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An empirical analysis of the impact of renewable and non-renewable energy consumption on economic growth and carbon dioxide emissions: evidence from seven Northeast Asian countries

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Abstract

Oil and natural consumption are non-renewable energy sources that are the main drivers of economic growth, but these energy sources are also the main causes of environmental degradation in Northeast Asian countries. The main objective of this study is to examine the impact of renewable energy consumption, non-renewable energy consumption on CO2 emissions, and economic growth in seven selected Northeast Asian countries during the period 1970–2020. First, the cross-sectional dependence test recommended by Pesaran, Ullah, and Yamagata (2008) concludes that there is no cross-sectional dependence in the panel data model, so it is feasible to use the first-generation panel data methods. Later, cointegration tests proposed by Pedroni (Oxford Bull Econ Stat 61:653–670, 1999, Economet Theor 20:597–625, 2004), Kao (J Econom 90:1–44, 1999), and Westerlund (2007) were adopted, revealing long-term cointegration relationships among model panel variables. Long-term variable coefficient elasticities were detected using the estimation techniques of panel fully modified ordinary least squares (FMOLS) and panel dynamic ordinary least squares (DOLS). Two-way causality of variables was detected using the Dumitrescue-Hurlin (Econ Model 29:1450–1460, 2012) panel causality test. The results of the analysis highlight the significant progressive effects of renewable energy consumption, nonrenewable energy consumption, employed labor force, and capital formation on long-run economic growth. The study also concluded that renewable energy consumption significantly reduced long-term CO2 emissions, while non-renewable energy consumption significantly contributed to long-term CO2 emissions. Estimates from the FMOLS technique reflect a significant progressive effect of GDP and GDP3 on CO2 emissions, while GDP2 has a significant adverse effect on CO2 emissions, thus validating the N-shaped EKC assumption in selected group of countries. Furthermore, the feedback hypothesis is supported based on the two-way causality between renewable energy consumption and economic growth. Strategically, this evidence-based empirical study demonstrates that renewable energy is a valuable process that can protect the environment and contribute to future economic growth in selected countries by addressing energy security and reducing carbon emissions.

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Data availability

The data that support the findings of this study are openly available in World Development Indicator page published by (World Bank 2020), at https://databank.worldbank.org/source/world-development-indicators.

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Funding

This was supported by a National Foundation Project: Statistical research on the evaluation index and formation Mechanism of 516 rural revitalization in China (No.: 19BTJ047).

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Authors and Affiliations

  1. College of Economics and Management, Fujian Agriculture and Forestry University, Fuzhou, 350002, China

    Qiang Wang & Xuerong Xu

  2. Northeast Agriculture University (NEAU), Harbin, 150038, China

    Arshad Ali

  3. Business School, Zhengzhou University of Industrial Technology, Henan, 451199, China

    Yuanchun Chen

Authors
  1. Qiang Wang
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  2. Arshad Ali
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  3. Yuanchun Chen
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  4. Xuerong Xu
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Contributions

A.A. (Ali), Q.W (Wang), and Y.C (Chen) contributed to the conceptualization of the study, analysis, design, and conclusions; reviewed the manuscript; and approved the final submission. X.X. (Xu) conceptualized the study, review, software data curation, and editing and literature search.

Corresponding author

Correspondence to Xuerong Xu.

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The study obtained ethical approval from Fujian Agriculture and Forestry University Fuzhou 511 350002, China

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The authors declare no competing interests.

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Wang, Q., Ali, A., Chen, Y. et al. An empirical analysis of the impact of renewable and non-renewable energy consumption on economic growth and carbon dioxide emissions: evidence from seven Northeast Asian countries. Environ Sci Pollut Res 30, 75041–75057 (2023). https://doi.org/10.1007/s11356-023-27583-0

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  • DOI: https://doi.org/10.1007/s11356-023-27583-0

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