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Disaster risk insurance and catastrophe models in risk‐prone small Caribbean islands
Author(s) -
Joyette Antonio R.T.,
Nurse Leonard A.,
Pulwarty Roger S.
Publication year - 2015
Publication title -
disasters
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.744
H-Index - 70
eISSN - 1467-7717
pISSN - 0361-3666
DOI - 10.1111/disa.12118
Subject(s) - gross domestic product , natural hazard , government (linguistics) , product (mathematics) , socioeconomic status , hazard , business , risk pool , poison control , caribbean region , market liquidity , development economics , small island developing states , natural disaster , economics , actuarial science , economic growth , finance , geography , insurance policy , casualty insurance , medicine , political science , latin americans , environmental health , population , philosophy , linguistics , chemistry , organic chemistry , meteorology , law , ecology , biology , climate change , mathematics , geometry
Post‐catastrophe recovery and financial liquidity have long challenged small Caribbean islands. These states are vulnerable to multifarious natural hazards that often cause considerable socioeconomic dislocation. Such events inflict heavy losses on businesses and households, and significantly disrupt all aspects of government operations. After Hurricane Ivan devastated the economies of some islands in September 2004—with estimated losses of as much as 200 per cent of gross domestic product in some cases—regional governments, aided by the World Bank and international donors, approved the creation of a regional catastrophe insurance scheme. This parametric‐based mechanism is underpinned by derivatives‐based catastrophe modelling whose outputs determine policy triggers and pay outs. Hazard models, particularly catastrophe models, are not widely accepted as yet. Despite recent advancements, major concerns have rendered them peripheral tools for many establishments. This paper reviews the region's vulnerabilities and examines constraints on the application of these models and suggests a means of improving their efficacy and acceptability.