{"title":"Green versus grey: Impact of renewable and non-renewable energy usage on Canada's growth trajectory in the context of internal and external forces","authors":"Md. Idris Ali , Md. Monirul Islam , Brian Ceh","doi":"10.1016/j.sftr.2024.100258","DOIUrl":null,"url":null,"abstract":"<div><p>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.</p></div>","PeriodicalId":34478,"journal":{"name":"Sustainable Futures","volume":null,"pages":null},"PeriodicalIF":3.3000,"publicationDate":"2024-08-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2666188824001084/pdfft?md5=05d8496b958f09865d873141b38de6d5&pid=1-s2.0-S2666188824001084-main.pdf","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Sustainable Futures","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2666188824001084","RegionNum":2,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ENVIRONMENTAL SCIENCES","Score":null,"Total":0}
引用次数: 0
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.
期刊介绍:
Sustainable Futures: is a journal focused on the intersection of sustainability, environment and technology from various disciplines in social sciences, and their larger implications for corporation, government, education institutions, regions and society both at present and in the future. It provides an advanced platform for studies related to sustainability and sustainable development in society, economics, environment, and culture. The scope of the journal is broad and encourages interdisciplinary research, as well as welcoming theoretical and practical research from all methodological approaches.