Probabilistic cost-benefit analysis of disaster risk management in a development context
被引:59
作者:
Kull, Daniel
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World Bank, Global Facil Disaster Reduct & Recovery, CH-1211 Geneva 20, SwitzerlandWorld Bank, Global Facil Disaster Reduct & Recovery, CH-1211 Geneva 20, Switzerland
Kull, Daniel
[1
]
Mechler, Reinhard
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机构:
Int Inst Appl Syst Anal, Laxenburg, Austria
Vienna Univ Econ & Business, Vienna, AustriaWorld Bank, Global Facil Disaster Reduct & Recovery, CH-1211 Geneva 20, Switzerland
Mechler, Reinhard
[2
,3
]
Hochrainer-Stigler, Stefan
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机构:
Int Inst Appl Syst Anal, Laxenburg, AustriaWorld Bank, Global Facil Disaster Reduct & Recovery, CH-1211 Geneva 20, Switzerland
Hochrainer-Stigler, Stefan
[2
]
机构:
[1] World Bank, Global Facil Disaster Reduct & Recovery, CH-1211 Geneva 20, Switzerland
Limited studies have shown that disaster risk management (DRM) can be cost-efficient in a development context. Cost-benefit analysis (CBA) is an evaluation tool to analyse economic efficiency. This research introduces quantitative, stochastic CBA frameworks and applies them in case studies of flood and drought risk reduction in India and Pakistan, while also incorporating projected climate change impacts. DRM interventions are shown to be economically efficient, with integrated approaches more cost-effective and robust than singular interventions. The paper highlights that CBA can be a useful tool if certain issues are considered properly, including: complexities in estimating risk; data dependency of results; negative effects of interventions; and distributional aspects. The design and process of CBA must take into account specific objectives, available information, resources, and the perceptions and needs of stakeholders as transparently as possible. Intervention design and uncertainties should be qualified through dialogue, indicating that process is as important as numerical results.
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页码:374 / 400
页数:27
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