Exploring carbon dioxide emissions and their drivers in global leading economies A Panel vector autoregression perspective
Indian Agricultural Research Journals
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Title |
Exploring carbon dioxide emissions and their drivers in global leading economies A Panel vector autoregression perspective
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Creator |
K Nirmal Ravi Kumar
Moses Shyam M S Madhav K Vijay Krishna Kumar Adinan Bahahudeen Shafiwu |
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Subject |
CO2-emissions
Panel cross-dependence Panel vector autoregression gross domestic product gross fixed capital formation temperature change urbanization |
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Description |
This study delves the intricate interplay between carbon dioxide (CO2) emissions and economic development in the top 20 CO2-emitting nations from 2011 to 2021. By examining the influential factors such as Gross Domestic Product (GDP), Gross Fixed Capital Formation (GFCF), Temperature Change (TC), and Urbanization (UPop), the study unravels their profound impact on CO2-emissions. The study begins with testing the stationarity of its variables, finding that they become stationary after first-order differencing. The cross-section dependence test highlights the shared common factors among observations. Although the study initially seeks long-term equilibrium relationships, the findings don’t strongly support this. Consequently, the focus shifts to examining short-term dynamics through first-order differences. The study has employed Panel VAR Model to balance temporal dependencies and model simplicity. It has found that lagged CO2-emissions [d(CO2 (-1))] show a significant and positive association with current CO2-emissions , while a two-period lag [d(CO2 (-2))] is not significant, suggesting an immediate CO2 -impact. The GDP has been found negatively related to CO2-emissions, indicating increased GDP leads to slight emission-reduction. The GFCF has shown a positive link, emphasizing capital investments’ emission impact. The temperature change (TC) has shown a nuanced relationship, with short-term increases driving emissions. The Urbanization (UPop) consistently raises CO2-emissions. The impulse response functions (IRFs) have visually illustrated CO2 responses to standard deviation shocks in GDP, GFCF, TC, and UPop, revealing complex relationships over time. The variance decomposition analysis has revealed strong autocorrelation in economic variables, indicating that past values strongly predict future behaviour. The Granger-causality tests have established significant relationships, showing GDP and GFCF causing CO2-emissions, emphasizing economic growth’s impact. The UPop drives CO2-emissions, reflecting urbanization challenges. However, reverse causality and the TC-emissions link lack clear statistical significance. These findings suggest the policymakers to prioritize green investments, sustainable practices, urban planning, climate-resilient policies, international cooperation, carbon pricing mechanisms, and public awareness. These multifaceted strategies would ensure equilibrium between economic growth and environmental sustainability through addressing the intricate dynamics of emissions while emphasizing the need for global collaboration.
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Publisher |
Agricultural Economics Research Association (India)
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Date |
2024-08-08
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Type |
info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion Peer-reviewed Article |
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Format |
application/pdf
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Identifier |
https://epubs.icar.org.in/index.php/AERR/article/view/154830
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Source |
Agricultural Economics Research Review; Vol. 37 No. 1 (2024): Agricultural Economics Research Review; 13-34
0974-0279 0971-3441 |
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Language |
eng
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Relation |
https://epubs.icar.org.in/index.php/AERR/article/view/154830/55416
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