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Weather-Based Crop Insurance Contracts for African Countries

Author

Listed:
  • Karuaihe, Raphael N.
  • Wang, H. Holly
  • Young, Douglas L.

Abstract

Weather constitutes the major source for production risk in agriculture. Weather index can be used construct crop insurance that demand less information and can avoid moral hazard and adverse selection problems. Based on mean-variance model, theoretical results on the optimal insurance coverage and its impact from risk preference, basis risk, and premium loading are derived, which are quite consistent to the empirical results from the expected utility model. Using South Africa corn data, we investigate growers' demand and efficiency of alternative hypothetical weather index crop insurance programs. In contrast to previous work that suggests that a single-variable weather index suffices to develop an insurance contract, this study shows that the insured grower achieves a higher utility from multivariate weather indices. The most important single weather index we found in the study area was GDD, and the combination of rainfall and either temperature or GDD outperformed the single variable indices by a large margin. Depending on the growers risk preference, s/he may choose to buy o r offer such insurance for sale if the price is not actuarially fair. The risk protection value of weather-indexed-insurance follows the predictive power of the index on yield in general, though not exactly.

Suggested Citation

  • Karuaihe, Raphael N. & Wang, H. Holly & Young, Douglas L., 2006. "Weather-Based Crop Insurance Contracts for African Countries," 2006 Annual Meeting, August 12-18, 2006, Queensland, Australia 25378, International Association of Agricultural Economists.
  • Handle: RePEc:ags:iaae06:25378
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    File URL: http://purl.umn.edu/25378
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    Cited by:

    1. Heidelbach, Olaf, 2007. "Efficiency of selected risk management instruments: An empirical analysis of risk reduction in Kazakhstani crop production," Studies on the Agricultural and Food Sector in Transition Economies, Leibniz Institute of Agricultural Development in Transition Economies (IAMO), volume 40, number 92323.
    2. World Bank, 2012. "Disaster Risk Financing and Insurance in Sub-Saharan Africa," World Bank Other Operational Studies 26769, The World Bank.
    3. Bokusheva, Raushan & Breustedt, Gunnar & Heidelbach, Olaf, 2007. "Ex-ante evaluation of weather-based index insurance and area-yield insurance for reducing crop yield risk," 101st Seminar, July 5-6, 2007, Berlin Germany 9250, European Association of Agricultural Economists.
    4. Gunnar Breustedt & Raushan Bokusheva & Olaf Heidelbach, 2008. "Evaluating the Potential of Index Insurance Schemes to Reduce Crop Yield Risk in an Arid Region," Journal of Agricultural Economics, Wiley Blackwell, vol. 59(2), pages 312-328, June.
    5. Sannikova, Marina & Bukusheva, Raushan, 2007. "Instruments Reducing Climatic Risk for Russian Agriculture," 101st Seminar, July 5-6, 2007, Berlin Germany 9271, European Association of Agricultural Economists.

    More about this item

    Keywords

    Risk and Uncertainty; C51; C61; G22; Q14;

    JEL classification:

    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
    • G22 - Financial Economics - - Financial Institutions and Services - - - Insurance; Insurance Companies; Actuarial Studies
    • Q14 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Agriculture - - - Agricultural Finance

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