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Determinants of the global and regional CO_2 emissions: What causes what and where?

机译:全球和区域CO_2排放的决定因素:什么原因和原因?

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Using the Stochastic Impacts by Regression on Population, Affluence, and Technology (STIRPAT) model and an unbalanced panel dataset of 128 countries covering 1990-2014, this study aims to examine the key impact factors (KIFs) of the global and regional carbon dioxide (CO2) emissions and analyse the effectiveness of non-renewable and renewable energies. Given the potential cross-sectional dependence and slope heterogeneity, a series of econometric techniques allowing for cross-sectional dependence and slope heterogeneity is applied. The overall estimations imply that the KIFs at the global level are economic growth, followed by population size, non-renewable energy, and energy intensity in order of their impacts on CO2 emissions; conversely, the KIFs at the regional level vary across different regions and estimators. The results also suggest that renewable energy can lead to a decline in CO2 emissions at the global level. At the regional level, only for two regions (i.e., S. & Cent. America and Europe & Eurasia) renewable energy has a significant and negative effect on CO2 emissions, which may be affected by the share of renewable energy consumption in the primary energy mix. Finally, the results indicate varied causality relationships among the variables across regions.
机译:使用回归分析对人口,富裕度和技术的随机影响(STIRPAT)模型和覆盖1990-2014年的128个国家的不平衡面板数据集,本研究旨在研究全球和区域二氧化碳的关键影响因素(KIF)(二氧化碳排放量并分析不可再生和可再生能源的有效性。给定潜在的横截面依赖性和斜率异质性,应用了一系列允许横截面依赖性和斜率异质性的计量经济学技术。总体估计表明,全球范围内的关键绩效指标是经济增长,其次是人口规模,不可再生能源和能源强度,以其对二氧化碳排放的影响顺序排列;相反,区域级别的KIF随区域和估算器的不同而不同。结果还表明,可再生能源可以导致全球范围内二氧化碳排放量的下降。在区域一级,仅对于两个区域(即,南美和中美洲以及欧洲和欧亚大陆),可再生能源对CO2排放具有显着的负面影响,这可能会受到可再生能源在一次能源消费中所占份额的影响混合。最后,结果表明跨地区的变量之间存在不同的因果关系。

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