Risk management in broiler farming: optimizing poultry insurance coverage using a spatial panel data analysis
IntroductionBroiler producers face various risks, leading to productivity and financial fluctuations worldwide. Agricultural insurance is an important risk management tool to stabilize income. Employing optimal insurance methods is crucial for effective production risk management.MethodIn this study...
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Frontiers Media S.A.
2025-05-01
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| Series: | Frontiers in Animal Science |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fanim.2025.1468935/full |
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| author | Mohammad Ebrahim Hasan-Nejad Amir Mohammadi-Nejad Mohammad Ghorbani Seyed Yaghoub Zeraatkish |
| author_facet | Mohammad Ebrahim Hasan-Nejad Amir Mohammadi-Nejad Mohammad Ghorbani Seyed Yaghoub Zeraatkish |
| author_sort | Mohammad Ebrahim Hasan-Nejad |
| collection | DOAJ |
| description | IntroductionBroiler producers face various risks, leading to productivity and financial fluctuations worldwide. Agricultural insurance is an important risk management tool to stabilize income. Employing optimal insurance methods is crucial for effective production risk management.MethodIn this study, we used the panel method and spatial regression model to assess the impact of explanatory variables on the demand for poultry insurance. The explanatory variables included risk factors, the number of birds, loss cases, insurance premiums, and insurers' commitment to each insured chicken. The data for this study was obtained from the Agricultural Insurance Fund from 2010 to 2020 in Iran.Results and DiscussionThe results indicate that an increase in mortality rates, loss cases, and risk factors positively and significantly influences the volume of insured chickens. Furthermore, increasing the insurer's commitment to each chicken positively and substantially affects poultry insurance demand. Specifically, a 1% increase in the insurer's commitment for each chicken in a province corresponds to a 1.1% rise in the number of insured chickens. An examination of the overall long-term effects reveals that a 1% increase in the risk factor, the number of loss cases, and the insurer's commitment for each chicken in a province, leads to an average rise of 0.14%, 0.35%, and 1.2%, respectively, in the number of insured chickens within the same province. These findings highlight the importance of risk management strategies, such as agricultural insurance, in stabilizing the income of broiler producers. Policymakers and industry stakeholders should focus on strengthening the insurance system and increasing insurers' commitment to promoting the uptake of poultry insurance among producers. |
| format | Article |
| id | doaj-art-ea2907b0d46546ae9cf71bda1afc31f0 |
| institution | DOAJ |
| issn | 2673-6225 |
| language | English |
| publishDate | 2025-05-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Animal Science |
| spelling | doaj-art-ea2907b0d46546ae9cf71bda1afc31f02025-08-20T03:09:43ZengFrontiers Media S.A.Frontiers in Animal Science2673-62252025-05-01610.3389/fanim.2025.14689351468935Risk management in broiler farming: optimizing poultry insurance coverage using a spatial panel data analysisMohammad Ebrahim Hasan-Nejad0Amir Mohammadi-Nejad1Mohammad Ghorbani2Seyed Yaghoub Zeraatkish3Department of Agricultural Economics, SR.C., Islamic Azad University, Tehran, IranDepartment of Agricultural Economics, SR.C., Islamic Azad University, Tehran, IranCenter for Remote Sensing and GIS Research, Faculty of Earth Sciences, Shahid Beheshti University, Tehran, IranDepartment of Agricultural Economics, SR.C., Islamic Azad University, Tehran, IranIntroductionBroiler producers face various risks, leading to productivity and financial fluctuations worldwide. Agricultural insurance is an important risk management tool to stabilize income. Employing optimal insurance methods is crucial for effective production risk management.MethodIn this study, we used the panel method and spatial regression model to assess the impact of explanatory variables on the demand for poultry insurance. The explanatory variables included risk factors, the number of birds, loss cases, insurance premiums, and insurers' commitment to each insured chicken. The data for this study was obtained from the Agricultural Insurance Fund from 2010 to 2020 in Iran.Results and DiscussionThe results indicate that an increase in mortality rates, loss cases, and risk factors positively and significantly influences the volume of insured chickens. Furthermore, increasing the insurer's commitment to each chicken positively and substantially affects poultry insurance demand. Specifically, a 1% increase in the insurer's commitment for each chicken in a province corresponds to a 1.1% rise in the number of insured chickens. An examination of the overall long-term effects reveals that a 1% increase in the risk factor, the number of loss cases, and the insurer's commitment for each chicken in a province, leads to an average rise of 0.14%, 0.35%, and 1.2%, respectively, in the number of insured chickens within the same province. These findings highlight the importance of risk management strategies, such as agricultural insurance, in stabilizing the income of broiler producers. Policymakers and industry stakeholders should focus on strengthening the insurance system and increasing insurers' commitment to promoting the uptake of poultry insurance among producers.https://www.frontiersin.org/articles/10.3389/fanim.2025.1468935/fullagricultural insurancebroilerprofitabilityoptimizingpanel data analyses |
| spellingShingle | Mohammad Ebrahim Hasan-Nejad Amir Mohammadi-Nejad Mohammad Ghorbani Seyed Yaghoub Zeraatkish Risk management in broiler farming: optimizing poultry insurance coverage using a spatial panel data analysis Frontiers in Animal Science agricultural insurance broiler profitability optimizing panel data analyses |
| title | Risk management in broiler farming: optimizing poultry insurance coverage using a spatial panel data analysis |
| title_full | Risk management in broiler farming: optimizing poultry insurance coverage using a spatial panel data analysis |
| title_fullStr | Risk management in broiler farming: optimizing poultry insurance coverage using a spatial panel data analysis |
| title_full_unstemmed | Risk management in broiler farming: optimizing poultry insurance coverage using a spatial panel data analysis |
| title_short | Risk management in broiler farming: optimizing poultry insurance coverage using a spatial panel data analysis |
| title_sort | risk management in broiler farming optimizing poultry insurance coverage using a spatial panel data analysis |
| topic | agricultural insurance broiler profitability optimizing panel data analyses |
| url | https://www.frontiersin.org/articles/10.3389/fanim.2025.1468935/full |
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