Hostname: page-component-cd9895bd7-mkpzs Total loading time: 0 Render date: 2024-12-27T23:44:59.344Z Has data issue: false hasContentIssue false
  • English
  • Français

Does development reduce fatalities from natural disasters? New evidence for floods

Published online by Cambridge University Press:  28 August 2013

Susana Ferreira ,
Kirk Hamilton  and
Jeffrey R. Vincent
Susana Ferreira
Affiliation:
University of Georgia, 313 Conner Hall, Athens, GA 30602, USA. Phone: +1 706 542 0086. Fax: +1 706 542 0739. Email: [email protected]
Kirk Hamilton
Affiliation:
The World Bank, Washington, DC, USA. Email: [email protected]
Jeffrey R. Vincent
Affiliation:
Duke University, Durham, NC, USA. Email: [email protected]
Get access Rights & Permissions [Opens in a new window]

Abstract

We analyze the impact of development on flood fatalities using a new data set of 2,171 large floods in 92 countries between 1985 and 2008. Our results challenge the conventional wisdom that development results in fewer fatalities during natural disasters. Results indicating that higher income and better governance reduce fatalities during flood events do not hold up when unobserved country heterogeneity and within-country correlation of standard errors are taken into account. We find that income does have a significant, indirect effect on flood fatalities by affecting flood frequency and flood magnitude, but this effect is nonmonotonic, with net reductions in fatalities occurring only in lower income countries. We find little evidence that improved governance affects flood fatalities either directly or indirectly.

Type
Research Article
Information
Environment and Development Economics , Volume 18 , Issue 6 , December 2013 , pp. 649 - 679
Copyright
Copyright © Cambridge University Press 2013 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Anbarci, N., Escaleras, M., and Register, C.A. (2005), ‘Earthquake fatalities: the interaction of nature and political economy’, Journal of Public Economics 89(9–10): 1907–1933.CrossRefGoogle Scholar
Angrist, J.D. and Pischke, J.S. (2009), Mostly Harmless Econometrics: An Empiricist's Companion, Princeton and Oxford: Princeton University Press.CrossRefGoogle Scholar
Athey, S. and Stern, S. (2002), ‘The impact of information technology on emergency health care outcomes’, Rand Journal of Economics 33(3): 399–432.CrossRefGoogle ScholarPubMed
Bradshaw, C.J.A., Sodi, N.S., Peh, K.S.H., and Brook, B.W. (2007), ‘Global evidence that deforestation amplifies flood risk and severity in the developing world’, Global Change Biology 13: 2379–2395.Google Scholar
Burby, R.J. (2006), ‘Hurricane Katrina and the paradoxes of government disaster policy: bringing about wise governmental decisions for hazardous areas’, Annals of the American Academy of Political and Social Science 604: 171–191.CrossRefGoogle Scholar
Cameron, A.C. and Trivedi, P.K. (2009), Microeconometrics Using Stata (revised edn), College Station, TX: Stata Press.Google Scholar
Cavallo, E. and Noy, I. (2010), ‘The economics of natural disasters: a survey’, IDB WP Series No. IDB-WP-124, Inter-American Development Bank, Washington, DC.Google Scholar
Cavallo, E., Powell, A., and Becerra, O. (2010), ‘Estimating the direct economic damage of the earthquake in Haiti’, Economic Journal 120: 298–312.Google Scholar
CIESIN-CIAT (Center for International Earth Science Information Network-Centro Internacional de Agricultura Tropical) (2005), Gridded Population of the World Version 3 (GPWv3): Population Grids, Palisades, NY: Socioeconomic Data and Applications Center (SEDAC), Columbia University, [Available at] http://sedac.ciesin.columbia.edu/gpw.Google Scholar
Combs, D.L., Quenenmoen, L.E., and Parrish, R.G. (1998), ‘Assessing disaster attributable mortality: development and application of definition and classification matrix’, International Journal of Epidemiology 28: 1124–1129.Google Scholar
Criss, R.E. and Shock, E.L. (2001), ‘Flood enhancement through flood control’, Geology 29: 875–878.2.0.CO;2>CrossRefGoogle Scholar
DFO (Dartmouth Flood Observatory) (2010), Website, [Available at] http://floodobservatory.colorado.edu.Google Scholar
Escaleras, M., Anbarci, N., and Register, C.A. (2007), ‘Public sector corruption and major earthquakes: a potentially deadly interaction’, Public Choice 132: 209–230.Google Scholar
FAO (2001), ‘Global Forest Resources Assessment 2000’, FAO Forestry Paper No. 140, FAO, Rome.Google Scholar
FAO (2006), ‘Global Forest Resources Assessment 2005’, FAO Forestry Paper No. 147, FAO, Rome.Google Scholar
FAO (2007), State of the World's Forests 2007, Rome: FAO.Google Scholar
FAO and CIFOR (2005), ‘Forests and floods: drowning in fiction or thriving on facts?’, RAP Publication 2005/03 Forest Perspectives 2, CIFOR and FAO Regional Office for Asia and the Pacific Bogor, Indonesia.Google Scholar
Ferreira, S. and Ghimire, R. (2012), ‘Forest cover, socioeconomics, and reported flood frequency in developing countries’, Water Resources Research 48, W08529; doi:10.1029/2011WR011701.CrossRefGoogle Scholar
Ferreira, S. and Vincent, J.R. (2010), ‘Governance and timber harvests’, Environmental and Resource Economics 47: 241–260.Google Scholar
Freeman, P.K., Keen, M., and Mani, M. (2003), ‘Dealing with increased risk of natural disasters: challenges and options’, IMF Working Paper No. WP/03/197, Washington, DC: IMF.CrossRefGoogle Scholar
Greene, W.H. (2006), Econometric Analysis, 6th edn, New York: Prentice Hall.Google Scholar
Guimarães, P. (2008), ‘The fixed effects negative binomial model revisited’, Economics Letters 99(1): 63–66.CrossRefGoogle Scholar
Healy, A. and Malhotra, N. (2009), ‘Myopic voters and natural disaster policy’, American Political Science Review 103: 387–406.Google Scholar
Heckman, J.J. (1976), ‘The common structure of statistical models of truncation, sample selection and limited dependent variables and a simple estimator for such models’, Annals of Economic and Social Measurement 5: 475–492.Google Scholar
Hilbe, J.M. (2012), Negative Binomial Regression, 2nd ednCambridge: Cambridge University Press.Google Scholar
IPCC (Intergovernmental Panel on Climate Change) (2007), Impacts, Adaptation and Vulnerability, Cambridge: Cambridge University Press.Google Scholar
Johnston, M. (2001), ‘Measuring corruption: numbers versus knowledge versus understanding’, in Jain, A.K. (ed.), The Political Economy of Corruption, London and New York: Routledge, pp. 157–179.Google Scholar
Jonkman, S.N. (2005), ‘Global perspectives on loss of human life caused by floods’, Natural Hazards 34: 151–175.Google Scholar
Jonkman, S.N. and Kelman, I. (2005), ‘An analysis of the causes and circumstances of flood disaster deaths’, Disasters 29: 75–97.Google Scholar
Kahn, M.E. (2005), ‘The death toll from natural disasters: the role of income, geography, and institutions’, Review of Economics and Statistics 87(2): 271–284.Google Scholar
Kaufmann, D., Kraay, A., and Zoido-Lobaton, P. (1999), ‘Aggregating governance indicators’, Policy Research Working Paper No. 2195, World Bank, Washington, DC.Google Scholar
Keefer, P., Neumayer, E., and Plümper, T. (2011), ‘Earthquake propensity and the politics of mortality prevention’, World Development 39(9): 1530–1541.Google Scholar
Kellenberg, D.K. and Mobarak, A.M. (2008), ‘Does rising income increase or decrease damage risk from natural disasters?’, Journal of Urban Economics 63: 788–802.Google Scholar
Knack, S. and Keefer, P. (1995), ‘Institutions and economic performance: cross-country tests using alternative institutional measures’, Economics and Politics 7: 207–227.Google Scholar
Mauro, P. (1995), ‘Corruption and growth’, Quarterly Journal of Economics 110: 681–712.Google Scholar
Mauro, P. (1997), ‘The effects of corruption on growth, investment, and government expenditure: a cross-country analysis’, in Kimberly, A.E. (ed.), Corruption and the Global Economy, Washington, DC: Institute for International Economics, pp. 83–108.Google Scholar
OFDA/CRED (Office of Foreign Disaster Assistance, USAID/Center for Research of the Epidemiology of Disasters) (2010), International Disaster Database (Data version: v12.07, 2010), Brussels: Universite Catholique de Louvain, [Available at] http://www.emdat.be.Google Scholar
Pinter, N. (2005), ‘One step forward, two steps back on U.S. floodplains’, Science 308: 207–208.Google Scholar
PRS Group (Political Risk Services) (2010), Website, [Available at] http://www.prsgroup.com/.Google Scholar
Raschky, P.A. (2008), ‘Institutions and the losses from natural disasters’, Natural Hazards Earth Systems Science 8: 627–634.CrossRefGoogle Scholar
Ravallion, M. (2008), ‘Evaluating anti-poverty programs’, in Schultz, T.P. and Strauss, J.A. (eds), Handbook of Development Economics, Amsterdam: Elsevier, Chapter 59.Google Scholar
Sheets, B. and Williams, J. (2001), Hurricane Watch: Forecasting the Deadliest Storms on Earth, New York: Vintage Books (Random House).Google Scholar
Toya, H. and Skidmore, M. (2007), ‘Economic development and the impacts of natural disasters’, Economics Letters 94(1): 20–25.Google Scholar
Tyndall Centre for Climate Change Research (TCCCR) (2011), Climate Data, Norwich: TCCCR, [Available at] http://www.cru.uea.ac.uk/cru/data/hrg/timm/cty/obs/TYN_CY_1_1.html.Google Scholar
Van Dijk, A.I.J.M., van Noordwijk, M., Calder, I.A., Bruijnzeel, S.L.A., Schellekens, J., and Chappell, N.A. (2009), ‘Forest–flood relation still tenuous – comment on “Global evidence that deforestation amplifies flood risk and severity in the developing world” by C.J.A. Bradshaw, N.S. Sodi, K.S.-H. Peh, and B.W. Brook’, Global Change Biology 15: 110–115.Google Scholar
WDI (2010), World Development Indicators, [Available at] http://databank worldbank.org/ddp/home.do.Google Scholar
Wheeler, D. (2010), ‘Quantifying vulnerability to climate change: implications for adaptation assistance’, Mimeo, Washington, DC: Center for Global Development.Google Scholar
White, G.F., with Brinkmann, W.A.R., Cochrane, H.C., and Ericksen, N.J. (1975), Flood Hazard in the United States: A Research Assessment, Boulder, CO: Institute of Behavioral Science, University of Colorado.Google Scholar
Wooldridge, J.M. (2002), Econometric Analysis of Cross-Section and Panel Data, Cambridge, MA: MIT Press.Google Scholar