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ISSN:2164-6376 (print)
ISSN:2164-6414 (online)
Discontinuity, Nonlinearity, and Complexity

Dimitry Volchenkov (editor), Dumitru Baleanu (editor)

Dimitry Volchenkov(editor)

Mathematics & Statistics, Texas Tech University, 1108 Memorial Circle, Lubbock, TX 79409, USA

Email: dr.volchenkov@gmail.com

Dumitru Baleanu (editor)

Cankaya University, Ankara, Turkey; Institute of Space Sciences, Magurele-Bucharest, Romania

Email: dumitru.baleanu@gmail.com

Demand Behaviour for Weather Index Insurance Products in Regions Prone to Agricultural Droughts

Discontinuity, Nonlinearity, and Complexity 10(4) (2021) 765--780 | DOI:10.5890/DNC.2021.12.015

Dmitry V. Kovalevsky , Maria Manez Costa

Climate Service Center Germany (GERICS), Helmholtz-Zentrum Hereon, Fischertwiete 1, 20095 Hamburg, Germany

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Abstract

Weather index insurance (WII) is a promising insurance scheme relevant for the agricultural sector, particularly in many low-income countries, including regions prone to agricultural droughts. WII policies might be more affordable to farmers, as the payouts in these insurance schemes are based on weather indices objectively determined for the specific agricultural regions, and therefore a costly individual loss assessment is not necessary. To successfully implement and scale up WII schemes, the development of transdisciplinary models properly addressing the complexity of relevant socio-natural processes and their interplay is necessary. We develop a stochastic model to simulate the demand for insurance policies in a drought-prone region under an assumption that weather and climate services, as tailored products for regions vulnerable to droughts, provide forecasts of the weather index on which the insurance scheme is based. Therefore, the simulated demand for the insurance policy might depend on the quality of the available weather index forecast. Presented modelling results suggest that both the income of individual producers and the dynamics of aggregate demand for insurance policies might be sensitive to the quality of the available weather index forecast. The developed modelling approaches can inform the design and implementation of WII schemes in drought-prone regions.

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