What drives renewable energy in the group of seven economies? Evidence from non-parametric panel methods

Abstract

In the last few decades, the environmental degradation, global warming, and climate change remained the life-threatening issues across the globe. Specifically, the use of non-renewable fossil fuels is regarded as the most significant reason of such inclined issues. However, the policy-makers and scholars are now more concerned about the recovery of environmental quality, where renewable energy is considered as the primary solution to the existing issue. The developed economies and environment related international organizations rapidly enhances the use and promotion of renewable energy after the taking pledge in the Kyoto Protocol Agreement (1997). Nonetheless, the scholars are participating in analyzing the key drivers of renewable energy. Still, the proper drivers of renewable energy are not properly addressed in the existing literature. To fill this gap, current study analyzed the group of seven (G7) economies over the period 1990-2020. Using various panel data techniques such as slope heterogeneity, cross-section dependence, unit root, and cointegration test, the results indicates that the slopes are heterogeneous, and the cross-section dependence, as well as cointegration exists among the panel economies. Besides, the irregular distribution of data leads to the adoption of novel Method of Moments Quantile Regression accommodating four quantiles, i.e., ((Formula presented.) (Formula presented.) (Formula presented.) and (Formula presented.)). The examined results asserted that economic growth and energy efficiency negatively and significantly affects renewable energy consumption ((Formula presented.)). Whereas, developed environmental related technologies, environmental taxes, and composite risk index are positively affecting (Formula presented.) in the study panel. Besides, improved energy efficiency (energy efficiency squared) also contributed to the promotion of renewable energy consumption. The Granger causality test estimates reveals bidirectional and unidirectional causal association between the variables. Based on the empirical results, policies are provided that could help developed economies in the promotion of renewable energy consumption, improve economic growth, and enhances environmental sustainability.