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 th...

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Main Authors: Riaman, Riaman, Sukono, Sukono, Supian, Sudradjat, Ismail, Noriszura
Format: Article
Language:English
Published: Growing Science 2021-01-01
Series:Decision Science Letters
Online Access:http://www.growingscience.com/dsl/Vol10/dsl_2021_8.pdf
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spelling doaj-f0575a8b053d40ddb15e3e898db7fdf22021-05-10T10:01:10ZengGrowing 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, Noriszura 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.http://www.growingscience.com/dsl/Vol10/dsl_2021_8.pdf
collection DOAJ
language English
format Article
sources DOAJ
author Riaman, Riaman
Sukono, Sukono
Supian, Sudradjat
Ismail, Noriszura
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
author_facet Riaman, Riaman
Sukono, Sukono
Supian, Sudradjat
Ismail, Noriszura
author_sort Riaman, Riaman
title 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_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_sort analysing the decision making for agricultural risk assessment: an application of extreme value theory
publisher Growing Science
series Decision Science Letters
issn 1929-5804
1929-5812
publishDate 2021-01-01
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.
url http://www.growingscience.com/dsl/Vol10/dsl_2021_8.pdf
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