision makers identify the most promising policy options to reduce welfare losses due to floods. Calibrated with household surveys, the model suggests that welfare losses from the July 2005 floods in Mumbai were almost double the asset losses, because losses were concentrated on poor and vulnerable populations. Applied to river floods in 90 countries, the model provides estimates of country-level socioeconomic resilience. Because floods disproportionally affect poor people, each $1 of global flood asset loss is equivalent to a $1.6 reduction in the affected country's national income, on average. The model also assesses and ranks policy levers to reduce flood losses in each country. It shows that considering asset losses is insufficient to assess disaster risk management policies. The same reduction in asset losses results in different welfare gains depending on who benefits. And some policies, such as adaptive social protection, do not reduce asset losses, but still reduce welfare losses. Asset and welfare losses can even move in opposite directions: increasing by one percentage point the share of income of the bottom 20 percent in the 90 countries would increase asset losses by 0.6 percent, since more wealth would be at risk. But it would also reduce the impact of income losses on wellbeing, and ultimately reduce welfare losses by 3.4 percent.

Suggested Citation

  • Hallegatte,Stephane & Bangalore,Mook & Vogt-Schilb,Adrien Camille, 2016. "Assessing socioeconomic resilience to floods in 90 countries," Policy Research Working Paper Series 7663, The World Bank.
  • Handle: RePEc:wbk:wbrwps:7663
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    File URL: http://documents.worldbank.org/curated/en/387821467309551281/pdf/WPS7663.pdf
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    Cited by:

    1. Ilan Noy & Nguyen Doan & Benno Ferrarini & Donghyun Park, 2020. "Measuring the Economic Risk of COVID‐19," Global Policy, London School of Economics and Political Science, vol. 11(4), pages 413-423, September.
    2. Rio Yonson, 2018. "Floods and Pestilence: Diseases in Philippine Urban Areas," Economics of Disasters and Climate Change, Springer, vol. 2(2), pages 107-135, July.
    3. Rio Yonson & Ilan Noy, 2018. "Measurement of Economic Welfare Risk and Resilience of the Philippine Regions," CESifo Working Paper Series 6953, CESifo.
    4. Jafino,Bramka Arga & Walsh,Brian James & Rozenberg,Julie & Hallegatte,Stephane, 2020. "Revised Estimates of the Impact of Climate Change on Extreme Poverty by 2030," Policy Research Working Paper Series 9417, The World Bank.
    5. Daniel Osberghaus & Christina Demski, 2019. "The causal effect of flood experience on climate engagement: evidence from search requests for green electricity," Climatic Change, Springer, vol. 156(1), pages 191-207, September.
    6. Sándor Kovács & Mohammad Fazle Rabbi & Domicián Máté, 2021. "Global Food Security, Economic and Health Risk Assessment of the COVID-19 Epidemic," Mathematics, MDPI, vol. 9(19), pages 1-16, September.
    7. Chen Chen & Jessica Hellmann & Lea Berrang-Ford & Ian Noble & Patrick Regan, 2018. "A global assessment of adaptation investment from the perspectives of equity and efficiency," Mitigation and Adaptation Strategies for Global Change, Springer, vol. 23(1), pages 101-122, January.

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