A prior study [42] analyzes the impact of the “resources curse” on the green growth of Chinese cities for 2003–2018 (which was estimated by the Global Malmquist Luenberger (Global ML) index). Based on the results of the difference-in-differences method (DID), the scholars concluded that China could boost green economic growth by providing effective environmental regulations measured by the sulfur dioxide removal rate in the city. In addition, they empirically justify that declining corruption (as the indicator of governance quality) leads to boosting green economic growth. Hou et al. [43] apply Super-SBM techniques to analyze the relationship between income inequality and green economic growth. Based on the empirical results, they confirm that effective environmental regulation can compensate for the negative impact of income inequality on green economic growth. Scholars emphasize that the Chinese government should modernize environmental regulation, which consequently could enhance green economic growth. Pan et al. [44] prove that effective environmental regulations could boost green growth in developing countries that undergo the transformation process. Applying the difference-in-differences method (DID) model, they empirically justify that improving environmental regulations increases green economic growth by 14.2%, and this effect is long term. Li et al. [45] arrive at a similar conclusion on the positive effect of environmental regulation on Chinese green economic growth and confirm the crucial role of green financing in attaining green economic growth. Applying TOPSIS and entropy methods Lin B. and Y. [6] prove the statistically significant impact of environmental regulation on green economic growth in Chinese cities. However, the power of the environmental regulation impact depends on the Chinese regions. The impact of environmental regulation on the green development of China is estimated by means of the Tobit model [46]. Based on the empirical findings, this research confirms that environmental regulation promotes green development in the long term. In addition, Liu et al. [47] empirically prove that environmental regulations restrict the positive impact of digitalization on green economic growth. It is highlighted that the government should provide coherent ecological, financial, and digital policy in the country to attain green economic growth. Luo S. and Zhang S. [48] confirm that green regulation has a statistically significant positive impact on green economic growth. Luo et al. [49] prove the U-shaped effect on the eco-efficiency of China. Scholars emphasize that in the short term, environmental regulation decreases green growth, and in the long term, environmental regulation is conducive to green growth due to enhancing renewable energy and attracting green investment. Similar conclusions on the U-shape relationship between environmental regulations and green economic growth are confirmed by prior studies [50,51,52,53]. In addition, scholars [52] outline that improving environmental regulations reduces the negative impact of FDI on the green economic development of China. Song et al. [54] outline that environmental regulation had a mediating effect on the link between digitalization and green economic growth in Chinese provinces in 2011–2019. Based on the results of the symmetric and asymmetric links among green economic growth, green technologies, innovations, and environmental regulations (applying the linear autoregressive distributed lag model (ARDL)), Su and Gao [55] confirm that environmental regulations positively affect green economic growth in the long term. The results of nonlinear autoregressive distributed lag models (NARDL) show that positive changes in environmental regulations have a statistically significant positive impact on green economic growth. At the same time, the negative shock in environmental regulations does not have a statistically significant impact on green economic growth.

Prior studies [56] do not confirm the impact of the “resources curse” on the green growth of China. At the same time, they maintain that renewable energy capabilities boost green economic growth. Luo S. and Zhang S. [48] prove that renewable energies require appropriate environmental regulations that are conducive to green economic growth in Belt and Road countries. Applying FMOLS and DOLS techniques, Ahmed et al. [57] also confirm that extending renewable energy positively contributes to green economic growth in South Asian economies in 2000–2018 and argue that renewable energy reduces the consumption of traditional energy resources and enhances green GDP generation, which contributes to green economic growth. Aimon et al. [58] show that growth of renewable energy by 1% decreases fuel oil consumption by 0.006%, which, consequently, restricts environmental degradation and contributes to green economic growth. At the same time, scholars prove that green economic growth has a negative effect on declining fuel oil consumption. Improving green economic growth by 1% results in a reduction in fuel oil consumption by 0.07%. Cao L. [59] analyzes the impact of renewable energy on the green growth of E7 developing countries in 2005–2018 by applying second-generation panel cointegration techniques, and his findings show the positive link between renewable energy and the green economic growth index with declining carbon dioxide emissions in the long and short run. Renewable energy is emphasized as the core catalysator of carbon dioxide emissions and green growth in the short term in China [60], while requiring sufficient green finance [61,62,63,64]. The ARDL model is applied to confirm the hypothesis that the green finance tax rate on energy and green tax revenues from energy taxes positively affect renewable energy, which is the core stimulator of green economic growth in Romania [61]. Similar conclusions are obtained by [65] for South Asian countries and by [66] for ten leaders in green growth (Iceland, Denmark, Netherlands, the United Kingdom, Norway, Finland, France, Germany, Sweden, and South Korea), which confirms the core macroeconomics theory [65,66]. Fang et al. [65] elaborate the ordinary least square model (OLS) to confirm that research and development and industry modernization stimulate green economic growth due to enhancing renewable energies and declining carbon dioxide emissions. The links among green growth, green energy, and green finance in China are analyzed for the period of 2011–2019 [67]. Based on the empirical results, it is concluded that green growth positively affects the spread of green energy, and this impact is heterogeneous and asymmetric. Green innovations play a mediating role in the link between green economic growth and green energy; however, the mediating impact of green finance is not significant. A positive impact of renewable energy on green growth is proven for non-OECD countries [68]. However, for OECD countries, this impact is not statistically significant. Furthermore, Taşkın et al. [69] reported controversial results, confirming the positive contribution of green energy to green economic growth despite the high cost of developing relevant infrastructure for renewable energy in OECD countries for the 1990–2015 period.

Based on the Korean experience, Lee K. [70] stresses that energy efficiency is one of the core and effective drivers that allows carbon dioxide emissions to be reduced to attain green economic growth. Data envelopment analysis (DEA) is used to justify the positive relationship between attaining sustainable development goals and the energy efficiency of 20 Asian and Pacific countries [71]. Applying meta-frontier SBM and DEA (data envelopment analysis), Luo S. and Zhang S. [48] study green economic growth through energy efficiency and confirm that the latter has a positive effect on green economic growth. Lee et al. [5] and Khan et al. [72] empirically justify that improving energy efficiency (due to enlarging renewable energy) is the predictor of green economic growth. In addition, Khan et al. [72] emphasize the impact of the governance effect on extending renewable energy and energy efficacy technologies. Kėdaitienė and Klyvienė [73] prove that improving energy intensity and changing the structure of final energy consumption contribute to the economic growth of EU countries, involving green growth. Lin and Benjamin [74] also confirm the coherent conclusions for Shanghai based on the results of quantile analysis. High energy intensity and energy poverty are shown to decrease green economic growth in West African states [75]. Withal, the spread of green energy allows changes in the structure of final energy consumption. Sun et al. [76] maintain that energy efficiency is the crucial determinant of green economic growth and, based on the analysis of the leaders on energy efficiency (France, Germany, the Netherlands, Switzerland, and the UK), demonstrate that technological innovation and knowledge spillover positively contribute to energy efficiency. Moreover, the advancement of research and development capabilities in the countries is needed. Chen et al. [77] assert that energy efficiency depends on energy intensity, structure, and value of final energy consumption, which is conducive to sustainable development goals (clean and affordable energy, decent work and economic growth, industry, innovation and infrastructure, quality education). In addition, they empirically justify that the structural transformation of the economy could provoke a decline in energy intensity and restructure the final energy consumption. Energy efficiency is able to improve by changing the energy consumption structure [78], simultaneously leading to a decline in greenhouse gas emissions. Consequently, it promotes attaining green economic growth and sustainable development [79,80]. Yan et al. [81] indicate that EU countries have different levels of energy efficiency that depend on technological and energy infrastructure, the efficacy of energy policy, and the spread of renewable energy.