Simulation and analysis of area-based yield (ARBY) index insurance for rice
The ARBY simulation in six municipalities in the 2023-2024 dry season was conducted to assess its potential performance and financial viability. The simulation covers analysis of coverage levels, loss ratio, and the impact of factors such as correlated risks and yield distributions. Key findings in...
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| Format: | Ponencia |
| Language: | Inglés |
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International Rice Research Institute
2024
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| Online Access: | https://hdl.handle.net/10568/169689 |
| _version_ | 1855519739979235328 |
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| author | Alcala, Jeric |
| author_browse | Alcala, Jeric |
| author_facet | Alcala, Jeric |
| author_sort | Alcala, Jeric |
| collection | Repository of Agricultural Research Outputs (CGSpace) |
| description | The ARBY simulation in six municipalities in the 2023-2024 dry season was conducted to assess its potential performance and financial viability. The simulation covers analysis of coverage levels, loss ratio, and the impact of factors such as correlated risks and yield distributions. Key findings include: (a) the simulation revealed that ARBY is financially sustainable under standard conditions, with expected loss ratios of 44.83% for 80% coverage and 56.11% for 90% coverage. These ratios indicate that the product is viable for both farmers and insurers, balancing affordability and risk management; (b) the probability of financial ruin—where total claims exceed collected premiums—was calculated at 13.90% for 80% coverage and 20.70% for 90% coverage. Although ARBY remains sustainable at both levels, higher coverage increases the financial risk, suggesting the need for additional risk management strategies such as reinsurance or risk pooling; (c) correlated risks occur when multiple regions experience yield losses simultaneously due to widespread events like typhoons or droughts. The study showed that even under these conditions, ARBY maintained a robust performance, with loss ratios varying by less than 5% from initial assumptions; (d) when testing the model with skew-normal yield distributions (reflective of real-world conditions), the loss ratios increased significantly—83.12% for 80% coverage and 63.90% for 90% coverage. This highlights the importance of accurate yield data and suggests the need for continuous refinement of the yield estimation models used in ARBY; and (e) accurate and up-to-date yield data is crucial for setting trigger yields and determining premiums. A 5% underestimation of historical yields could lead to loss ratios over 100%, risking the financial sustainability of the product. |
| format | Ponencia |
| id | CGSpace169689 |
| institution | CGIAR Consortium |
| language | Inglés |
| publishDate | 2024 |
| publishDateRange | 2024 |
| publishDateSort | 2024 |
| publisher | International Rice Research Institute |
| publisherStr | International Rice Research Institute |
| record_format | dspace |
| spelling | CGSpace1696892025-01-24T01:30:40Z Simulation and analysis of area-based yield (ARBY) index insurance for rice Alcala, Jeric simulation analysis crop insurance risk management The ARBY simulation in six municipalities in the 2023-2024 dry season was conducted to assess its potential performance and financial viability. The simulation covers analysis of coverage levels, loss ratio, and the impact of factors such as correlated risks and yield distributions. Key findings include: (a) the simulation revealed that ARBY is financially sustainable under standard conditions, with expected loss ratios of 44.83% for 80% coverage and 56.11% for 90% coverage. These ratios indicate that the product is viable for both farmers and insurers, balancing affordability and risk management; (b) the probability of financial ruin—where total claims exceed collected premiums—was calculated at 13.90% for 80% coverage and 20.70% for 90% coverage. Although ARBY remains sustainable at both levels, higher coverage increases the financial risk, suggesting the need for additional risk management strategies such as reinsurance or risk pooling; (c) correlated risks occur when multiple regions experience yield losses simultaneously due to widespread events like typhoons or droughts. The study showed that even under these conditions, ARBY maintained a robust performance, with loss ratios varying by less than 5% from initial assumptions; (d) when testing the model with skew-normal yield distributions (reflective of real-world conditions), the loss ratios increased significantly—83.12% for 80% coverage and 63.90% for 90% coverage. This highlights the importance of accurate yield data and suggests the need for continuous refinement of the yield estimation models used in ARBY; and (e) accurate and up-to-date yield data is crucial for setting trigger yields and determining premiums. A 5% underestimation of historical yields could lead to loss ratios over 100%, risking the financial sustainability of the product. 2024-09-25 2025-01-22T21:41:25Z 2025-01-22T21:41:25Z Presentation https://hdl.handle.net/10568/169689 en Open Access application/pdf International Rice Research Institute Alcala, J. (2024). Simulation and analysis of area-based yield (ARBY) index insurance for rice. Presented at the ClimBeR Workhop Strengthening Climate Resilience in the Philippines: Insights and Policy Recommendations from the ClimBeR Initiative. September 25, 2024, Alabang, Philippines. |
| spellingShingle | simulation analysis crop insurance risk management Alcala, Jeric Simulation and analysis of area-based yield (ARBY) index insurance for rice |
| title | Simulation and analysis of area-based yield (ARBY) index insurance for rice |
| title_full | Simulation and analysis of area-based yield (ARBY) index insurance for rice |
| title_fullStr | Simulation and analysis of area-based yield (ARBY) index insurance for rice |
| title_full_unstemmed | Simulation and analysis of area-based yield (ARBY) index insurance for rice |
| title_short | Simulation and analysis of area-based yield (ARBY) index insurance for rice |
| title_sort | simulation and analysis of area based yield arby index insurance for rice |
| topic | simulation analysis crop insurance risk management |
| url | https://hdl.handle.net/10568/169689 |
| work_keys_str_mv | AT alcalajeric simulationandanalysisofareabasedyieldarbyindexinsuranceforrice |