2009 Reports

Designing Index-Based Weather Insurance for Farmers In Central America: Final Report to the World Bank Commodity Risk Management Group, ARD

Giannini, Alessandra; Hansen, James W.; Holthaus, Eric; Ines, Amor Valeriano M.; Kaheil, Yasir; Karnauskas, Kristopher B.; McLaurin, Megan; Osgood, Daniel E.; Robertson, Andrew W.; Shirley, Kenneth; Vicarelli, Marta

This report is one of the deliverables for the project "Commodity Risk Management Group (ARD) seeks a qualified firm for Designing Index-Based Weather Insurance Contracts For Farmers in Central America, Terms of Reference." In this report, we document the development of eleven revised and improved standardized drought contracts, including six contracts specified in the World Bank's Commodity Risk Management Group's Terms of Reference for this project. Contracts are developed for three locations in Nicaragua (Chinandega, Leon, and Managua) for rice, soy, and sorghum crops and three locations in Honduras (La Conce, Catacamas, and Guayabillas/Olancho) for sorghum, soy, and maize crops. We provide background on the contract structure and design methods used. The final standardized drought contracts perform very well in our statistical analysis using crop models, likely due to the strong potential represented by the initial contracts proposed by project partners. In this report we provide a detailed report and discussion of the contracts and the refinement process. Of course, it is important that project partners make sure to validate this performance through alternate sources of information, such as discussions with farmers, experts, and accurate historical yield data, when available. For the future, for standardization of the process, it could be worthwhile to make a more systematic process for quantitatively evaluating and tuning the contracts for additional risks (such as excess rainfall) based on farmer interviews and agronomic knowledge. Specifically we recommend evaluating each risk of the contract independently prior to bundling. We also recommend development of a process for documentation of farmer and expert interviews that would provide information on the risk, as well as a historical record of when each risk was an issue. More intimate inclusion of Reinsurers in the design process for standardized contracts, as well as development of guidelines for features that may lead to additional expense could help provide for fewer surprises in reinsurance pricing. We also recommend that the contracts for additional risks be structured and designed so that they can be adjusted to meet price, payout, and coverage constraints through systematic statistically-based tuning of a small number of parameters. In response to queries raised during the project by project partners we have deepened our study of the climate of Central America and its implications for the forecasts, we find that although there appears to be a strong link between the natural ENSO climate cycle and contract payouts, there is probably little scope for geographical hedging, as crops covered do not span the geographic regions with negatively correlated rainfall. It is likely that the best hedging strategy would be to include excess contracts in the drought portfolio. Also, we see little evidence for altering contracts or pricing to address potential long term precipitation trends in the near term. Given the strong potential for index insurance as a mechanism for adapting to climate risk, we highly recommend that products and prices be regularly updated over the years, with care to ensure the value and product continuity with each change. In response to queries raised during the project by project partners, we perform an in depth illustration and analysis of the use of rainfall simulators on the contracts. We illustrate the limitations of rainfall simulators as well as their potential for improving contract design and pricing for areas with short datasets, developing rainfall simulator for the analysis. Certain features of some contracts (the shifting sowing window) led a wide range of rainfall simulators to under-represent variability. Often, subtle contract features can lead to a lack of robustness to sensitivity tests and difficulty in analysis, and potentially could lead to increased reinsurance pricing without substantially adding to the quality of the coverage. We have noticed that the bulk of the protection of many of the contracts could be provided through much simpler indices that are much more robust to sensitivity tests and perform much more predictably on rainfall simulators when practically implementable. It may be that an additional stage of index design might be very valuable following the development of a sophisticated contract. This additional stage would be to determine if the bulk of the coverage of the contract could be duplicated in a simplified statistical approximation of the contract.