Agricultural Insurance Premium Determination Model for Risk Mitigation Based on Rainfall Index: Systematic Literature Review

Astrid Sulistya Azahra (), Muhamad Deni Johansyah and Sukono
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Astrid Sulistya Azahra: Master Program in Mathematics, Faculty of Mathematics and Natural Sciences, Universitas Padjadjaran, Jatinangor 45363, Indonesia
Muhamad Deni Johansyah: Department of Mathematics, Faculty of Mathematics and Natural Sciences, Universitas Padjadjaran, Jatinangor 45363, Indonesia
Sukono: Department of Mathematics, Faculty of Mathematics and Natural Sciences, Universitas Padjadjaran, Jatinangor 45363, Indonesia

Risks, 2024, vol. 12, issue 12, 1-26

Abstract: Rainfall is significantly essential in the agricultural sector to increase productivity. However, rainfall instability serves as a potential source of risk, causing crop failure and negatively impacting the welfare of farmers. To mitigate this risk, rainfall index-based agricultural insurance offers financial protection to farmers. There is no information on how to set a reasonable premium in index-based agricultural insurance. Therefore, this research aimed to systematically explore a model for determining a rainfall index-based agricultural insurance premium, focusing on the methods used and their effectiveness in mitigating the risk of harvest failure in the agricultural sector. The Preferred Reporting Items for Systematic Review and Meta-Analysis (PRISMA) method and a bibliometric analysis were used to collect and analyze articles from Scopus, ScienceDirect, and Dimensions databases. The results showed that there were 15 articles on determining a rainfall index-based agricultural insurance premium, where 4 used the Black–Scholes method and 11 applied other main methods. Meanwhile, no articles applied the fractional Black–Scholes method in determining agricultural insurance premiums based on the rainfall index, providing new opportunities for further research. The results contributed to the development of a model for agricultural insurance premium determination that could generate more diverse and flexible premium estimates as a sustainable method to mitigate the risk of harvest failure. This research is expected to serve as a reference for developing rainfall index-based agricultural insurance in the future and contribute to the Government of the Agriculture Department’s policy formulation regarding insurance programs for farmers.

Keywords: agricultural; insurance; premium; risk; rainfall index; fractional Black–Scholes; systematic literature review (search for similar items in EconPapers)
JEL-codes: C G0 G1 G2 G3 K2 M2 M4 (search for similar items in EconPapers)
Date: 2024
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