On Interaction of the Green Growth and Environmental Quality in ECOWAS: Environmental Regulation

Environmental regulation and green productivity growth: Empirical evidence on the Porter Hypothesis from OECD industrial sectors

Based on the panel data of provincial units in China from 2000 to 2020, this paper uses the entropy method to calculate agricultural environmental regulation level in China from the perspectives of afforestation projects, water conservancy projects and environmental protection projects. Then, this paper calculates agricultural non-point source pollutant emissions in China by using the unit survey and evaluation method, and calculates agricultural green productivity growth in China by using the SBM directional distance function and Luenberger productivity index. On this basis, the influence of environmental regulation on agricultural green productivity growth in China and its mechanism are empirically analysed. The results show that:(1) During the sample period, agricultural environmental regulation level and agricultural green productivity growth increased significantly, while the emission density of agricultural non-point source pollution decreased significantly; (2) On the whole, environmental regulation significantly promoted agricultural green productivity growth in China, which was mainly reflected in the promotion of agricultural green technology progress change; (3) Environmental regulation can significantly promote agricultural green productivity growth in China through the channel of agricultural innovation investment. The innovation of this paper lies in the measurement of agricultural environmental regulation, and the analysis of the moderating effect of agricultural innovation investment on the impact of environmental regulation on agricultural green productivity growth in China. The research conclusions of this paper verify the ‘Porter Hypothesis’ theory in the field of agriculture, and have guiding significance for China to promote agricultural green productivity growth by relying on environmental regulation.

Green economic growth is the best alternative strategy for sustainable development. Existing literature investigated the determinants of green economic growth in China and provides mixed results. Thus, our study explores the impact of green environmental technology, financial innovation, and environmental regulations on green economic growth by controlling the impact of renewable energy consumption, trade, and education. The study explores the symmetric and asymmetric associations by employing ARDL and NARDL approaches. The ARDL long-run findings display that green environmental technologies, environmental regulations, and financial innovations positively and significantly contribute to green economic growth. However, the NARDL long-run findings infer that positive shock in green environmental technology, financial innovation, and environmental regulation exerts a significant and positive impact on green growth, while negative shock in green environmental technology, financial innovation, and environmental regulation has an insignificant impact on green growth. Based on the findings, the study delivers important policy implications to promote green economic growth in China.

The idea of green growth stresses the necessity for economic expansion while resolving environmental issues, notably climate change. The Internet of Things (IoT) and environmental regulations have the potential to support green growth. Therefore, this study intends to examine the empirical link between the IoT, environmental regulations, and green growth in China by utilizing the autoregressive distributed lag (ARDL) and quantile autoregressive distributed lag (QARDL) methods to analyze data from 1997 to 2021. Data are obtained from reputable local and international sources like the Organisation for Economic Co-operation and Development (OECD), World Development Indicators (WDI), the Energy Information Administration (EIA), and the National Bureau of Statistics of China. Findings derived from the baseline ARDL model prove that the IoT, environmental regulations, renewable energy consumption, and research and development (R&D) encourage long-run green growth. Likewise, the robust model also highlights that the internet, environmental policy stringency, renewable energy consumption, and R&D help encourage green growth. In the short run, environmental policy stringency and the internet are favorably linked to green growth in the robust model, and renewable energy consumption is favorably linked to green growth in the baselines model; however, environmental regulation is negatively linked to green growth. The findings from the QARDL analysis show that the impact of the IoT on promoting green growth is significant across all quantiles. On the other hand, the effects of environmental regulation are more pronounced at higher levels of green growth. These findings imply that policymakers should try to increase the role of digitalization in society by promoting the IoT and the internet to decouple economic growth and environmental pollution. Moreover, the digitalization policy should be supported by implementing strict environmental laws and regulations.

Exploring suitable types and intensities of environmental regulations to promote technological innovation and guide industrial green growth is an essential goal for China. This paper uses the SBM super-efficiency model with the GML index to measure the level of green growth in China’s citrus industry from 2008 to 2019, and examines the impact generated by heterogeneous environmental regulations and the mediating effect of technological innovation using a panel Tobit model. The study found that: (1) From 2008 to 2019, the green growth level of the citrus industry has gradually improved, with an average annual growth rate of 2.7%, and the contribution of technical efficiency is more significant than technological progress. (2) The green growth of the citrus industry is closely related to the intensity and type of environmental regulation. The impact of market-incentive environmental regulation has an inverted U-shape, the impact of guidance-based environmental regulation is U-shaped, and the command-and-control environmental regulation has no significant effect. (3) The mediating effect suggests that guidance-based environmental regulation promotes green growth in the citrus industry by stimulating technological innovation. In contrast, market-incentive environmental regulation inhibits technological innovation and thus discourages green growth in the citrus industry. According to the study results, the government should strive to ensure the effective implementation of environmental laws and regulations, optimize the channels and amounts of investment in environmental governance, strengthen environmental protection-related media campaigns, and guide the citrus industry to break through technological bottlenecks to promote green growth.

The inflow of foreign direct investment (FDI) has both advanced China's economic development process and influenced the ecological quality of China's regions. Under the deepening of economic globalization and the continuous deterioration in environmental quality, the correlation mechanism between foreign direct investment, environmental regulation, and economic growth is becoming increasingly complex. Therefore, based on the slacks-based measure (SBM) model and the Global Malmquist-Luenberger (GML) index, this study measured the level of green economic growth using data from 30 provinces and cities from 2004-2019 and constructed a panel fixed-effect regression model to study the effect of foreign direct investment on green economic growth in China. The study found that foreign direct investment significantly promoted green economic growth in China, foreign direct investment promoted green economic growth through independent innovation and inhibited green economic growth through imitation innovation, and environmental regulation moderated the impact of foreign direct investment on green economic growth. This paper incorporated foreign direct investment, heterogeneous technological innovation, green economic growth, and environmental regulation into the research framework, and thereby further enriched and improved the research on the theoretical mechanism of green economic growth. The research conclusion clarified the influence mechanism of foreign capital on the quality of China's economic development, which was conducive to the formulation of more reasonable policies for attracting investments and to the promotion of the formation of a positive interaction mechanism between environmental regulation and foreign direct investment, which is of great practical significance for China's economy to achieve sustainable development.

Addressing the geographical relocation of the pollution-intensive gray side of low-carbon green production, our study analyzes potential determinants of green and gray growth performance of industrialized/developed countries (IDCs) and industrializing/emerging economies (IEEs) over the 1996–2015 period. We define green growth by low-carbon output, while we link gray growth to comparative advantages of pollution havens. Green and gray growth models include such predictors as domestic income and foreign direct investment (FDI) together with composite indices for globalization, environmental policy stringency (EPS), industrialization, and control of corruption. Considering non-stationarity, cross-section dependency, endogeneity, and heterogeneity concerns, we employ bootstrap and residual-based cointegration analyses followed by long-run estimations using the Common Correlated Effects Mean Group (CCEMG) and Dynamic Ordinary Least Squares (DOLS) estimators and causality examination through Dumitrescu-Hurlin and Emirmahmutoglu-Kose tests. The key findings of the study are as follows: (i) income is positively associated with green growth for both IEEs and IDCs, whereas the income-gray growth nexus is negative for IEEs. (ii) Although inward FDI stocks are positively related to green and gray growth of IEEs and outward FDI stocks are negatively associated with green and gray growth of IDCs, these relationships are mediated by EPS. (iii) Globalization encourages both green and gray growth for IDCs. (iv) Even though EPS inhibits green growth and encourage gray growth in IEEs, these direct effects widely depend on the indirect effects of control of corruption. (v) IEEs’ higher gray growth performance is substantially explained by their increased industrial competitiveness, whereas the link is negative for IDCs. (vi) Control of corruption fosters both green and gray growth in IEEs. Overall, “growing gray” does not necessarily mean “not growing green” and vice versa. Globally, the low-carbon benefits of greening countries may be counterbalanced by the environmental costs of graying economies. From a policy perspective, IEEs need to reinforce environmental policies by green efficiency, green industrialization, and anti-corruption plans to decouple economic growth from carbon dioxide emissions.Supplementary InformationThe online version contains supplementary material available at 10.1007/s11356-021-13127-x.

How R&D expenditure intermediate as a new determinants for low carbon energy transition in Belt and Road Initiative economies

The interaction effects of environmental regulation and technological innovation on regional green growth performance

Towards cities' green growth: The combined influence of economic growth targets and environmental regulations

Green energy, green innovation, and political stability led to green growth in OECD nations

The impact of fintech innovation on green growth in China: Mediating effect of green finance

As the answer to sustainability concerns, green economic growth has gradually attracted considerable attention. Notably, the optimization of the institutional environment contributes to green economic growth from the perspective of new institutional economics. However, few studies have systematically explained the connection between the institutional environment and green growth. In this study, the institutional environment was divided into three dimensions: governmental, legal, and cultural subenvironments. We adopted econometric models with the effect of every dimension on green growth and empirically analyzed with the generalized method of moments, based on Chinese provincial panel data from the years 2000–2016. The results indicated that there was an inverted U‐shaped relationship between China’s institutional environment and its green growth. That is, the institutional environment can initially promote China’s green growth but, if it is not changed, will eventually inhibit it. In addition, the analysis on the three dimensions of the institutional environment highlighted that the role of the cultural subenvironment in green growth is greater than those of the governmental and legal subenvironments.

The path to green economy: Do environmental taxes and renewable energy transition matter in OECD countries?

PurposeThe development of green economy is of academic and policy importance to governments and policymakers worldwide. In the light of the necessity of renewable energy to sustain green economic growth, this study aims to examine the relationship between renewable energy consumption and green economic growth, controlling for the impact of trade openness for Organization for Economic Co-operation and Development countries over the period 1990-2015, within a multivariate panel data framework.Design/methodology/approachTo investigate the long-run relationship between variables, panel cointegration tests are performed. Panel Granger causality based on vector error correction models is adopted to understand the short- and long-run dynamics of the data. Furthermore, ordinary least square (OLS), dynamic OLS and fully modified OLS methods are used to confirm the long-run elasticity of green growth for renewable energy consumption and trade openness. Moreover, system generalized method of moment is applied to eliminate serial correlation, heteroscedasticity and endogeneity problems. The authors used the panel Granger causality test developed by Dumitrescu and Hurlin (2012) to infer the directionality of the causal relationship, allowing for both the cross-sectional dependence and heterogeneity.FindingsThe results suggest that renewable energy consumption and trade openness exert positive effects on green economic growth. The results of long-run estimates of green economic growth reveal that the long-run elasticity of green economic growth for trade openness is much greater than for renewable energy consumption. The estimated results of the Dumitrescu and Hurlin (2012) test reveal bidirectional causality between green economic growth and renewable energy consumption, providing support for the feedback hypothesis.Practical implicationsThis paper provides strong evidence of the contribution of renewable energy consumption on green economy for a wide range of countries. Despite the costs of establishing renewable energy facilities, it is evident that these facilities contribute to the green growth of an economy. Governments and public authorities should promote the consumption of renewable energy and should have a support policy to promote an active renewable energy market. Furthermore, the regulators must constitute an efficient regulatory framework to favor the renewable energy consumption.Social implicationsMany countries focus on increasing their GDP without taking the environmental impacts of the growth process into account. This paper shows that renewable energy consumption points to the fact that countries can still increase their economic growth with minimal damage to environment. Despite the costs of adopting renewable energy technologies, there is still room for economic growth.Originality/valueThis paper provides evidence on the contribution of renewable energy consumption on green economic growth for a wide range of countries. The paper focuses on the impact of renewable energy on economic growth by taking environmental degradation into consideration on a wide scale of countries.