Investigating the agricultural losses due to climate variability: An application of conditional value-at-risk approach

Sukono, S.; Riaman, R.; Supian, S.; Hidayat, Y.; Saputra, J.; Pribadi, D.

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Decision Science Letters

ISSN 1929-5812 (Online) - ISSN 1929-5804 (Print) Quarterly Publication Volume 10 Issue 1 pp. 71-78 , 2021

Investigating the agricultural losses due to climate variability: An application of conditional value-at-risk approach Pages 71-78 Download PDF

Authors: Sukono Sukono, Riaman Riaman, Sudradjat Supian, Yuyun Hidayat, Jumadil Saputra, Diantiny Mariam Pribadi

DOI: 10.5267/j.dsl.2020.10.002

Keywords: Allocation of agricultural land, Climate variable, Crop insurance, Optimization, Risk measure, Optimal Decision

Abstract: The agricultural sector is directly affected by climate variables. The presence of climate variability causes a considerable risk to agricultural productivities. Thus, risk management is an alternative to reduce risks, including optimizing the allocation of farmland and choosing crop insurance for a specific planting date. The purpose of this study is to investigate the agricultural risk management through risk measure of climate variability using the Conditional Value-at-Risk (CVaR) in rice production. This paper investigated several possible considerations of agricultural insurance premiums based on losses climate index. We concluded that the climate index insurance policy is the best choice that farmers can choose for each planting date, the higher the significance value considered, the more the value of Value-at-Risk and Conditional Value-at-Risk.

How to cite this paper

 Sukono, S., Riaman, R., Supian, S., Hidayat, Y., Saputra, J & Pribadi, D. (2021). Investigating the agricultural losses due to climate variability: An application of conditional value-at-risk approach.Decision Science Letters , 10(1), 71-78.

Refrences

Artzner, P., Delbaen, F., Eber, J. M., & Heath, D. (1999). Coherent measures of risk. Mathematical Finance, 9(3), 203-228.
Azad, N., Zangeneh, G., SeyedAliAkbar, S., & Valipour, A. (2013). A survey on critical factors influencing agricultural insurance. Management Science Letters, 3(1), 237-242.
Berg, E., & Schmitz, B. (2007). Weather-based instruments in the context of whole farm risk management (No. 686-2016-47135).
Cabrera, V. E., Fraisse, C. W., Letson, D., Podestá, G., & Novak, J. (2006). Impact of climate information on reducing farm risk by optimizing crop insurance strategy. Transactions of the ASABE, 49(4), 1223-1233.
Cabrera, V. E., Solis, D., & Letson, D. (2009). Optimal crop insurance under climate variability: contrasting insurer and farmer interests. Transactions of the ASABE, 52(2), 623-631.
Caruso, R., Petrarca, I., & Ricciuti, R. (2016). Climate change, rice crops, and violence: Evidence from Indonesia. Journal of Peace Research, 53(1), 66-83.
Jain, V., & Dharmaraja, S. (2019). Crop insurance in India: a mathematical review. In Operations Research in Development Sector (pp. 97-107). Springer, Singapore.
Kawanishi, M., & Mimura, N. (2015). Assessment of insurance for paddy production: a case study in Indonesia. Climate and Development, 7(3), 257-266.
Krokhmal, P., Palmquist, J., & Uryasev, S. (2002). Portfolio optimization with conditional value-at-risk objective and constraints. Journal of Risk, 4, 43-68.
Liu, J., Men, C., Cabrera, V. E., Uryasev, S., & Fraisse, C. W. (2008). Optimizing crop insurance under climate variability. Journal of Applied Meteorology and Climatology, 47(10), 2572-2580..
Ochieng, J., Kirimi, L., & Mathenge, M. (2016). Effects of climate variability and change on agricultural production: The case of small scale farmers in Kenya. NJAS-Wageningen Journal of Life Sciences, 77, 71-78..
Pasaribu S. M., & Sudiyanto A. (2016): Agricultural risk management: lesson learned from the application of rice crop insurance in Indonesia. In: Kaneko S., Kawanishi M. (eds) Climate Change Policies and Challenges in Indonesia. Springer, Tokyo.
Pasaribu, S. M. (2010). Developing rice farm insurance in Indonesia. Agriculture and Agricultural Science Procedia, 1, 33-41.
Quaranta, A. G., & Zaffaroni, A. (2008). Robust optimization of conditional value at risk and portfolio selection. Journal of Banking & Finance, 32(10), 2046-2056.
Rockafellar, R. T., & Uryasev, S. (2000). Optimization of conditional value-at-risk. Journal of Risk, 2, 21-42.
Rockafellar, R. T., & Uryasev, S. (2002). Conditional value-at-risk for genereal loss distributions. Journal of Banking & Finance, 26, 1443-1471.
Tong, X., Qi, L., Wu, F., & Zhou, H. (2010). A smoothing method for solving portfolio optimization with CVaR and applications in allocation of generation asset. Applied Mathematics and Computation, 216(6), 1723-1740.
Wang, C. P., & Huang, H. H. (2016). Optimal insurance contract under VaR and CVaR constraints. The North American Journal of Economics and Finance, 37, 110-127.
Yoshioka, N. (2017), A reconsideration of crop insurance as climate change adaptation approach. Journal of Economics and Sustainable Development, 8(22), 1-8.
Zhu S., & Fukushima M. (2009). Worst-case conditional value-at-risk with application to robust portfolio management. Operations Research, 57(5), 1155-1168.