Four Parameter Beta Generalized Mixed Effect Tree and Random Forest for Area Yield Crop Insurance

Dian Kusumaningrum (), Hari Wijayanto (), Anang Kurnia, Khairil Anwar Notodiputro and Muhlis Ardiansyah
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Dian Kusumaningrum: Prasetiya Mulya University, Business Mathematics Program Study
Hari Wijayanto: IPB University, Program on Statistics and Data Science - School of Data Science, Mathematics, and Informatics
Anang Kurnia: IPB University, Program on Statistics and Data Science - School of Data Science, Mathematics, and Informatics
Khairil Anwar Notodiputro: IPB University, Program on Statistics and Data Science - School of Data Science, Mathematics, and Informatics
Muhlis Ardiansyah: IPB University, Program on Statistics and Data Science - School of Data Science, Mathematics, and Informatics

A chapter in Mathematical and Statistical Methods for Actuarial Sciences and Finance, 2024, pp 211-217 from Springer

Abstract: Abstract Area Yield Index (AYI) was considered as the most potential alternative crop insurance policy in Indonesia. To support this policy, delivering accurate paddy productivity prediction is a must. Thus, we purpose a new flexible Be-ta Four Parameter Generalized Mixed Effect Tree and Random Forest predic-tion model that combines the use of tree regression and random forest with a Bayesian beta four parameter GLMM approach. This model takes into con-sideration that paddy productivity has a bounded minimum and maximum distribution or known as a Beta Four Parameter distribution, variation effect of paddy productivity between areas, and captures complex linear and non-linear relationships in the data. This model was incorporated to design a pro-totype AYI crop insurance in Central Kalimantan, Indonesia that can be fur-ther developed in other areas. Farmer survey data integrated with processed satellite data was utilized in the process. Results show that high predictive accuracy was achieved in the proposed model. Therefore, beneficial for accu-rately assessing risk, setting fair premiums, reducing adverse selection, effi-ciently allocating resources, and ensuring the long-term sustainability of the paddy crop insurance program.

Keywords: Area Yield Index (AYI); Beta Four Parameter Distribution (B4P); General-ized Linear Mixed Model (GLMM); Beta Four Parameter Generalized Mixed Effect Tree (B4P GMET); Beta Four Parameter Generalized Mixed Effect Random Forest (B4P GMERF) (search for similar items in EconPapers)
Date: 2024
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DOI: 10.1007/978-3-031-64273-9_35

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