College of Economics and Management, Fujian Agriculture and Forestry University, Fuzhou, 350002, China.
Northeast Agriculture University (NEAU), Harbin, 150038, China.
Environ Sci Pollut Res Int. 2023 Jun;30(30):75041-75057. doi: 10.1007/s11356-023-27583-0. Epub 2023 May 20.
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 CO 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 CO emissions, while non-renewable energy consumption significantly contributed to long-term CO emissions. Estimates from the FMOLS technique reflect a significant progressive effect of GDP and GDP on CO emissions, while GDP has a significant adverse effect on CO 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.
石油和天然气等不可再生能源是经济增长的主要驱动力，但也是东北亚国家环境恶化的主要原因。本研究的主要目的是检验 1970 年至 2020 年期间，七个选定的东北亚国家可再生能源消费、不可再生能源消费对 CO2 排放和经济增长的影响。首先，Pesaran、Ullah 和 Yamagata（2008）提出的横截面依存性检验得出，面板数据模型中不存在横截面依存性，因此可以使用第一代面板数据方法。之后，采用 Pedroni（Oxford Bull Econ Stat 61：653-670，1999；Economet Theor 20：597-625，2004）、Kao（J Econom 90：1-44，1999）和 Westerlund（2007）提出的协整检验，发现模型面板变量之间存在长期协整关系。使用面板完全修正最小二乘法（FMOLS）和面板动态最小二乘法（DOLS）的估计技术检测长期变量系数弹性。使用 Dumitrescue-Hurlin（Econ Model 29：1450-1460，2012）面板因果检验检测变量之间的双向因果关系。分析结果突出表明，可再生能源消费、不可再生能源消费、就业劳动力和资本形成对长期经济增长具有显著的渐进影响。研究还得出结论，可再生能源消费显著降低了长期 CO2 排放，而不可再生能源消费则显著促进了长期 CO2 排放。FMOLS 技术的估计反映了 GDP 和 GDP 对 CO2 排放的显著渐进影响，而 GDP 对 CO2 排放有显著的不利影响，从而验证了所选国家组的 N 型 EKC 假设。此外，基于可再生能源消费与经济增长之间的双向因果关系，支持反馈假设。从战略上讲，这项基于证据的实证研究表明，可再生能源是一个有价值的过程，可以通过解决能源安全问题和减少碳排放来保护环境，并为选定国家的未来经济增长做出贡献。
