Analysing the decision making for agricultural risk assessment: An application of extreme value theory
As the most contributed sectors in agriculture, rice farming is facing various risks, namely uncertainty such as crop failure caused by climate change, including air temperature, weather, rainfall and others. Indonesia is categorised as an agricultural country with a tropical climate. By this season...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Growing Science
2021-01-01
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| Series: | Decision Science Letters |
| Online Access: | http://www.growingscience.com/dsl/Vol10/dsl_2021_8.pdf |
| _version_ | 1818387286377627648 |
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| author | Riaman, Riaman Sukono, Sukono Supian, Sudradjat Ismail, Noriszura |
| author_facet | Riaman, Riaman Sukono, Sukono Supian, Sudradjat Ismail, Noriszura |
| author_sort | Riaman, Riaman |
| collection | DOAJ |
| description | As the most contributed sectors in agriculture, rice farming is facing various risks, namely uncertainty such as crop failure caused by climate change, including air temperature, weather, rainfall and others. Indonesia is categorised as an agricultural country with a tropical climate. By this season, the farmers can plant the rice. Rice farming is currently an inseparable part of most agricultural societies in Indonesia, especially in West Java. However, changes in air temperature, weather and annual rainfall, can increase the uncertainty and upward the risk of crop failure. Thus, the current study seeks to investigate the decision making for agricultural risk assessment (climate variable) through the formulation of a risk model for agricultural insurance in Indonesia. This study utilised the climate variables, which consist of air temperature, wind speed, maximum and minimum temperatures, and rainfall. For determining the magnitude of risk, we applied the Block Maxima method and Peak Over Threshold. The results of this study found that the highest risk of losses occurred in November, December, January, February and March with a value of 0.17485. |
| first_indexed | 2024-12-14T04:07:32Z |
| format | Article |
| id | doaj.art-f0575a8b053d40ddb15e3e898db7fdf2 |
| institution | Directory Open Access Journal |
| issn | 1929-5804 1929-5812 |
| language | English |
| last_indexed | 2024-12-14T04:07:32Z |
| publishDate | 2021-01-01 |
| publisher | Growing Science |
| record_format | Article |
| series | Decision Science Letters |
| spelling | doaj.art-f0575a8b053d40ddb15e3e898db7fdf22022-12-21T23:17:48ZengGrowing ScienceDecision Science Letters1929-58041929-58122021-01-0110335136010.5267/j.dsl.2021.2.003Analysing the decision making for agricultural risk assessment: An application of extreme value theoryRiaman, RiamanSukono, SukonoSupian, SudradjatIsmail, NoriszuraAs the most contributed sectors in agriculture, rice farming is facing various risks, namely uncertainty such as crop failure caused by climate change, including air temperature, weather, rainfall and others. Indonesia is categorised as an agricultural country with a tropical climate. By this season, the farmers can plant the rice. Rice farming is currently an inseparable part of most agricultural societies in Indonesia, especially in West Java. However, changes in air temperature, weather and annual rainfall, can increase the uncertainty and upward the risk of crop failure. Thus, the current study seeks to investigate the decision making for agricultural risk assessment (climate variable) through the formulation of a risk model for agricultural insurance in Indonesia. This study utilised the climate variables, which consist of air temperature, wind speed, maximum and minimum temperatures, and rainfall. For determining the magnitude of risk, we applied the Block Maxima method and Peak Over Threshold. The results of this study found that the highest risk of losses occurred in November, December, January, February and March with a value of 0.17485.http://www.growingscience.com/dsl/Vol10/dsl_2021_8.pdf |
| spellingShingle | Riaman, Riaman Sukono, Sukono Supian, Sudradjat Ismail, Noriszura Analysing the decision making for agricultural risk assessment: An application of extreme value theory Decision Science Letters |
| title | Analysing the decision making for agricultural risk assessment: An application of extreme value theory |
| title_full | Analysing the decision making for agricultural risk assessment: An application of extreme value theory |
| title_fullStr | Analysing the decision making for agricultural risk assessment: An application of extreme value theory |
| title_full_unstemmed | Analysing the decision making for agricultural risk assessment: An application of extreme value theory |
| title_short | Analysing the decision making for agricultural risk assessment: An application of extreme value theory |
| title_sort | analysing the decision making for agricultural risk assessment an application of extreme value theory |
| url | http://www.growingscience.com/dsl/Vol10/dsl_2021_8.pdf |
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