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ABSTRACT The field of energy economics is steeped in numerous studies that have centered on the relationship between energy consumption and economic growth, using multiple causality tests. However, with leveraging the previous studies, the literature needs to be expanded and enriched by harnessing modern, alternative econometric techniques. The aim of this study is to estimate panel quantile regression (PQR) models to find out the relationship between the energy consumption and the economic growth, by employing this technique on three separate models based on total, renewable and non-renewable energy consumption. With this three-tier feature built on the PQR models, our study is separated from the others and becomes a candidate to be a trailblazer. We unveil the effects of the energy usage on the economic growth at different quantile levels by using the annual dataset comprising the time span 2012-2022 for E7 countries. By and large, the aggregated numbers indicate that the renewables could be considered as a drive for the EG among higher-income countries, yet a drawback for lower-income countries. As for the renewables, while the solar EC poses a threat for the EG of the E7 countries as a whole at any level, the wind EC stands out as a driving force. On the non-renewables side of the study, the oil EC has a potential to ruin the higher-income countries as opposed to the coal EC, which supports the EG for the higher-income countries. When it comes to the gas EC, it shows a positive pattern for all countries.
Değirmenci et al. (Fri,) studied this question.