by roughly 15 percent as people withdrew funds to cope with the problems created by the event. It took at least three years to recover from the compounded problems of loan defaults, loan restructuring, and savings and member deposit withdrawals. ENSO insurance was presented to the Peruvian insurance
regulators as a form of business-interruption insurance designed to pay for consequential losses and extra costs linked to extreme flooding, which is highly correlated with ENSO. ENSO insurance fits well in a class of insurance called “contingency insurance.” Contingency insurance is intended to protect policyholders against a variety of consequences associated with a specific event; these consequences can include loss of assets, losses in normal business revenues, and increased costs associated with addressing the event. Experience in Peru suggests that formulating index insurance as contingency insurance against a natural disaster has potential applications in many regions of the world highly exposed to severe weather risks such as drought or flood. The ENSO insurance uses the monthly sea surface temperature for ENSO Region 1.2 (0–10° South, 80–90° West), measured and reported by the NOAA Climate Prediction Center. The basis for payment is the average of two months—November and December. Three contracts are available with three different thresholds where payments begin (23.4, 24.0, and 24.5 degrees Celsius); each of these contracts reaches a maximum when the measure reaches 27 degrees. The payout function is linear. Indemnity payments are made in early January, just as flooding begins, and flooding continues from February to April. Indemnity payments are made by multiplying the payout rate times the sum insured, which is selected by the insured party. A risk assessment that estimates the largest losses that may occur under the worst flooding event is likely the best starting point for selecting a sum to be insured. Prudent buyers of insurance will be more likely to select a value that is less than these estimates, given the expense of this type of insurance and the fact that they have other risk-management mechanisms that can be blended with the ENSO insurance in an optimal fashion. Since the ENSO insurance pays before the catastrophe,
educational efforts have focused on helping people in the target markets understand how to use the extra cash to mitigate the impending crisis. Farmers’ associations in remote regions of Piura have expressed an interest in using the funds to clear drainage systems because heavy rains associated with ENSO increase the likelihood that
drainage systems will clog. Lenders are interested in using payments to ease the liquidity crisis and associated cost. Those in the value chain are interested in smoothing their losses and maintaining their specialized workforce when revenues are temporarily low because of El Niño. Finally, ENSO insurance is also being offered to local and regional governments to provide ready cash to mitigate some problems associated with catastrophic flooding. To begin, the insurance company is offering ENSO insurance only to highly exposed risk aggregators. Demand from other firms and institutions that are exposed to El Niño risk will then drive the expansion of this market. Anecdotal evidence points to substantial interest in ENSO insurance. After some initial press releases on the product, the insurer was inundated with calls from a variety of firms and institutions interested in the product. At this stage, ENSO insurance is not being made available to smallholder households. The product can, however, be tied to other financial services in a fashion that gives smallholders greater access to these services at better prices.
Conclusion
El Niño events affect many regions of the world. The most dramatic effects probably occur in Peru and Ecuador, but El Niño affects other countries in South, Central, and North America as well as in Southeast Asia and East Africa. In some regions, El Niño is associated with flooding, and in others it is associated with drought. Although no other region may have as strong a correlation between sea surface temperature and flooding as northern Peru and southern Ecuador, this project may increase awareness and lead to new thinking and opportunities regarding the potential for forecast index insurance and the relationship between natural disaster risk and oceanic oscillations such as ENSO. n
For further reading: J. R. Skees, J. Hartell, and A. Murphy, “Using Index-based Risk Transfer Products to Facilitate Micro Lending in Peru and Vietnam,” American Journal of Agricultural Economics 89 (2007): 1255–61; J. R. Skees, “Chal- lenges for Use of Index-based Weather Insurance in Lower- Income Countries,” Agricultural Finance Review 68 (Spring 2008): 197–217; J. R. Skees and B. J. Barnett, “Enhancing Micro Finance Using Index-based Risk Transfer Products,” Agricultural Finance Review 66 (2006): 235–50.
Jerry R. Skees (
jskees@uky.edu) is president of GlobalAgRisk and the H. B. Price professor of policy and risk in the Department of Agricultural Economics at the University of Kentucky.Benjamin Collier (
benjamin@globalagrisk.com) is an employee of GlobalAgRisk and a PhD candidate in the Department of Agricultural Economics at the University of Kentucky.
INTERNATIONAL FOOD POLICY
RESEARCH INSTITUTE Supported by the CGIAR
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www.worldbank.org Copyright © 2010 International Food Policy Research Institute and the World Bank. All rights reserved. Contact
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