Search

This study aims to provide insights into the decoupling of GDP growth and greenhouse gas (GHG) emissions in Morocco, a developing country with the ambitious goals of reducing GHG and strongly vulnerable to the negative effects of climate change. The Engle-Granger cointegration method was used in addition to the Tapio elastic analysis based on annual time series data from 1990 to 2018. The cointegration test indicates a significant long-term relationship between greenhouse gas emissions and Gross Domestic Product with a coefficient equal to 0.85. On the other hand, Tapio's decoupling index method presents mixed results both by pollutant and by time period. Nevertheless, total greenhouse gas emissions, with a decoupling index valued at 0.7, exhibit a weak impact decoupling throughout the entire sample period wherein emissions continue to grow at a lower rate than the Gross Domestic Product. The findings are coherent with the view that more aggressive carbon pricing initiatives (CPI) policies will likely be necessary to achieve the ambitious goals set by the Moroccan government to achieve absolute decoupling. [Display omitted] • Engle-Granger cointegration and Tapio's elastic analysis to study decoupling. • One of the first decoupling studies done for North Africa particularly Morocco. • Long-term relationship found between Gross Domestic Product and greenhouse gases. • Weak decoupling state was the most frequent in Morocco between 1990 and 2018. • Need for more aggressive policies such as carbon pricing initiatives (CPI). [ABSTRACT FROM AUTHOR]

The significance of environmental quality for the movement of human capital and economic development is growing. This study utilizes the difference-in-difference (DID) approach to analyze the effects of the implementation of new ambient air quality standards (NAAQS) on economic development and investigate its underlying mechanism. The research indicates that the NAAQS promotes urban economic growth, and this impact tends to progressively intensify over time. According to the analysis of the mechanism, the NAAQS had a significant impact on the city's human capital, which in turn contributed to economic growth. The analysis of heterogeneity indicates that the NAAQS promotes economic growth primarily in the eastern region, in large and medium-sized cities, and in cities where the government pays more attention to environmental protection. This study offers a new explanation for how environmental information disclosure (EID) promotes economic growth and provides policy enlightenment for local governments on how to increase talent inflow. [Display omitted] • New ambient air quality standards (NAAQS) are taken as a quasi-natural experiment. • The generalized multiperiod DID method is used in this paper. • NAAQS can promote economic growth. • Human capital structure plays an intermediary role between NAAQS and economic growth. • The policy effects are affected by the heterogeneity across cities. [ABSTRACT FROM AUTHOR]

Bearing in mind the devastating nature of climate change, the question of how climate change affects economic growth is becoming increasingly important. The aim of this paper is to answer this question by eliminating the most important methodical shortcoming of the available literature. The analysis is based on an advanced plug-in model averaging procedure that allows taking into account a very large number of potentially important growth determinants. The results of the analysis show that the growth of CO 2 and CH 4 emissions by 1%, increases on average the economic growth rate by 0.00132 and 0.00537 percentage points, respectively. In addition, an increase in surface temperature change by one degree Celsius results in an average increase in the rate of economic growth by 0.865 percentage points. Finally, increasing the number of climate-related disasters by one leads to an average increase in the economic growth rate of 0.115 percentage points. The obtained findings also reveal the impact of climate change is very heterogeneous across countries. Such results imply that the current extent of global warming and climate change does not yet have a dominant negative impact on economic growth. • The impact of climate change on economic growth is very heterogeneous. • The average effect of climate change on economic growth is still positive. • Surface temperature change increase by Celsius degree, increases growth by 0.865 pp on average. • Surface temperature change doesn't affect growth in at least 30% of countries. • The negative impact of climate change on economic growth is still relatively rare. [ABSTRACT FROM AUTHOR]

Urban green space (UGS) is susceptible to shocks from multiple sources, including the economy and governance. It is now a global policy challenge to ensure the sustainability and livability of cities. Nevertheless, available studies have reached contradictory conclusions regarding the economic impact on UGS. Using statistical data, empirical studies in the Chinese context failed to differentiate between built-up areas and municipalities and neglected data matching within the study area. To address these gaps, this study explored the relationship between the economy and UGS at various quantiles by constructing unconditional quantile regression (UQR) models using panel data from 283 Chinese cities (2001–2019). The relationship between economic growth and the total area of UGS in the municipal zone (ugs_area) and UGS coverage of built-up areas (ugs_rate) was generally positive and statistically significant, according to the analysis. Furthermore, the study observed heterogeneity in the relationship between the economy and ugs_area and ugs_rate across different quantiles, indicating a growing presence of UGS appearing in the periphery of built-up areas. Cities strived to increase ugs_area and ugs_rate to meet the National Garden City (NGC) standards. After NGC designation, ugs_area and ugs_rate decreased significantly. Moreover, the positive correlation coefficient between the economy and UGS in provincial capital cities was considerably greater than in non-provincial capital cities. This study contributes to UGS research by revealing the nonlinear impact of driving factors. In addition to distinguishing between UGS in municipal districts and those specifically in built-up areas, this study quantifies the impact of governance variables. The study provides a valuable resource for planning UGS in China and promoting harmonious integration of economic growth, governance, and UGS in rapidly developing cities. [Display omitted] • We explored the effect of multiple factors in shaping the UGS. • This study includes panel data of 283 cities (2001–2019) using econometric methods. • Economic growth is pushing UGS to the urban fringe, despite benefiting UGS growth. • Economic impact on ugs_area is stronger in provincial capitals. • Upon designating as an NGC, the citie's ugs_area and ugs_rate significantly decline. [ABSTRACT FROM AUTHOR]

The pursuit of sustainable development has become a prevalent goal in numerous countries. Therefore, renewable energy development is deemed the prime alternative, as it not only curtails CO2 emissions but also stimulates economic prosperity. Hence, there is a need to investigate rational options for renewable energy development. This paper utilises a research framework that combines linear and non-linear modelling. The specific results are as follows. The study's findings reveal that wind, solar and hydro energy can each promote economic growth and lower carbon emissions. Nevertheless, wind energy exhibits the most effective reduction in emissions, followed by solar energy, and lastly, hydro energy. When it comes to promoting economic development, hydro energy proves to be the most effective, followed by wind energy and then solar energy. Additionally, a panel threshold model is utilised to assess further the CO 2 reduction for solar, wind, and hydro energy across a range of economic levels. The results indicate a double threshold effect for wind energy, whereby the effectiveness of CO 2 suppression initially increases and then decreases as the economic level rises. In contrast, the use of solar power displays a sole threshold effect that incentivizes CO 2 emissions at sub-threshold economic levels, yet significantly curbs them beyond it. Similarly, hydro energy also demonstrates a single threshold effect, but lacks statistical significance below the established threshold and actually heightens carbon emissions above it. Our observations can assist in creating sustainable renewable energy development strategies. [Display omitted] • Investigating the impacts of solar, wind, and hydro on economic growth and carbon emission. • Using the linear and nonlinear panel data in 22 countries from 2001 to 2020. • Solar, wind, and hydro contribute to economic growth and carbon emissions reduction. • Countries with a good economy prioritize wind and solar, while others prioritize hydro and wind. [ABSTRACT FROM AUTHOR]

The climate crisis is recognized as one of the world's most serious concerns, posing a threat to environmental, social, and economic growth. However, previous work has failed to address the dynamic effects through which economic growth may affect green growth and climate crisis. In this research, we take a closer look at the impact of carbon emissions, eco-innovation adoption, and international collaboration on economic growth and the influence of economic growth on green growth. This paper used the generalized method of moments (GMM) for 54 African countries from 2010 to 2019, allied with an imbalanced panel of 540 observations. This paper finds a positive relationship between carbon emissions, eco-innovation international cooperation, and economic growth with p-values lower than 0.047. Our study discovers economic growth's robust and positive impact on green growth with a p-value of 0.009. This research finds a three-pronged mediating effect of economic growth between its driving factors and green growth. Lastly, this paper furnishes new visions into the argument over economic growth versus green growth. It informs policymakers of the need to pay attention to the growing effect of eco-innovation driving factors on attaining sustainable and greener growth and climate crisis mitigation. [ABSTRACT FROM AUTHOR]

This study aims to investigate the impact of renewable energy consumption on the economic growth of G7 countries and explore the potential nonlinear relationship between the two variables. Initially, the NARDL model is employed to analyze the G7 countries, allowing for the control of nonlinear relationships and considering asymmetric effects. The findings of the NARDL model reveal an asymmetric long run cointegration relationship between renewable energy consumption and economic growth in Canada and the US, while other countries show different dynamics. Subsequently, a causal dynamic impact analysis is conducted to gain further insights into the relationship between renewable energy consumption and economic growth. In the next step, the advantage of panel data analysis is utilized to investigate the overall impact across all G7 countries. For this purpose, the study extends the NARDL model to the PNARDL (Panel Nonlinear Autoregressive Distributed Lag) model, which facilitates the control of asymmetric effects and nonlinearity in the panel data model. In this context, this study is one of the first studies to control the nonlinearity in panel data analysis. The results from the PNARDL model demonstrate that renewable energy has a positive long-term relationship with economic growth in G7 countries; however, this relationship is statistically insignificant. [ABSTRACT FROM AUTHOR]

This study investigates the impact of trade on environment and economic growth in G20 countries from 1990 to 2019, for environmentally sensitive goods (ESGs). Traditional and modern approach of hypothesizing Environmental Kuznets Curve (EKC), are employed. Cross-Sectional-Autoregressive-Distributed Lag (CS-ARDL) model is used to determine short-run and long-run cointegration between environment, growth and trade variables. To analyze the asymmetric impacts of environmental stringency on carbon emissions, Nonlinear Autoregressive Distributed Lag (NARDL) model is used. The results demonstrate that trade-induced EKC of ESGs for G20 is inverted-U shaped. Further, the study shows that trade-induced economic growth results in higher carbon emission, but mitigates environmental degradation at an early stage. Stringency has asymmetric effects on carbon emission, as observed from the findings. Given the controversial nature of research on the environmental impact of trade, particularly with respect to environmentally sensitive items, the present study is unique in terms of selecting the research topic and adds specific value to the literature in comparing the relationship between economic growth and environmental quality, with and without-trade, of toxic product. Moreover, the study highlights the importance of an asymmetrical analysis of the relationship between legislative strictness and environmental degradation from a policy-making perspective of G20. • This is a panel study accounting for trade-induced economic growth in G20 economies. • The study mainly revolves around the trade in environmentally sensitive goods. • Both the traditional and modern approaches for EKC framework have been employed. • The study analyzes the asymmetric impacts of environmental stringency on carbon emissions. • The results reveal that trade-induced growth is more pollutive and technologically advanced in the G20. [ABSTRACT FROM AUTHOR]

Climate change has steadily gained attention as the global economy has grown more quickly, preventing continued high-quality economic growth. In this context, the eco-innovation concept has recently risen to the top of the list of academic research topics since it is a crucial tool that combines reduced environmental effects with a favourable socioeconomic impact. Nevertheless, the environmental situation is not improving despite the increasing eco-innovation level. From one perspective, instead of concentrating on how eco-innovation lessens carbon emissions, this research explores the indirect effect of carbon emissions on the GDP-eco-innovation nexus. From another perspective, since FDI might lessen harmful pollution, this research analyses the indirect effect of FDI on the economic growth-eco-innovation nexus. Therefore, this paper highlights the relationship between eco-innovation and economic growth (GDP), considering the dual mediating roles of carbon emissions and FDI. First, we examine the effects of GDP on eco-innovation activities in nine MENA countries from 2000 to 2019 using the geographic Durbin model based on spatial panel data. Second, this paper analysed the dual mediating effect of carbon emissions and FDI using the spatial stepwise regression model. The findings of this paper are as follows: (i) GDP positively impacts eco-innovation activities, and (ii) carbon emissions and FDI mediate the GDP-eco-innovation nexus. Therefore, GDP, FDI, and carbon emissions are significant drivers of eco-innovation. This research represents an essential step towards a better understanding of the need to support the transition to sustainability. [ABSTRACT FROM AUTHOR]

Information and Communication Technology (ICT), especially internet-use and technological innovation are argued to have brought significant structural changes that drive economic growth. The current study verifies this argument using data for 16 emerging economies from 2000 to 2018. In this analysis, we have investigated the effects of ICT, innovation, electricity-consumption and renewable power generation, on the economic growth of the emerging economies. Using Instrumental-Variable GMM and fixed-effects regression with Driscoll-Kraay standard-errors, it is found that, ICT not only increases economic growth monotonically, but also increases the effectiveness of financial development on growth. However, ICT is also found to accentuate the negative effects of trade on economic growth. In order to account for the heterogeneities among these economies, both conditional and unconditional panel quantile estimators have been used for an income-level analysis. This shows that internet-use increases growth significantly in the lower and middle-income quantiles; innovation is found to have significant negative effects on growth, except for the highest income-quantile, while the positive growth-effects of electricity-consumption are confirmed across all quantiles. These findings suggest that the emerging economies should increase internet-connectivity to induce network-effect and to improve their capital markets, while also augmenting renewable electricity generation for environmentally-sustainable economic growth. • Internet-use increases economic growth monotonically for the overall sample of emerging economies. • Internet-use increases growth significantly in the lower and middle-income quantiles. • Innovation is found to have significant negative effects on economic growth, except for the highest income-quantile. • Electricity consumption significantly increases growth, but renewable power generation have insignificant effects. • The interaction of internet-use with trade and financial development are significantly negative and positive respectively. [ABSTRACT FROM AUTHOR]

Understanding the economic consequences of climate change has become necessary for economists as evidence indicates that climate is changing and will have detrimental consequences in the upcoming decades, especially in developing countries. Accordingly, this study examines the consequences of climate change on economic growth in Iran located in the mid-latitude belt of arid and semiarid regions on Earth. The present study implements a dynamic integrated assessment model to evaluate the potential impact of climate change on per capita output, per capita consumption, capital per worker, input prices, and welfare over the current century. Two classes of climate change scenarios from CMIP3 (A2 and A1B) and CMIP5 (RCP 4.5, RCP 6.0, and RCP 8.5) under two assumptions of damage function known as "W-damage" and "DS-damage" were examined. In addition, three channels of damage –current production, productivity growth, and capital depreciation–were investigated. In general, the simulation results revealed a significant effect on the selected variables. Nevertheless, the effects were strongly dependent on climatic scenarios and assumptions about the damage function. The consequences of climate change under DS-damage were far more considerable than those under W-damage. The effects of capital damage from climate change were also more significant compared to those of other damage channels. It was revealed that the fall in consumption and welfare was far higher than the corresponding output reduction. When climate change damages from all examined channels were considered, capital per worker was dramatically affected. In particular, under the DS-damage assumption, it tended to decline over the study horizon. This happens while the contribution of capital to production is lower than expected for developing economies. [ABSTRACT FROM AUTHOR]

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]

Political institutions play a key role in countries' environmental footprints since they govern environmental policies. Democracy is an important institutional variable that can exacerbate or alleviate the ecological footprint (EF). The limited literature on democracy and EF association unfold conflicting results. Therefore, this empirical research studies the effect of democracy on EF in Pakistan, where various strict policies have weakened democracy and the country has also been severely affected by climate change. The study employs the novel Augmented ARDL (AARDL) approach to quantify the impact of democracy on EF by including population density, clean energy, and economic growth. The findings from the AARDL method unfold cointegration among variables. The long-run results reveal that democracy is negatively associated with EF. The results also suggest the Environment Kuznets Curve (EKC) hypothesis between EF and economic growth while accounting for democracy in the model. Hence, the study concludes that democracy is a significant driver of environmental sustainability. Further, the estimates of the AARDL also support a mitigating impact of clean energy on EF, while population density upsurges EF. Finally, the AARDL based causality test is applied, which disclosed causality between most regressors and EF. Lastly, detailed policy implications are directed. [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]

Green growth, a-growth, post-growth and degrowth are prominent concepts on the role of economic growth for achieving environmental sustainability. In this article, we investigate the attitudes of environmental protection specialists towards these concepts by conducting a survey with employees of the German Environment Agency (UBA). We develop three measures of attitudes towards the concepts: An implicit position based on responses to statements related to the debate on economic growth and the environment, a position choice based on choosing one concept without referring to its name and an explicit position based on choosing a concept with reference to its name. The analysis leads to four major results. (1) Environmental protection specialists predominantly express a preference for growth-critical concepts (a-growth/post-growth and degrowth) as compared to green growth. (2) A-growth/post-growth is the most favoured concept. (3) The results are stable for all three attitude-measures. (4) Specialists with more knowledge on the concepts are even more likely to prefer growth-critical concepts. Our results further support previous empirical findings that a large share of people and, in particular, specialists are in favour of growth-critical concepts, making policy-options towards such concepts more feasible. [Display omitted] • Environmental protection experts favour growth-critical concepts over green growth. • The most favoured concepts are a-growth and post-growth. • Experts with more knowledge on the topic tend to prefer growth-critical concepts. • Expert opinions support environmental policies beyond 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]

The implementation of environmental regulation needs to consider not only pollution control but also its impact on economic growth. Using the provincial panel data in China from 2000 to 2017, this paper constructs dynamic spatial panel models and employs system GMM approach to evaluate the nonlinear and spatial effects of environmental regulation on economic growth and CO 2 emissions, respectively. The results suggest that, first, environmental regulation presents a significant "N"-shaped effect on economic growth and an inverted "N" effect on CO 2 emissions at the national level and in the eastern and central regions; while the effects are both"N"-shaped in the western region. Second, environmental regulation presents significant spatial effects on economic growth and CO 2 emissions. The enhancement of regional environmental regulation helps the economic growth and CO 2 emissions reduction in neighboring provinces at the national level and in the eastern and central regions, however, the spatial effects are opposite in the western provinces, proving the co-exists of "race to the top" and "race to the bottom" strategies of environmental regulation competition among China's regions. Third, the effects of environmental regulation on economic growth and CO 2 emissions are affected by FDI, and the moderating effect of FDI is regional heterogenous. • Building a dynamic spatial panel model based on the spatial spillover theory. • Proving an "N"-type effect of environmental regulation on economic growth. • The effect of environmental regulation on CO 2 emissions is regionally different. • Environmental regulation affects the role of FDI on economy and CO 2 emissions. • The spatial spillover effects of environmental regulation are proved. [ABSTRACT FROM AUTHOR]

This study employs spatial simultaneous equations models with the Generalized Spatial Three-Stage Least Squares (GS3SLS) method to evaluate the interrelationship between economic growth and air pollution under local government competition for China's "2 + 26" cities from 2007 to 2016. The results show an unbalanced spatial agglomeration effect of economic growth and air pollution across the region. Findings indicate that air pollution accompanies economic growth in the "2 + 26" cities, and economic growth has a U-shaped relationship with air pollution. Moreover, tax income and foreign investment competitions increase air pollution. Suggestions for the "2 + 26" cities include organizing a cross-regional agency for integrated management of the economy and air quality, constructing multiple economic-center cities, reforming the political promotion mechanism, and developing the ecological compensation mechanism for air pollution. • Spatial bi-directional effect of economic growth and air pollution under local government competition are demonstrated. • Local government competition on tax income and foreign investment further increases the air pollution. • Multiple economic-center cities should be developed for economic and environmental coordination in China's "2 + 26" cities. • The political performance appraisal in China is suggested to adopt a more economic-environmental-balanced scheme. • An ecological compensation mechanism for air pollution is supposed to be established. [ABSTRACT FROM AUTHOR]

Environmental sustainability has gained much attention in the recent decade. This study examines the links among energy intensity, non-linear financial development, and environmental sustainability in the presence of economic growth of the Asia Pacific Economic Cooperation (APEC) countries from a period of 1990–2016. We apply advanced econometric methodologies for empirical analysis. Empirical results support the presence of inverted U-shaped Environment Kuznets Curve (EKC). Our linear function findings indicate that energy intensity, financial development, and economic growth are positively associated with the ecological footprint. However, these variables are negatively related to APEC countries' ecological footprint in the non-linear phase. These results support the EKC hypothesis for APEC countries. We found a positive relationship between energy intensity and ecological footprint, indicating that energy intensity is associated with deteriorating environmental sustainability. We confirm a financial development-driven U-shaped link with an ecological footprint at a maximum turning point of −7.9653. There are U-shaped and N-shaped EKC relationships between economic growth and ecological footprint at a maximum and minimum turning point of −8.07029 and 23.5465, respectively. Overall, at the initial stage, financial development and economic growth deteriorate the environment to a point after which it improves. Policymakers are encouraged to advocate technological advancements, address market failure, get the price right by pricing the pollution like carbon pricing, reforming inefficient subsidies, and decouple the links between environmental vicious and economic goods. Study limitations and directions for future research in the area have been discussed as well. • Examined links among energy intensity, financial development, and environmental sustainability. • Energy intensity, financial development, and economic growth are positively related to ecological footprint. • EKC hypothesis validates for APEC countries. • Linear: energy intensity, financial development, and economic growth deteriorate environmental sustainability. • Non-linear: financial development, and economic growth improve environmental sustainability. [ABSTRACT FROM AUTHOR]

This paper, firstly, investigates the relationship between clean energy and economic growth using satellite remote sensing data to proxy economic activities. Then, this paper constructs a spatial autoregressive model, spatial error model, and spatial Durbin model to study the spatial spillover effects of financial development and clean energy. Further, this paper adopts the difference-in-differences (DID) model and the propensity score matching-DID (PSM-DID) method to conduct quasi-natural experiments on clean energy and examine whether China's energy policy can promote clean energy, thereby promoting economic growth. The analysis results reveal a positive correlation between clean energy and economic growth; local financial development promotes clean energy in the region but negatively impacts the clean energy in surrounding areas. Moreover, the findings confirm a significant positive relationship between the "policy treatment effect" and clean energy. Finally, we put forward relevant policy recommendations based on the empirical results. • Satellite remote sensing data acquired by DMSP/OLS is used to proxy GDP. • Clean energy has a significant role in promoting economic growth. • Spatial econometric models are constructed to study the spatial spillover effects. • The DID model and PSM-DID method are used to conduct quasi-natural experiments. • China's energy policy has a significant promoting effect on clean energy and GDP. [ABSTRACT FROM AUTHOR]

This paper aims to examine the causal relations between economic growth, electricity consumption, and urbanization indicators. Heterogeneous panel data techniques are performed to help shed light on the importance of the heterogeneity among three economic regions within China from 2000 to 2017. Our results show that the three indicators are all stationary and cointegrated after the first difference. Heterogeneity of the Granger causality is found between these three variables varies across the eastern, central, and western economic regions in China. In the long run, the eastern region presents a similar trend as the national level that long-run Granger causality of the three variables is found. Conversely, there is a unidirectional long-run causal relationship from economic growth to electricity consumption in the central region, while there is a bi-directional long-run causal relationship between economic growth and electricity consumption in the western region in China. Our empirical findings highlight the "urbanization ladder" effect which implies that as development, urbanization factor in the eastern region may play a promotion role in the tri-variate system when the urbanization reaches a higher level, while it may lack the influence in the central and western regions of China. From a regional perspective, it is further indicated that the improvement of urbanization can be practical measures in the central and western parts of China in the long run. • Economic growth, electricity consumption, and urbanization are cointegrated in eastern, central, and western China. • Granger causalities between the three variables vary across the three economic regions in China. • Urbanization does not have a causal effect on economic growth & electricity consumption in central-western China. • It is essential to accelerate the urbanization process in the central-western areas in China in the long run. [ABSTRACT FROM AUTHOR]

Environmental regulation provides new constraints and opportunities for economic growth. Based on OLG (Overlapping Generation) model, this paper re-characterizes the relationship between the intensity of environmental regulations and economic growth rate from two perspectives: technical level and healthy human capital. By using the panel data of 31 provinces and cities in China from 2004 to 2017, empirical tests were conducted through the mediation effect method and the contrast groups of OLS (Ordinary Least Squares) regression experiment to support the theoretical part. The results show that: (1) The non-linear relationship between environmental regulations and economic growth rate shows an "inverted U-shaped" curve, where the economic growth rate displays a correlation with the intensity of environmental regulations from positive to negative; (2) The internal action path of environmental regulations on economic growth shows the differentiated characteristics according to different industrial types. Specifically, under the established intensity of environmental regulation, the effect of regulatory policies on labor-intensive enterprises is more based on the technological level, while it is more inclined to the path of healthy human capital for capital-intensive enterprises. This paper enriches the theoretical system of economic growth under environmental regulations, which has important reference significance for promoting green development and ecological civilization construction. • Verify the relationship between intensity of environmental regulations and economic growth. • Analyze the role of technology level and healthy human capital to economic growth. • Explain the contributions of different factors to the production. [ABSTRACT FROM AUTHOR]

This study revisits the relationship between biomass energy and economic growth for the case of BRICS countries by adopting a newly introduced method: panel quantile regression with fixed effects via the method of moments. By applying this novel estimator based on the dataset from 1990 to 2017, our research provides a more detailed view of the heterogeneous impact of biomass energy production on different levels of economic growth of the BRICS countries. Specifically, our analysis results disclose that the influence of biomass energy production is insignificant at the 5th quantile, but it is positive and significant at the remaining quantiles. The impact of biomass energy extraction is also increasing gradually as quantile levels of economic growth increase. In addition to the above results, we also use the Dumitrescu-Hurlin causality test to confirm the bidirectional causal nexus between economic growth and biomass energy. These results are the basis for us to make some policy recommendations for BRICS countries. • Revisiting the link between biomass energy and economic growth of BRICS countries. • Panel quantile regression with fixed effects via the method of moments are applied. • A positive relation between biomass energy and economic growth is confirmed. • The impact of biomass energy on economic growth is greater in higher-income countries. • The bidirectional causal connection exists between economic growth and biomass energy. [ABSTRACT FROM AUTHOR]

Decoupling the trends of energy-related carbon emissions from economic growth is an essential precondition and condition for cost-effective climate stabilization. Using an extended Kaya identity and the Tapio decoupling definitions, this study explored the role and magnitude of drivers associated with carbon emissions and economic growth decoupling across 134 countries. The retrospective (1995–2015) decomposition analysis was complemented by exploring the future decoupling projections using assumptions of the Shared Socio-economic Pathways (SSP) framework. The results indicate that less mature developing economies are carbonizing their energy systems at faster rates (about 1–4%/year) compared to developed economies. While emerging developing economies are progressively transitioning towards weak decoupling. Overall the deterioration of structural and intensity technology drivers, including conversion efficiency, emission factor, and fossil fuel mix, are the major pinch points to achieving absolute decoupling among developing economies. The prospective analysis of the SSP assumptions also indicate that - developing economies exhibit very minimal signs of decoupling and decarbonization relative to developed economies. The study provides instructive insights about the urgency of addressing global decarbonization, especially among developing economies. • Compared the technology and scale driver of CO 2 -GDP decoupling across income class. • Downscaled the projection of CO 2 -GDP decoupling using assumptions of mitigation. • Developing economies exhibit minimal evidence of strong decoupling. • Structural energy drivers inhibit strong decoupling among developing economies. [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]

Several economists assume natural resources as crucial and essential for economic growth. However, the other group of researchers questions the role and states that richness of natural resources does not guarantee economic growth. Therefore, the aim of this study is to examine the effect of natural resources on economic growth using time series data from 1970 to 2018. The current study has applied a novel methodology of quantile-on-quantile regression in top five selected Asian economies which have the most natural resources in the region. The findings confirm that natural resources have a positive and significant impact on economic growth in all countries, except India. The findings confirm that the effect of natural resources on economic growth is negative and significant in the Indian economy. The findings affirm that in most of the countries, the results are significant and positive on the high quantiles of natural resources and economic growth, suggesting that the higher the rent of natural resources leads to the higher the economic performance of five selected Asian economies. Based on the findings, government and policymakers are recommended to formulate the policy that provides a platform to use the NR in a better and efficient manner, which can help the country to boost the economic performance. Image 1 • Natural resources are crucial and essential for economic growth. • The study examines the effect of natural resources on economic growth using time series data from 1970 to 2018. • A novel methodology of quantile-on-quantile regression is applied. • Top five selected Asian economies which have the most natural resources in the region were selected. • The findings confirm that natural resources have a positive and significant impact on economic growth, except India. [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 aim of this paper is to analyze the relationship among iron and steel industries, air pollution and economic growth in China. Using monthly time series from 2000 to 2017, we adopt a Long Short Term Memory (LSTM) approach. The empirical results show that the relationship between economic growth and steel production is very strong in the first stage. Furthermore, in our model, we can see that the reduction of polluting emissions is linked to the principle of sustainable development. In particular, this phenomenon lies in the economic growth model responsible for the future generation. [ABSTRACT FROM AUTHOR]

Since the Belt and Road Initiative (BRI) has increased the economic growth of many developing countries in Asia, more attention should be paid to carbon dioxide (CO2) emissions in these regions. Based on the Tapio decoupling model and Kaya-LMDI model, this paper investigates the spatiotemporal evolution of decoupling and driving factors of CO2 emissions of 57 BRI countries from 1991 to 2016. The results are as follows. First, the decoupling statuses of higher income countries are generally better than lower income countries. Second, Northeast Asia, South Asia, and West Asia accounted for 68.5%, 16.8%, and 13.3% of CO2 emission increases in BRI countries from 1991 to 2016. Third, almost all countries' CO2 emissions significantly rise due to economic growth, while energy intensity reduces CO2 emissions to some extent. Energy exports increase CO2 emissions to varying degrees in Asia countries, but their impact has gradually fallen. Except for Europe, the population size effect increases CO2 emissions, especially in West Asia. China, India, Russia, and five OPEC countries show similar characteristics with the above regions. • The Tapio decoupling model is applied to analyze the CO 2 decoupling of 57 Belt and Road Initiative countries. • Five driving forces of CO 2 emissions are identified via the Kaya-LMDI model. • Spatiotemporal characteristics of decoupling and driving forces are highlighted. [ABSTRACT FROM AUTHOR]

This study investigates the validity of the Environmental Kuznets Curve (EKC) hypothesis for six West African countries over 1970–2017 while using human capital and biocapacity as additional determinants of carbon emissions. It uses the panel quantile regression method that provides robust results in case the classical econometric assumptions fail. The empirical results revealed that a U-shaped relationship between economic growth and Carbon dioxide (CO 2) emissions holds in the low, middle and high-emissions countries as opposed to the inverted U-shaped EKC hypothesis. Trade openness reduces environmental performance in low-emission countries. Financial development has mixed impacts on CO 2 emissions across the quantiles. While financial development enhances environmental quality in the low-emissions countries, it exerts a detrimental impact in the middle and high-emissions countries. Human capital has significantly positive effects on the lower, middle and upper quantiles. The obtained results highlight the need for raising environmental awareness and promoting green R&D. In addition, relevant incentives are required to redirect private credits towards green projects and renewable energy development. • CO 2 emissions affect economic growth in West African countries. • Environmental Kuznets Curve (EKC) hypothesis is tested using panel quantile regression. • The U-shaped relationship between economic growth and CO 2 emissions is found. • Financial development cleans environment only in the lower quantile. • Human capital increases CO 2 emissions in all quantiles. [ABSTRACT FROM AUTHOR]

The study of the relationship between water pollution and economic growth holds great significance for sustainable development. Under Environmental Kuznets Curve (EKC) hypothesis, this paper focuses attention on a Chinese context and investigates the relationship between water pollution discharge--waste water (WW), chemical oxygen demand (COD) and ammonia nitrogen (NH 4 –N) and economic growth--per capita Gross Domestic Production (GDPPC), based on a comparison of the results from two variable coefficient panel data models–-a Locally Weighted Smoothed Regression Estimator and Smoothing Scatterplots Model (LOWESSM) which is a nonparametric model, and a Semi-parametric Seemingly Unrelated Regression Model (SSURM) which considers the contemporaneous correlation of water pollutants that most previous studies have ignored. The empirical results indicate that there exist differences that can be represented by the characteristics of different EKC types, or different turning points under the same EKC type and that the SSURM may be more conducive to reflecting the real relationship between water pollution and economic growth. The study also finds that there are eight types of EKC which can be categorized as "good EKCs" (negative monotonic shape, inverted N-shape, inverted U-shape and M-shape), "bad EKCs" (positive monotonic shape, N-shape and U-shape) and "transition EKC" (positive monotonic and flat-tailed shape) and the proportion of "good EKCs" in economically developed areas (71.43%) is lower than that in the less economically developed areas (76.47%) in terms of COD discharge. Results suggest that addressing the state of water pollution will not occur automatically as GDPPC increases, but requires the regulatory power of government environmental policies. Image 1 • Exploring correlation of pollutants by semi-parametric seemingly unrelated model. • Semiparametric seemingly unrelated model reflects income-pollution relation better. • Eight types of Environmental Kuznets Curve are found, including a new M-shape. • Good EKCs' proportion in underdeveloped area (76%) is higher than developed (71%). [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]

Investigation of the relationship between electricity consumption and economic growth among industries helps to find nexus of industrial development. However, the existing studies in this area are limited. Most of the existing studies focus on mining the point-point relationship at the aggregate level, network relationships among industries are neglected. It may lose some vital information and result in misleading judgement would be made for policymakers. To fill up the gap, this paper explores the network relationship between electricity consumption and economic growth of eight industries in China to detect the crucial industries and key causal transmission paths of electricity consumption-economic growth among industries. Empirical results over the period from 2007Q1 to 2017Q3 indicate that (a) Agriculture, Financial Industry, and Real Estate Activities are the driving forces of economic growth-relation network (GRN) and the engines of social development; (b) the economic growth of Transport, Storage and Post is the key bridge of overall-relation network (ORN) and GRN; (c) the electricity consumption of Construction and Real Estate Activities are the endpoints of the ORN which are affected by economic growth in other industries; (d) The most important transmission section of ORN is Industry (G2)→Transport, Storage and Post (G5)→Construction (G3)→Industry (E2), and that of GRN is Industry (G2)→Transport, Storage and Post (G5)→Construction (G3). [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]

The integration of the circular economy (CE), a model promoting the cyclical use of resources, and Industry 4.0, an intelligent-based approach to manufacturing, is expected to achieve sustainability. Finding the most suitable path for technological progress and structural change to promote economic growth is the key to adopting Industry 4.0 technologies and successfully transforming to a CE, and thus, key to China achieving sustainable development quickly. This study identifies the joint effects of energy- and environment-biased technological progress and multi-dimensional industrial structural change on economic growth, and empirically verifies the specific effects within China. Our results are as follows. First, pollution abatement technological progress, backstop technological progress and autogenous structural ecologicalization are the main drivers of sustainable economic growth. Second, innovation policies have a positive impact on national economic growth by promoting pollution abatement technological progress. Finally, in sub-regions' regression, backstop and environment technology, and structural ecologicalization promote eastern China's economy, while policies drive environment technological progress and structural ecologicalization to stimulate economic growth in central and western China. Our results imply that policymakers should take into consideration the readiness levels of each region regarding the adoption of Industry 4.0 and circular economy, and that the government should consider and ensure the participation of all stakeholders, including firms. • Focus on the economy's driving forces under Industry 4.0 and circular economy. • Environment and new-energy technological progress promote economic growth in China. • Innovation policy drives economic growth by inducing biased technological progress. • Backstop and environment technological progress benefit eastern and central China. • Industrial policy works well on structural ecologicalization and regional economy. [ABSTRACT FROM AUTHOR]

This study aims to assess the impact of circular economy on economic growth. In the process of rapid economic growth, China has been facing with the pressure of insufficient supply of resources and environmental pollution, which makes the development model of circular economy (CE) an imperative transformation. China has carried out two batches of CE pilot cities to promote the construction of ecological economy and change the traditional economic development model, which is employed as a quasi-natural experiment in this study. The effect of this CE policy on the local economic growth is explored using the Propensity Score Matching (PSM) method and Difference-in-Differences (DID) model and a panel data of 163 Chinese cities from the year of 2001–2012 has been used. The results show that the growth rate of GDP of the pilot cities decreases significantly but the economic decline gradually recovers as time goes on. In addition, this study further conducts the regional heterogeneity analysis to compare the economic growth of CE pilot cities in three economic zones, i.e., eastern, central and western economic zones, and the sectoral heterogeneity analysis to compare the economic growth of three main industries, i.e., primary, secondary and tertiary industries. Finally, discussion of above results is presented and recommendations for the promotion of urban CE are proposed. [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]