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Global Assessment Report on Disaster Risk Reduction 2011
Revealing Risk, Redefining Development
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1.2 Extreme events or extreme risks?


Countries with weak governance are likely to find it difficult to address the underlying risk drivers. These include badly managed urban and regional development, the degradation of hazard-regulating ecosystems such as wetlands, mangroves and forests, and high levels of relative poverty. With some exceptions, these tend to be low- and lower-middle-income countries.

Extreme hazards and events are not synonymous with extreme risks. When similar numbers of people are affected by hazards of similar severity, wealthier and poorer countries generally experience radically different losses and impacts (UNISDR, 2009

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UNISDR (United Nations International Strategy for Disaster Reduction). 2009. Global assessment report on disaster risk reduction: Risk and poverty in a changing climate. Geneva, Switzerland: United Nations International Strategy for Disaster Reduction.
Click here to go to GAR09 page.
). GAR09 highlighted that poverty is both a cause and consequence of disaster risk. Across all the major hazards, poorer countries with weaker governance tend to experience far higher mortality and relative economic loss compared to wealthier countries with stronger governance. Mortality risk, for example, is approximately 225 times greater in low-income countries compared to OECD countries, when similar numbers of people are exposed to tropical cyclones of the same severity (Peduzzi et al., 2011

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Peduzzi, P., Chatenoux, B., Dao, H., De Bono, A., Herold, H., Kossin, J., Mouton, F. and Nordbeck, O. 2010. Global trends in human exposure, vulnerability and risk from tropical cyclones. JOURNAL (submitted).
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). Governance refers to the actions, processes, traditions and institutions by which authority is exercised and decisions are taken and implemented. Whereas relative wealth is a key determinant, governance factors such as the strength of democracy (Keefer et al., 2010

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Keefer, P., Neumayer, E. and Plumper, T. 2010. Earthquake propensity and the politics of mortality prevention. Policy Research Working Paper 4952. Washington DC, USA: The World Bank.
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), inequality (UNISDR, 2009

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UNISDR (United Nations International Strategy for Disaster Reduction). 2009. Global assessment report on disaster risk reduction: Risk and poverty in a changing climate. Geneva, Switzerland: United Nations International Strategy for Disaster Reduction.
Click here to go to GAR09 page.
) and voice and accountability (UNISDR, 2009

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UNISDR (United Nations International Strategy for Disaster Reduction). 2009. Global assessment report on disaster risk reduction: Risk and poverty in a changing climate. Geneva, Switzerland: United Nations International Strategy for Disaster Reduction.
Click here to go to GAR09 page.
), all play roles in the social construction of risk.

Box 1.4 Haiti, Chile and New Zealand, 2010

Extreme hazards are translated into risk through exposure and vulnerability, as tragically illustrated in all its dimensions by the earthquake that struck Haiti on 12 January 2010. The earthquake produced severe intensities of VII to IX on the Modified Mercalli scale, and mortality was very high, estimated at 222,517(UNOCHA, 2010

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UNOCHA (United Nations Office for the Coordination of Humanitarian Affairs). 2010. Haiti situation report 19. New York, USA: United Nations Office for the Coordination of Humanitarian Affairs.
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).1  This high death toll reflected the exposure of large numbers of people, and vulnerability factors such as extreme poverty, corruption, a fragile democracy, and a lack of earthquake experience in a country where they only occur infrequently (Keefer et al., 2010

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Keefer, P., Neumayer, E. and Plumper, T. 2010. Earthquake propensity and the politics of mortality prevention. Policy Research Working Paper 4952. Washington DC, USA: The World Bank.
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).

In contrast, the 27 February 2010 earthquake in Chile was by any standards an extreme event, releasing five hundred times more energy than the earthquake in Haiti the previous month. However, it only killed 486 people, a fraction of those who died in Haiti. In contrast to Haiti, exposure was lower, and Chile has a history of dealing with earthquakes. It is also an upper-middle-income country with a consolidated democracy and low levels of corruption.2 

The earthquake that hit Christchurch, New Zealand, on 3 September 2010 also produced intensities of up to IX on the Modified Mercalli scale. However, only some 500 buildings were destroyed and no lives were lost. While an estimated 154 people were killed in another earthquake on 22 February 2011 (New Zealand, 2011

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Government of New Zealand. 2011. Quake update 73. Auckland, New Zealand: Government of New Zealand.
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), the low casualty rate in both events reflects tough building regulations, strict enforcement, and experience in dealing with earthquakes.

Figure 1.4 Shakemap of Haiti Earthquake in 2010

Figure 1.4 Shakemap of Haiti Earthquake in 2010 Zoom
Source: UNEP/GRID-Europe 2010

The quality of a country’s governance appears to have a significant influence on the underlying drivers of risk. Drivers identified in GAR09 include badly planned and managed urban and regional development, the degradation of hazard-regulating ecosystems such as wetlands, mangroves and forests, and increasing poverty and inequality (UNISDR, 2009

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UNISDR (United Nations International Strategy for Disaster Reduction). 2009. Global assessment report on disaster risk reduction: Risk and poverty in a changing climate. Geneva, Switzerland: United Nations International Strategy for Disaster Reduction.
Click here to go to GAR09 page.
). These drivers interact through multiple feedback loops and together translate hazards into disaster risk.

Figure 1.5 presents a composite index that measures the quality of governance and how well countries are addressing these three underlying risk drivers. In other words, it indicates whether a country’s risk governance capacities and arrangements can effectively address underlying risk drivers. Countries with weak governance and that have great difficulty addressing underlying drivers are, with some exceptions, mostly low- and lower-middle-income countries. Those at the bottom of the index, such as Haiti, Chad or Afghanistan, are also experiencing conflict or political instability.



Figure 1.5 Risk governance capacity and World Bank country classification

Figure 1.5 Risk governance capacity and World Bank country classification
(Source: DARA, 2011

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DARA. 2011. Indice de reduccion del riesgo. Análisis de capacidades y condiciones para la reducción del riesgo de desastres. Madrid, Spain: DARA.
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; Lavell et al., 2010

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Lavell, C., Canteli, C., Rudiger, J. and Ruegenberg, D. 2010. Data spread sheets developed in support of the DARA 'risk reduction index: Conditions and capacities for risk reduction'. Geneva, Switzerland: UNISDR.
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; adapted by UNISDR).


This composite graph displays countries’ risk governance capacities and their relative wealth by World Bank income regions. Approximately 90 percent of the countries with the strongest capacities are high-income countries. On the other hand, low- and lower-middle income countries account for more than 95 percent of the quintile with the lowest capacities.

These rankings derive from an analysis of indicators of the disaster risk drivers identified in GAR09 (UNISDR, 2009

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UNISDR (United Nations International Strategy for Disaster Reduction). 2009. Global assessment report on disaster risk reduction: Risk and poverty in a changing climate. Geneva, Switzerland: United Nations International Strategy for Disaster Reduction.
Click here to go to GAR09 page.
), being poverty, weak urban and local governance, ecosystem degradation, and government effectiveness and accountability. Each quintile is then subdivided based on the number of countries per World Bank category within it.


Economic studies (Albala-Bertrand, 1993

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Albala-Bertrand, J.M. 1993. The political economy of large natural disasters: With special reference to developing countries. Oxford, UK: Clarendon Press.
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; Kahn, 2005

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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.
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; Noy, 2009

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Noy, I. 2009. The macroeconomic consequences of disasters. Journal of Development Economics 88 (2): 221–231.
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; Cavallo et al., 2010

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Cavallo, E., Galiani, S., Noy, I. and Pantano, J. 2010. Catastrophic natural disasters and economic growth. Department of Research and Chief Economist, IDB-WP-183. Washington DC: Inter American Development Bank.
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) provide conflicting evidence as to how and when disasters affect productivity, capital growth, employment, inequality and other macroeconomic parameters (GAR 11 paperMoreno and Cardona, 2011

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GAR11 Moreno, A. and Cardona, O.D. 2011. Efectos de los desastres naturales sobre el crecimiento, el desempleo, la inflación y la distribución del ingreso: Una evaluación de los casos de Colombia y México. Background Paper prepared for the 2011 Global Assessment Report on Disaster Risk Reduction. Geneva, Switzerland: UNISDR.

Click here to view this GAR paper.
). But some evidence indicates that poorer countries with weak governance have less capacity to absorb and recover from disaster loss, and less ability to prevent losses spilling over into other parts of the economy (Noy, 2009

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Noy, I. 2009. The macroeconomic consequences of disasters. Journal of Development Economics 88 (2): 221–231.
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). The penetration of catastrophe insurance in such countries is still incipient. There are a growing number of parametric crop insurance schemes for example (World Bank, 2009

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World Bank. 2009. Catastrophe risk financing in middle and low income countries: Review of the World Bank group products and services. Washington DC, USA: The World Bank.
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a), but these reach less than 5 percent of eligible households in India, and only 17 percent in Malawi (Cole et al., 2008

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Cole, S., Giné, X., Tobacman, J., Townsend, R., Topalova, P. and Vickery, J. 2008. Barriers to managing household risk: Evidence from India. Washington DC, USA: The World Bank.
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; Giné et al., 2008

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Giné, X., Townsend, R. and Vickery, J. 2008. Patterns of rainfall insurance participation in rural India. World Bank Economic Review 22 (3): 539.
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).

Within countries, different localities also have widely varying risk governance capacities. As Figure 1.6 shows, whereas Hurricane Mitch engulfed a large part of Central America in October 1998, most mortality in Honduras, the worst-affected country, was concentrated in a relatively small number of highly vulnerable and exposed municipalities. Following the hurricane, poorer households lost a greater proportion of their assets than wealthier households and had significantly more difficulty in recovering (Morris and Wodon, 2003

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Morris, S. and Wodon, Q. 2003. The allocation of natural disaster relief funds: Hurricane Mitch in Honduras. World Development 31 (7): 1279.
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; Carter et. al., 2006

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Carter, M., Little, P., Mogues, T. and Negat, W. 2006. Shocks, sensitivity and resilience: Tracking the economic impacts of environmental disaster on assets in Ethiopia and Honduras. Discussion Paper No. 32. Washington, DC, USA: International Food Policy Research Institute.
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).

Figure 1.6 Translating hurricane hazard into disaster risk: the impact of Hurricane Mitch in Honduras, 2008. Number of people killed

Figure 1.6 Translating hurricane hazard into disaster risk
(Sources: Image (NOAA, 1998

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NOAA (National Oceanic and Atmospheric Administration). 2003. NOAA gets U.S. consensus for el Niño/La niña index, definitions. Washington, DC, USA: National Oceanic and Atmospheric Administration.
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), Damage (COPECO, 1998

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COPECO (Comisión Permanente de Contingencias), La Red. 1998. Registros de Desastres y Perdidas en Honduras por el Huracán Mitch con la Comisión Permanente de Contingencias. Comayaguela, Honduras: Comisión Permanente de Contingencias. Available at www.desinventar.net..
), Hurricane path (USGS, 1998

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USGS (United States Geological Survey). 1998. Coral reefs in Honduras: Status after hurricane Mitch. Reston, VA, USA: United States Geological Survey.
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). Collage by UNISDR)



1 The real death toll may be much lower. Some commentators have cited 40,000–50,000 (Suárez et al., 2010

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Suárez, G., García Acosta, V. and Altez, R. 2010. Un desastre más allá del terremoto. Letras Libres 12 (135): 20–23.
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). Disaster mortality rates may be drastically over-reported, even by international organizations (UNISDR, 2009

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UNISDR (United Nations International Strategy for Disaster Reduction). 2009. Global assessment report on disaster risk reduction: Risk and poverty in a changing climate. Geneva, Switzerland: United Nations International Strategy for Disaster Reduction.
Click here to go to GAR09 page.
).
2 Chile had the lowest level of corruption in Latin America according to the 2009 Corruption Perceptions Index (CPI), and was ranked the 25th least corrupt country in the world (Transparency International, 2009

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Transparency International. 2009. Corruption Perceptions Index 2009. Berlin, Germany: Transparency International..
).

GAR 11 Background documents
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