Borensztein, Eduardo, Eduardo Cavallo, and Patricio Valenzuela, 2008, “Debt Sustainability Under Catastrophic Risk: The Case for Government Budget Insurance,” IMF Working Paper WP/08/44 (Washington D.C.: International Monetary Fund).
EM-DAT, Emergency Events Database (http://www.emdat.be/).
International Monetary Fund, 2006, “Grenada—Request for Three-Year Arrangement Under the Poverty Reduction and Growth Facility,” Country Report No. 06/277, (Washington D.C.: International Monetary Fund).
Rasmussen, Tobias, 2006, “Natural Disasters and Their Macroeconomic Implications,” in Sahay, Robinson, and Cashin, eds., The Caribbean: From Vulnerability to Sustained Growth, (Washington: International Monetary Fund), pp. 122–42.
Sahay, Ratna, 2006, “Stabilization, Debt, and Fiscal Policy in the Caribbean,” in Sahay, Robinson, and Cashin, eds., The Caribbean: From Vulnerability to Sustained Growth, (Washington D.C.: International Monetary Fund), pp. 17–57.
World Bank, 2006, “Background Document—Initial Results of Preparation Work: Caribbean Catastrophic Risk Insurance Facility,” (Washington D.C.: World Bank).
World Bank, 2007, “Background Document—Results of Preparation Work on the Design of a Caribbean Catastrophic Risk Insurance Facility,” (Washington D.C.: World Bank).
Prepared by Yu Ching Wong, Anthony Lemus, and Nancy Wagner.
While the Caribbean countries are also exposed to earthquakes, this paper focuses on the example of hurricanes, as they represent the most frequent threat for these countries.
Antigua and Barbuda (ATG), Dominica (DMA), Grenada (GRD), St. Kitts and Nevis (KNA), St. Lucia (LCA), and St. Vincent and the Grenadines (VCT).
The return period is an estimate of the interval of time between given disaster events (such as a hurricane) of a certain intensity or size.
The estimates for the high probability event of 1-in-18-years are extrapolated from data points for the other return periods available from the World Bank (2006). The probable maximum loss estimated by EQECAT for Caribbean Catastrophe Risk Insurance Facility (CCRIF) countries includes estimated direct losses to government-owned assets caused by hurricanes, and estimated indirect losses due to lost tax revenue and disaster relief expenditures. Due to the lack of data such as property tax records and building code classifications, the exposure database is constructed based on field data and a series of assumptions. In this regard, the CCRIF recognizes the need to improve the exposure database in order to raise the quality of risk assessment. See also Box 1 on the CCRIF.
Historical data are from 1900 to 2005.
The stochastic shocks to each variable are assumed to follow a normal distribution with mean zero and standard deviation based on historical volatility from 1997 to 2013.
In the case of the CCRIF, disbursement of an insurance payout is contingent on pre-established trigger events measured in terms of wind speed (for hurricane) and ground shaking (for earthquake) thresholds. This allows the insurance payment to meet the liquidity gap immediately following the aftermath of a disaster, without the need for an on-site loss assessment, which is usually time-consuming and costly (see World Bank 2006, 2007).