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Leveraging optimal portfolio of Drought-Tolerant Maize Varieties for weather index insurance and food security

Author

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  • Sebastain Awondo

    (University of Alabama)

  • Genti Kostandini

    (University of Georgia)

Abstract

We investigate the impact of optimizing a portfolio of Drought-Tolerant Maize Varieties (DTMVs) to manage weather risk and its implications on the development of sustainable micro-insurance markets. We use high-resolution climate data and on-farm trial data, involving 20 DTMVs, over 49 locations spanning eight countries in Africa and 5 mega-environments. Markov chain and multivariate spatial Bayes models are employed to generate multivariate space-time rainfall and maize yield distributions, and derive optimal semi-variance portfolio of DTMVs. We find that optimal portfolios significantly outperformed naive portfolios, overall, reducing insurance premium rates by 31–55%.

Suggested Citation

  • Sebastain Awondo & Genti Kostandini, 2022. "Leveraging optimal portfolio of Drought-Tolerant Maize Varieties for weather index insurance and food security," The Geneva Risk and Insurance Review, Palgrave Macmillan;International Association for the Study of Insurance Economics (The Geneva Association), vol. 47(1), pages 45-65, March.
    • Handle: RePEc:pal:genrir:v:47:y:2022:i:1:d:10.1057_s10713-021-00065-4
    DOI: 10.1057/s10713-021-00065-4
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    More about this item

    Keywords

    Weather risk; Drought-tolerant maize; Portfolio optimization; Downside risk measures; Index insurance; Africa;
    All these keywords.

    JEL classification:

    • Q12 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Agriculture - - - Micro Analysis of Farm Firms, Farm Households, and Farm Input Markets
    • D80 - Microeconomics - - Information, Knowledge, and Uncertainty - - - General

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