Achieving the objectives of the 2030 sustainable development goals agenda: Causalities between economic growth, environmental sustainability, financial development, and renewable energy consumption

Linked Agent
Publisher
Sustainable Development
Date Issued
2022
Language
English
English Abstract
Abstract : As the global concerns regarding climate change and the related environmental adversities continue to persist alongside rapid development of the world economies, the United Nations declared a set of compressive sustainable development goals (SDG) that are to be realized by the end of 2030. These goals are specifically conceptualized to collectively facilitate the attainment of sustainable socioeconomic development while concurrently improving the quality of the global environment. Hence, this study assesses the interlinkages between economic growth, environmental pollution, financial development, and renewable energy use in light of the objectives of SDG8, SDG13, SDG10, and SDG7 by considering the BRICS nations as a case study. Although the previous studies, in this regard, have predominantly focused on specifically scrutinizing the determinants of these four macroeconomic variables of concern, not much importance was shown to map the interrelationships among these variables. The econometric analysis conducted in this study utilizes quarterly frequency data covering the period from 1990-Q1 to 2020-Q4. Overall, the findings from causality and variance decomposition analyses reveal that in the long run these variables are influenced by each other which, in turn, also verifies the cross-linkages between the four SDG of concern. Besides, the causality-related findings appear to be robust when alternate causality estimators are employed. Therefore, based on these critically important causal relationships, a set of interactive SDG-related policies is recommended. KEYWORDS CO2 emissions, economic growth, environmental policy, financial development, Granger causality, renewable energy use, sustainable development goals, variance decomposition
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