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Under the dual background of global climate change and regional air pollution, the emission reduction effect of renewable energy has received increasing attention worldwide. However, few studies have evaluated the nonlinear effects and spillover effects of renewable energy consumption (REC) on economy and environment over space and time. In this study, we select panel data from 30 Chinese provinces from 2005 to 2017 and construct multiple models to quantitatively evaluate the nonlinear effects, spatial spillover effects, and spatio-temporal heterogeneity effects of REC on China's economy and the environment. The results show that REC has an N-shaped curve relationship with economic growth and has an inverted N-shaped curve relationship with haze pollution and carbon emissions. Furthermore, we find that the spatial spillover effect of REC is larger than the local effect. Interestingly, REC has a negative impact on economic growth in 40% of provinces, increases haze pollution in 30% of provinces, and increases carbon emission in 60% of provinces. It is worth noting that the current impact of REC on carbon emissions in China is at a stage of switching from negative to positive effects (60% of provinces have a positive impact). • REC has an inverted N-shaped curve relationship with environmental pollution. • REC has an N-shaped curve relationship with economic growth. • The spatial spillover effect of REC is larger than the local effect. • REC can decrease economic growth in 40% of China's provinces. • REC can increase haze pollution and carbon emission in 30% and 60% of provinces. [ABSTRACT FROM AUTHOR]

Although the impact of fossil fuel consumption is known worldwide, oil-producing countries stay away from using renewable energy sources due to commercial concerns, which causes an increase in global warming. We investigated the relationship between economic growth, renewable energy consumption, and ecological footprint in the oil-producing USA, Russia, Saudi Arabia, Canada, China, Brazil, Kuwait, and Nigeria for 1999–2017 using a dynamic panel data analysis and panel causality analysis. Our motivation was to demonstrate the oil-producing countries' growing ecological footprint/environmental pollution and the influence on global warming. Our objective is to analyze how economic growth and renewable energy consumption contribute to the ecological footprint in countries whose growth is based on oil production. We employed a dynamic Two-Step System Generalized Method of Moments test and Dumitrescu-Hurlin Heterogenous Panel Causality Test. Our findings demonstrate a significant effect of economic growth on ecological footprint, confirming the Pollution Haven Hypothesis and no significant effect of renewable energy consumption on ecological footprint. Future researchs based on our analysis may determine the optimum distribution of conventional and renewable energy production that guarantees economic growth while reducing global warming. The first contribution of our study to the literature is to examine the related nexus through dynamic panel data analysis, unlike the studies using static analysis. The second contribution is to identify the damage done to our planet by oil-producing countries' efforts to maintain their economic growth despite environmental degradation. In other words, by combining these two, our study's contribution is identifying the Pollution Haven Hypothesis by dynamic and causality analyses for oil-producing countries. Our findings demonstrate that; a) renewable energy consumption does not influence and is not a cause of the ecological footprint, b) economic growth is a cause and has an influence on the ecological footprint for most oil-producing countries. In our test results, it has been found out that a 1% increase in economic growth will increase the ecological footprint by 0.02828%. • Economic growth affects and cause of the ecological footprint. • Renewable energy does not affect and is not a cause of the ecological footprint. • Oil-producing countries' renewable energy investments are not enough. • The Pollution Haven Hypothesis is valid for most oil-producing countries. [ABSTRACT FROM AUTHOR]

This paper examines the nexus between renewable energy consumption (REC) and Gross Domestic Product (GDP) in G7 countries. To this end, we analyse data from 1980 to 2020 employing Toda and Yamamoto (1995) time causality test, Lemmens et al. (2008) frequency causality test and Hatemi-J's (2012) asymmetric causality approach. The findings differ across countries and are as follows. The conservative hypothesis is validated for the US and Canada. Specifically, we find significant and positive causal effect from GDP to REC in the long-term horizons (periods greater than 15 years for the US and 7 years for Canada). The growth hypothesis is confirmed for Germany. Precisely, significant and positive causal impact is shown from REC to GDP in the long-run horizons (periods longer than 7 years). The neutrality hypothesis is supported for France, the UK, Italy and Japan as there is no significant causal link at any time horizon. This is likely because the clean energy consumption does not reach a threshold beyond which it will start to have considerable interaction with economic growth. This study provides policymakers a better understanding of the REC-economic growth nexus to formulate appropriate policies. • We examine the nexus between renewable energy consumption and economic growth in G7 countries. • We use Toda and Yamamoto (1995) and Lemmens et al. (2008) tests and Hatemi-J's (2012) asymmetric causality approach. • For the US and Canada, significant and positive causal effect is shown from GDP to REC in the long-term horizons. • For Germany, significant and positive causal impact is displayed from REC to GDP in the long-run horizons. • For France, the UK, Italy and Japan, no significant causal link is found between REC and economic growth. [ABSTRACT FROM AUTHOR]

Under the downward pressure of the economy, China's extensive economic growth that relies on factor input is difficult to sustain. Scientific analysis of the industrial restructuring and energy consumption has become the key to realizing China's economic growth from high-speed to high-quality. Based on the fully-modified least square method and panel vector error correction model, this paper explores the equilibrium relationship and Granger causality among the industrial restructuring, energy consumption and economic growth at aggregated and disaggregated levels. The results show that: (1) The effect of industrial structure rationalization on economic growth is higher than that of industrial structure upgrading. When emphasizing industrial structure upgrade, the more reliable industrial policy to achieve China's sustainable economic growth is to pay attention to the industrial structure rationalization, especially in western China. (2) The impacts of natural gas and renewable energy consumption on economic growth are much smaller than coal and electricity consumption; more energy policies should be designed to encourage clean energy development. • The industrial structure rationalization has highest contribution to the economic growth of eastern China, followed by central and western China. • There exists unidirectional causality from industrial structure upgrading to structure rationalizing in western China and bidirectional causality between them in central China. • Effects of natural gas and renewable energy consumption on economic growth are much smaller than coal and electricity consumption. • Unidirectional long-term causality from renewable energy to economic growth exist in each sub-region. [ABSTRACT FROM AUTHOR]

We employ a non-parametric modelling technique to examine the time-varying impact of renewable and non-renewable energy consumption on economic growth. The specific nonparametric method that we employ is the local linear dummy variable estimation (LLDVE) method, which we apply to OECD and non-OECD panels for the period 1990 to 2015. While previous studies employing parametric models have recognised the existence of non-linearities and instability in the relationship between renewable (and non-renewable) energy consumption and economic growth, the LLDVE method has the advantage that it does not make any assumptions about functional form and, hence, is better able to approximate the non-linear relationship. Our estimates suggest that non-renewable energy consumption exerts a positive and significant impact on economic growth across OECD nations with the coefficient function exhibiting an upward trajectory over time. The impact of renewable energy consumption on economic growth, however, is statistically indistinguishable from zero in these countries for most of the study period. Both renewable and non-renewable energy consumption promote economic growth in non-OECD countries, suggesting that developing countries may play an important role in the transition process to renewables despite constraints in technical progress. [ABSTRACT FROM AUTHOR]

A boom in renewable energy consumption as a percentage of final energy consumption (REC) has a significant impact on cleaner production and environmental sustainability. However, studies on REC as for an individual country-case and panel case approach for top emitters are rare. Against this backdrop, this study investigates the long-run drivers of REC by using a time series data from 1990 to 2015. The FMOLS-grouped results indicate that economic growth and trade openness increase REC whereas population growth has a negative but significant impact on REC. To check for causal links, the innovating accounting approach using variance decomposition analysis is applied. The results show that there is a unidirectional causality running from economic growth, trade openness, and population growth to REC. Further, the predictive accuracy of the FMOLS based econometric output and the bi-directional long short-term memory (Bi-LSTM) is analyzed. The Bi-LSTM formulated algorithm outperformed the econometric output. The Bi-LSTM is utilized to forecast REC to the year 2030. The output from the Bi-LSTM shows that China, the US, India, the Russian Federation's, and Japan's REC will hit ∼11.3395, ∼11.1245, ∼34.6969, ∼2.9097, and ∼7.4859, respectively. The US and Japan's REC levels will increase while that of China, India, and Russia Federation will decrease. As a policy implication, new policy directives for China, India, and the Russian Federation are required to boost REC levels. [ABSTRACT FROM AUTHOR]

The main purpose of this paper is to develop an efficient multi-stage methodology to predict carbon dioxide emissions based on two important variables including the energy consumption and economic growth using the clustering, prediction machine learning techniques, and dimensionality reduction. To do so, we use the self-organizing map clustering algorithm to cluster the data and the adaptive neuro-fuzzy inference system and artificial neural network to construct the prediction models in each cluster of the self-organizing map to predict carbon dioxide emissions considering a set of input parameters including economic growth and energy consumption in Group 20 nations. Furthermore, we use the singular value decomposition for dimensionality reduction and missing values' prediction in the dataset. The results of the analysis of a real-world dataset found that the developed multi-stage approach was capable of predicting the carbon dioxide emissions on two indicators. To validate the proposed method, the results are compared with other existing methods. The outcomes demonstrate that the adaptive neuro-fuzzy inference system and artificial neural network techniques combined with the self-organizing map and singular value decomposition technique provide 0.065 accuracy in terms of the mean average error. In addition, when comparing singular value decomposition-self-organizing map-adaptive neuro-fuzzy inference system method with the singular value decomposition-self-organizing map-adaptive-artificial neural network method, the singular value decomposition-self-organizing map-adaptive neuro-fuzzy inference provides with 0.104 accuracy in predicting CO 2 emissions. Moreover, the multiple linear regression provides the worst accuracy (0.522) results compared with the artificial neural network and adaptive neuro-fuzzy inference system techniques. The analysis regarding the relationship between economic development, carbon dioxide emissions, and the energy consumption is extremely vital from the energy and economic policy-making aspects in Group 20 countries given that the primary focus of this group has been the governance of the global economy. [ABSTRACT FROM AUTHOR]

This study evaluates the potential impact of promoting non-fossil fuel energy on India's economic growth in a regime based non-linear asymmetric framework. The empirical outcomes affirm regime-shift and asymmetric cointegrating links of the non-fossil fuel energy usage represented by combustible renewables & waste (CREW) and alternative & nuclear energy (ANEN) with the gross domestic product (GDP). The study establishes the existence of threshold cointegration between CREW and GDP. The causal links between CREW and GDP are regime variant and asymmetric, whereas the dynamics between ANEN and GDP are proven to be asymmetric and regime invariant. CREW and GDP supports a feedback hypothesis in a normal regime and a conservation hypothesis in a rare regime. The asymmetric causality between CREW and GDP validates an inverse feedback hypothesis and a negative growth hypothesis. A negative growth hypothesis is also ascertained between ANEN and GDP. The empirical findings convey meaningful insights for government and policymakers. • Examines the link between non-fossil fuel energy and economic activity in India. • Regime shifts, threshold and asymmetric cointegration found. • Feedback hypothesis in a normal regime is demonstrated in long run. • Positive change in combustible renewables & waste causes economic growth adversely. • Negative changes in alternative & nuclear energy drives positive economic growth. [ABSTRACT FROM AUTHOR]

Designing a comprehensive policy framework for ascertaining sustainable development is a problem faced by most of the countries around the globe, and the developed nations are no exception to that. Environmental awareness-oriented policy design for achieving sustainable development goals is a challenge for the developed nations, and there lies the contribution of this study. This study analyzes the impact of renewable energy on carbon emissions, in presence of education, natural resource abundance, foreign direct investment, and economic growth for the Organization for Economic Co-operation and Development countries over the period of 1990–2015. Second generation methodologies are adapted for the empirical estimation. The results show the stimulating role of renewable energy consumption in shaping environmental quality. Education declines carbon emissions. Natural resource abundance and foreign direct investment deteriorate environmental quality. Moreover, the time series individual country analysis also confirms that renewable energy has a positive impact on economic growth. The heterogeneous causality analysis reveals the feedback effect, i.e., bidirectional causal associations among carbon emissions, education, and renewable energy consumption. This empirical evidence suggests that countries should increase investment in education and renewable energy sectors and plan for research and development in renewable energy for ensuring environmental sustainability. Image 1 • This study analyzes the impact of educational attainment on carbon emissions. • Study has been done for 27 OECD countries over the period of 1990–2015. • Results show stimulating role of educational attainment in shaping environmental quality. • Natural resource abundance and FDI deteriorates environmental quality. [ABSTRACT FROM AUTHOR]

Environmental degradation is an important threat to sustainable development. Economic growth and fossil fuel-based energy consumption are main factors causing environmental pollution. The use of renewable energy as an alternative for fossil fuels can help to reduce environmental pollution, and thus, sustainable development can be achieved. From this point of view, hydropower is the most widely used renewable energy source in several countries. However, the effects of hydropower energy on the environment are controversial. To add a new dimension to the discussion, this study investigates the relationship between hydropower energy consumption, ecological footprint and economic growth for the top six hydropower-consuming countries within the framework of the environmental Kuznets curve (EKC) hypothesis. The study employs newly developed cointegration and causality tests with smooth structural changes over the period 1965–2016. The findings of the Fourier bootstrap ARDL procedure demonstrate that no cointegration exist between the variables. Therefore, the EKC hypothesis is not valid for Brazil, China, Canada, India, Norway and the US. Furthermore, the findings of the Fourier Toda-Yamamoto causality test suggest unidirectional causality running from hydropower energy consumption to economic growth in Brazil, and bidirectional causality between these variables in China. In the case of the top six hydropower-consuming countries, no evidence was found for a causal relationship between hydropower energy and ecological footprint. Overall, these results are important for policy makers. Hydropower energy plays a crucial role in China and Brazil's economic growth policies. On the other hand, hydropower energy consumption and economic growth do not have a role in mitigating the ecological footprint in six countries. For this reason, different types of renewable energy consumption should be taken into consideration by countries for the solution of environmental problems. Image 1 • Fourier unit root, causality and cointegration tests are employed. • The EKC does not hold in the top six hydropower energy consuming countries. • No causal nexus between hydropower energy consumption and ecological footprint. • Hydropower energy is not used effectively enough to reduce ecological footprint. • Other renewable energy sources need to be promoted for sustainable development. [ABSTRACT FROM AUTHOR]