The BVAR Model for Analyzing CO2 Emissions on Renewable Energy, Economic Growth, and Forest Area
This research investigates the management of CO₂ emissions, a significant factor in the climate change phenomenon, focusing on Indonesia. The objective is to examine the correlation between CO₂ emissions and their causal variables: economic growth (measured by gross domestic product), forest area, a...
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| Format: | Article |
| Language: | English |
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Ital Publication
2025-06-01
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| Series: | Emerging Science Journal |
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| Online Access: | https://ijournalse.org/index.php/ESJ/article/view/2789 |
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| author | Dodi Devianto Ridho Saputra Mutia Yollanda Maiyastri Maiyastri Yudiantri Asdi Dony Permana Erna Tri Herdiani |
| author_facet | Dodi Devianto Ridho Saputra Mutia Yollanda Maiyastri Maiyastri Yudiantri Asdi Dony Permana Erna Tri Herdiani |
| author_sort | Dodi Devianto |
| collection | DOAJ |
| description | This research investigates the management of CO₂ emissions, a significant factor in the climate change phenomenon, focusing on Indonesia. The objective is to examine the correlation between CO₂ emissions and their causal variables: economic growth (measured by gross domestic product), forest area, and renewable energy (RE) consumption. The Bayesian vector autoregressive (BVAR) model was employed to address the complexity of multivariate interactions and overcome limitations associated with small datasets. The analysis revealed that economic growth and reduced forest area significantly contributed to high CO₂ emissions, while renewable energy consumption exhibited a mitigating effect. The BVAR model demonstrated substantial predictive accuracy, highlighting its suitability for analyzing environmental and economic data in resource-constrained scenarios. These findings emphasize the critical need for targeted policy actions in Indonesia, including safeguarding forest areas, addressing illegal logging and burning, and accelerating the transition to renewable energy. The study provides a novel application of the BVAR model in environmental research, showcasing its potential for generating actionable insights into emissions management. This study contributes to the understanding of sustainable development by proposing an innovative way to support evidence-based policies that reduce CO₂ emissions as well as mitigate climate change impacts. |
| format | Article |
| id | doaj-art-96cdd1e1e5184f0da592fd836ad3d7be |
| institution | Kabale University |
| issn | 2610-9182 |
| language | English |
| publishDate | 2025-06-01 |
| publisher | Ital Publication |
| record_format | Article |
| series | Emerging Science Journal |
| spelling | doaj-art-96cdd1e1e5184f0da592fd836ad3d7be2025-08-20T03:27:10ZengItal PublicationEmerging Science Journal2610-91822025-06-01931158117310.28991/ESJ-2025-09-03-022526The BVAR Model for Analyzing CO2 Emissions on Renewable Energy, Economic Growth, and Forest AreaDodi Devianto0https://orcid.org/0000-0003-0360-8604Ridho Saputra1Mutia Yollanda2Maiyastri Maiyastri3Yudiantri Asdi4Dony Permana5Erna Tri Herdiani6Department of Mathematics and Data Science, Universitas Andalas, Padang 25156Department of Mathematics and Data Science, Universitas Andalas, Padang 25156Department of Mathematics and Data Science, Universitas Andalas, Padang 25156Department of Mathematics and Data Science, Universitas Andalas, Padang 25156Department of Mathematics and Data Science, Universitas Andalas, Padang 25156Department of Statistics, Universitas Negeri Padang, Padang 25132Department of Statistics, Faculty of Mathematics and Natural Science, Hasanuddin University, Makassar 90245This research investigates the management of CO₂ emissions, a significant factor in the climate change phenomenon, focusing on Indonesia. The objective is to examine the correlation between CO₂ emissions and their causal variables: economic growth (measured by gross domestic product), forest area, and renewable energy (RE) consumption. The Bayesian vector autoregressive (BVAR) model was employed to address the complexity of multivariate interactions and overcome limitations associated with small datasets. The analysis revealed that economic growth and reduced forest area significantly contributed to high CO₂ emissions, while renewable energy consumption exhibited a mitigating effect. The BVAR model demonstrated substantial predictive accuracy, highlighting its suitability for analyzing environmental and economic data in resource-constrained scenarios. These findings emphasize the critical need for targeted policy actions in Indonesia, including safeguarding forest areas, addressing illegal logging and burning, and accelerating the transition to renewable energy. The study provides a novel application of the BVAR model in environmental research, showcasing its potential for generating actionable insights into emissions management. This study contributes to the understanding of sustainable development by proposing an innovative way to support evidence-based policies that reduce CO₂ emissions as well as mitigate climate change impacts.https://ijournalse.org/index.php/ESJ/article/view/2789carbon dioxidegross domestic productforest arearenewable energybayesian vector autoregressive |
| spellingShingle | Dodi Devianto Ridho Saputra Mutia Yollanda Maiyastri Maiyastri Yudiantri Asdi Dony Permana Erna Tri Herdiani The BVAR Model for Analyzing CO2 Emissions on Renewable Energy, Economic Growth, and Forest Area Emerging Science Journal carbon dioxide gross domestic product forest area renewable energy bayesian vector autoregressive |
| title | The BVAR Model for Analyzing CO2 Emissions on Renewable Energy, Economic Growth, and Forest Area |
| title_full | The BVAR Model for Analyzing CO2 Emissions on Renewable Energy, Economic Growth, and Forest Area |
| title_fullStr | The BVAR Model for Analyzing CO2 Emissions on Renewable Energy, Economic Growth, and Forest Area |
| title_full_unstemmed | The BVAR Model for Analyzing CO2 Emissions on Renewable Energy, Economic Growth, and Forest Area |
| title_short | The BVAR Model for Analyzing CO2 Emissions on Renewable Energy, Economic Growth, and Forest Area |
| title_sort | bvar model for analyzing co2 emissions on renewable energy economic growth and forest area |
| topic | carbon dioxide gross domestic product forest area renewable energy bayesian vector autoregressive |
| url | https://ijournalse.org/index.php/ESJ/article/view/2789 |
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