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Alternative Area Yield Index Based Crop Insurance Policies in Indonesia

In: Mathematical and Statistical Methods for Actuarial Sciences and Finance

Author

Listed:
  • Dian Kusumaningrum

    (Prasetiya Mulya University)

  • Rahma Anisa

    (IPB University)

  • Valantino Agus Sutomo

    (Prasetiya Mulya University)

  • Ken Seng Tan

    (Nanyang Business School, Nanyang Technological University)

Abstract

Starting in 2015, farmers in Indonesia could protect their paddy cultivation by participating in the insurance scheme enacted by the Paddy Plant Business Insurance (PPBI) program. Despite it is heavily subsidized by the government and that it is a Multi-Peril Crop Insurance (MPCI), less than 1% of the total farming land are insured. The lack of demand could be due to the fact that the existing MPCI’s indemnity depends on the damaged farming land, as opposed to the actual paddy productivity. In view of this drawback, this paper considers two other insurance schemes, with one generalizes the existing MPCI by integrating paddy productivity to the indemnity, and the other is an area yield index (AYI) policy. By calibrating to the empirical data, we conduct extensive Monte Carlo studies to assess the efficiency of these schemes. The simulated premium of the existing MPCI is around IDR 250,000. This is higher than current premium and the underprice can be detrimental to the PPBI program’s sustainability. By comparing cost of insurance and tail risk (VaR and TVaR), we conclude that the first scheme is not a viable solution due to its high premium and high tail risk. The AYI, on the other hand, is a viable option. Its premium is comparable to the existing MPCI but with a much smaller tail risk. Furthermore, it has the potential of overcoming many of the drawbacks that are commonly found in MPCI (such as moral hazard and high administrative cost).

Suggested Citation

  • Dian Kusumaningrum & Rahma Anisa & Valantino Agus Sutomo & Ken Seng Tan, 2021. "Alternative Area Yield Index Based Crop Insurance Policies in Indonesia," Springer Books, in: Marco Corazza & Manfred Gilli & Cira Perna & Claudio Pizzi & Marilena Sibillo (ed.), Mathematical and Statistical Methods for Actuarial Sciences and Finance, pages 285-290, Springer.
  • Handle: RePEc:spr:sprchp:978-3-030-78965-7_42
    DOI: 10.1007/978-3-030-78965-7_42
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