School of Economics and Econometrics, College of Business and Economics, University of Johannesburg, Auckland Park Kingsway Campus, PO Box 524, Auckland Park, Johannesburg, South Africa.
Environ Sci Pollut Res Int. 2022 Aug;29(40):61412-61445. doi: 10.1007/s11356-022-19731-9. Epub 2022 Apr 20.
This study examines the convergence in renewable energy consumption over the period 2000-2018 by using a convergence algorithm developed by Phillips and Sul. We used 183 countries which were sub-divided into five regions, namely: Sub-Saharan Africa (SSA); Middle East and North Africa (MENA); Europe and Central Asia (ECA); East and South Asia and the Pacific (ESAP); and America. The possible influencing determinants of the convergence/divergence clubs for the regions were also investigated by utilising multinomial logit regression. The determinants were majorly classified into macroeconomic, socio-economic, and institutional quality variables, which were computed via principal component analysis by using six governance indicators. The results show an absence of panel convergence and a weak speed of convergence for the regions. The final club formation results obtained from the iteration procedure show that 6 clubs (for SSA), 2 (for MENA and ECA), 5 (for ESAP), and 3 (for America) were formed for the regions. The determinants of renewable energy consumption play both significant and insignificant roles in the likelihood of a country belonging to a particular convergence club in each of the regions. This study found that at the regional level, the process of convergence in renewable energy consumption is yet to echo desirable emanations of renewable energy consumption policies sharing similar characteristics, but the narrative differs when clustering algorithms form clubs for each region. This implies that at regional levels, achieving convergence clubs in renewable energy consumption for environmental sustainability is possible, most especially when realistic policies around macroeconomic, socio-economic and institutional quality variables are taken into account.
本研究使用 Phillips 和 Sul 开发的收敛算法，考察了 2000-2018 年可再生能源消费的收敛情况。我们使用了 183 个国家，这些国家被分为五个地区，分别是：撒哈拉以南非洲（SSA）、中东和北非（MENA）、欧洲和中亚（ECA）、东亚和南亚及太平洋（ESAP）以及美洲。还利用多项逻辑回归研究了可能影响各地区收敛/发散俱乐部的决定因素。这些决定因素主要分为宏观经济、社会经济和制度质量变量，通过使用六个治理指标进行主成分分析来计算。结果表明，各地区不存在面板收敛，收敛速度也较弱。迭代过程中得出的最终俱乐部形成结果表明，6 个俱乐部（SSA）、2 个俱乐部（MENA 和 ECA）、5 个俱乐部（ESAP）和 3 个俱乐部（美洲）形成。可再生能源消费的决定因素在一国属于各地区特定收敛俱乐部的可能性方面发挥着重要和不重要的作用。本研究发现，在区域层面，可再生能源消费的收敛过程尚未反映出具有相似特征的可再生能源消费政策的理想影响，但当聚类算法为每个地区形成俱乐部时，情况就不同了。这意味着在区域层面上，实现环境可持续性的可再生能源消费的趋同俱乐部是有可能的，尤其是当考虑到宏观经济、社会经济和制度质量变量的现实政策时。
