Abstract

To effectively address climate change, economies worldwide must transition from grey, fossil fuel–dependant models to green, renewable energy–based systems, thereby striving to reduce global warming. However, a comparative study of how internal and external macro-economic dynamics influence both grey and green energy sources remains significantly underexplored. This study examines the effects of aggregated, renewable and non-renewable energy on economic growth. Therefore, this study investigates the connection between aggregated and disaggregated energy consumption (renewables and non-renewables) and economic growth in Canada by incorporating internal and external macro-economic determinants, along with institutional quality, which are variables during the period of 1990–2022. Using the dynamic autoregressive distributed lag (DARDL) approach, the study's results reveal that both aggregated and disaggregated energy consumption of renewable and non-renewable sources stimulate economic growth in the presence of both internal and external dynamics in both the short and long terms. However, this relationship is stronger in the context of internal dynamics than external ones. In addition, we conduct a counterfactual analysis by displaying 1 % (±) and 5 % (±) shocks to regressors and examining their effects on the regressed variable. Finally, we use the kernel-based regularised least squares (KRLS) machine learning algorithm to examine the cause-and-effect connectedness amongst variables. On the basis of the findings, this study recommends optimising both internal and external dynamics by adopting a diversified energy mix strategy. This approach will enable Canada to transition towards a sustainable and resilient economic future.

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