Convergence in renewable energy consumption and their influencing factors across regions: evidence from convergence algorithm approach

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.