Pure Premium Calculation of Rice Farm Insurance Scheme in Indonesia Based on The 4-Parameter Beta Mixture Distribution: A Recent Study

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Pure Premium Calculation of Rice Farm Insurance Scheme in Indonesia Based on The 4-Parameter Beta Mixture Distribution: A Recent Study

September 8, 2021 Engineering 0

Rice farm insurance (Asuransi Usaha Tani Padi – AUTP programme) was developed by the Indonesian government to safeguard rice farms against losses caused by floods, droughts, and pest and disease infestations. The method for calculating pure premiums for the rice farm insurance plan in Indonesia has been explored, assuming that the distribution of rice yield data is normal, gamma, or normal mixture distribution. For the situation of rice yield data distribution in the form of symmetry, the normal distribution can be applied. When the distribution of rice yield data is skewed to the right or positively skewed, the gamma distribution can be employed. In addition, unimodal distributions include the normal and gamma distributions. The method of calculating pure premiums for the rice farm insurance plan in Indonesia has also been studied, under the assumption that rice yield data follows a normal mixture distribution. The multimodal distribution can be classified as the normal mixing distribution. The normal mixture distribution’s characteristic is appropriate for rice yield data in Indonesia that includes data from multiple provinces. The 4-parameter beta mixed distribution, on the other hand, can be used to analyse rice yield data in Indonesia. In terms of the tail shape of the distribution, this distribution is more flexible than the conventional mixing distribution. In this research, the AUTP program’s pure premium calculation approach is defined using the assumption that rice yield data distribution is a 4-parameter beta mixed distribution. The method’s performance is assessed using Monte Carlo simulation. When the sample size is increased, the Monte Carlo simulation results reveal that the suggested method has higher accuracy and precision. The approach is applied to data on rice productivity in numerous Indonesian provinces from 1970 to 2016.

Author (S) Details

Aceng Komarudin Mutaqin
Department of Statistics, Universitas Islam Bandung, Indonesia.

Yayat Karyana
Department of Statistics, Universitas Islam Bandung, Indonesia.

Siti Sunendiari
Department of Statistics, Universitas Islam Bandung, Indonesia.

View Book :- https://stm.bookpi.org/NAER-V10/article/view/2989

 

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