Do economic policy uncertainty and environment-related technologies help in limiting ecological footprint? (original) (raw)
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Determinants of ecological footprint in BRICS countries: a panel data analysis
Environment, Development and Sustainability, 2023
This study aimed to examine the variables that might affect the ecological footprint by using 1992-2015 data of the BRICS countries (Brazil, Russia, India, China, and South Africa). The common correlated effects' mean group test was employed under the assumption of cross-sectional dependence and heterogeneity. In Brazil, an increase in energy consumption, technological development, and globalization decreased the ecological footprint by 0.043, 0.031, and 0.050 units, respectively, while an increase in urbanization increased the ecological footprint by 0.716 units. In Russia, on the other hand, no interpretation could be made because the coefficients were meaningless. In India, it had been observed that an increase of one unit in urbanization reduced the ecological footprint by 0.269 units. In China, it had been determined that a 1-unit increase in energy consumption reduced the ecological footprint by 0.043 units. In South Africa, the results could not be interpreted because the coefficients were insignificant. The results obtained vary according to the countries that revealed that local policies can also be effective on these variables. Therefore, countries have to act by examining the structures on their own to implement the policies they needed.
Energy Reports, 2023
This study examined the causal nexus between renewable energy consumption, GDP, and CO 2 emissions across BRICS and OECD countries from 1995 to 2021, using various econometric techniques including FMOLS and DOLS estimators. It also reviewed the most recent literature on this nexus, aiming to understand the impact of renewable energy development on economic growth and CO 2 emissions reduction. The long-run estimations from FMOLS and DOLS showed that the majority of the observed variable coefficients were statistically significant at 1%, 5%, and 10% levels. In panel FMOLS estimation for the BRICS, a 1% increase in GDP correlates with a 0.204% increase in renewable energy (RE). However, an increase in CO 2 emissions significantly reduce RE by 0.994%. In contrast, the panel DOLS estimation shows that a 1% increase in GDP improves RE by 0.399%, while an increase in CO 2 emissions drops RE by 1.369%. Similarly, in panel FMOLS estimation for the OECD indicates that a 1% increase in GDP correlates with a 0.083% rise in RE, but an increase in CO 2 emissions leads to a decrease in RE by 1.476%. In the DOLS panel, a 1% rise in GDP correlates with a 0.054% increase in RE, while an upsurge in CO 2 emissions diminishes RE by 1.369%. The nexus among renewable energy consumption, CO 2 emissions, and GDP is intricate and interconnected. Renewable energy is a key solution to mitigate CO 2 emissions and foster sustainable GDP growth. Nevertheless, CO 2 emission has significant negative impacts on both the deployment of renewable energy and GDP, underscoring the necessity for sustainable development practices.
Frontiers in Environmental Science, 2021
Although a number of studies have been conducted on the environmental Kuznets curve (EKC) and the pollution halo hypothesis (PHH), few researchers have assessed the scope in the light of the BRICS— Brazil, Russia, India, China, and South Africa—nations. Therefore, the current research assesses the income-induced EKC as well as the role of technological innovation and renewable energy consumption utilizing a dataset stretching from 1990 to 2018. The present research utilized the novel method of moments quantile regression (MMQR) developed by Machado and Silva (2019) to assess these interrelationships. The empirical outcomes from the MMQR affirmed an inverted U-shaped interrelationship between CO2 emissions and economic growth across all quantiles (first to ninth) for the BRICS nations, thus confirming the presence of the EKC hypothesis. Furthermore, we affirmed the PHH, thus confirming the negative interrelationship between globalization and ecological footprint across all quantiles ...
2021
This article seeks to analyze the impact of technological innovations, financial development, renewable energy consumption, economic growth, and population on the ecological footprint in Asia Pacific Economic Cooperation (APEC) countries by utilizing the balanced longitudinal data set during the period from 1990 to 2017. This study creates a new technological innovation index through principle component analysis including three important indicators that represent the technology and employs a consistent environmental framework identified as Stochastic Impacts by Regression on Population, Affluence and Technology (STIRPAT) model. The second generation panel estimation technique is employed to calculate robust and reliable outcomes. After confirming the cross-sectional dependency among series, panel unit root tests confirm that all variables are stationary at their first integrated order. Furthermore, Westerlund cointegration test confirms the presence of long-run association among variables. The outcomes explore that financial development and renewable energy utilization significantly accelerate the environmental quality by 0.0927% and 0.4274%, respectively. While, the increase in technological innovation activities, economic growth, and population size has a detrimental effect on environmental quality in the long run by 0.099%, 0.517%, and 0.458%, respectively. Moreover, the results of panel Dumitrescu and Hurlin (D-H) non-causality test discovered the bidirectional causality relationship between financial development, technological innovations, renewable energy consumption, economic growth, and population size with the ecological footprint. These empirical findings provide some vital policy implications for central authority and policymakers to overcome the detrimental impact on environmental quality in the APEC region.
Energies, 2021
Economic complexity makes it possible to assess the development of the countries, the relations of innovation, and the differentiation of products. The article considers the links between the hypotheses of the Kuznets environmental curve and economic complexity using panel data for the group of BRICS countries (Brazil, Russia, India, China, and South Africa) from 1990 to 2015. As an econometric strategy, this study considered the panel fully modified least squares (FMOLS), panel dynamic least squares (DOLS), fixed effects (FE), and Panel Quantile Regression. The empirical results showed that economic complexity, income per capita, renewable energy, and carbon dioxide emissions are integrated with the first difference when applying the unit root test. The arguments of Pedroni and Kao cointegration tests were also used. According to these results, the variables used in this research are cointegrated in the long run. The results validated the arguments of the EKC hypothesis, i.e., the ...
Environmental Science and Pollution Research
In the contemporary world, environmental degradation has become a concern for human beings. Accordingly, the impact of social welfare, economic policy uncertainty, natural resource rents, life expectancy, and trade openness are examined on ecological footprint (the most comprehensive proxy of environmental degradation) in 19 energy-intensive countries from 1997 to 2018. With this in mind, this study used the traditional panel ARDL and CS-ARDL approaches to evaluate how the study's variables influence ecological footprint. Notably, the results of the CS-ARDL approach are more robust due to cross-sectional dependence and slope heterogeneity problems. The outcomes revealed that economic policy uncertainty and trade openness affect the ecological footprint negatively in the short run and positively in the long run. Moreover, social welfare degrades the environment in the long run, and natural resource rents improve environmental quality by mitigating the ecological footprint in the short run and harming the environment in the long run. Besides, life expectancy does not significantly affect ecological footprint in the long or short run. Meanwhile, the results confirmed the bi-directional causal relationship between the study's variable and ecological footprint. Based on the outcomes, the way to adopt effective policies to improve the quality of the environment has been paved. Furthermore, a comprehensive policy framework for stricter environmental regulation is expected to be developed using the outcomes derived from this study.
Sustainability
Since the turn of twenty first century, economic policy uncertainty (EPU) and geopolitical risk (GPR) have escalated across the globe. These two factors have both economic and environmental impacts. However, there exists dearth of literature that expounds the impact of EPU and GPR on environmental degradation. This study, therefore, probes the impact of EPU and GPR on ecological footprint (proxy for environmental degradation) in selected emerging economies. Cross-sectional dependence test, slope heterogeneity test, Westerlund co-integration test, fully modified least ordinary least square estimator, dynamic OLS estimator, and augmented mean group estimator are employed to conduct the robust analyses. The findings reveal that EPU and non-renewable energy consumption escalate ecological footprint, whereas GPR and renewable energy plunge ecological footprint. In addition, findings from the causality test reveal both uni-directional and bi-directional causality between a few variables. ...
Stochastic Environmental Research and Risk Assessment
This study aims to demonstrate the impact of renewable energy consumption (REC) on environmental degradation using the EKC hypothesis testing for the BRIC and G-7 countries. Two EKC models were created and tested, with Model 2 including REC and other independent variables such as economic freedom (EF) and economic policy uncertainty (EPU), which affect the level of renewable energy consumption and CO 2 emissions. Empirical findings indicate that the EKC hypothesis is verified faster in the REC-EF-EPU-based EKC model (Model 2) than in the EF-EPU-based EKC model (Model 1) for G-7 countries since the turning point takes place earlier in Model 2 than in Model 1 with REC. This suggests that renewable energy consumption accelerates the reduction of CO 2 emissions. Moreover, this earlier turning point results in lower environmental cleaning costs, less time vesting, and saving resources and money for G-7 countries. However, the study found no evidence supporting the EKC hypothesis for the BRIC countries.
Energies, 2023
In this study, the focus is on examining the influence of renewable energy consumption, economic risk, and financial risk on the load capacity factor (LF) within the BRICS countries. The analysis covers the time span from 1990 to 2019. The empirical strategy uses the Method of Moments Quantile Regression (MMQR) and long-run estimators (Fixed Effects Ordinary Least Squares, FE-OLS; Dynamic Ordinary Least Squares, DOLS; and Fully Modified Ordinary Least Squares, FMOLS). The findings highlight the presence of a cointegrating relationship. Moreover, fossil fuels and economic growth cause LF to decrease, while economic risk and the use of renewable energy sources increase the deepening of the LF. Furthermore, the results of the MMQR method are confirmed by DOLS, FMOLS, and FE-OLS estimates. Causality results also demonstrate that these factors may forecast ecological quality, indicating that policies for renewable energy consumption, financial risk, renewable energy, and economic growth can all have an impact on the degree of LF. In light of this research, policymakers should strongly encourage expenditures on environmentally friendly technologies and economic and financial stability to increase energy efficiency as well as sustain the widespread adoption and use of energy-saving products.
Environmental Science and Pollution Research, 2020
This study aims to examine the impact of economic growth, financial openness, trade openness, and energy intensity on the ecological footprint of BRICS countries for the period 1996-2016 in the framework of the environmental Kuznets curve (EKC). In the research phases, the effects of financial openness and trade openness on ecological footprint were examined both individually and as a whole using three models. The results indicate that the EKC hypothesis is not valid in all BRICS countries. Specifically, the individual results demonstrate that the EKC model using financial openness is valid only for India, while the EKC model using trade openness is valid both for India and South Africa. Furthermore, financial openness has reduced environmental pollution in India and South Africa. Trade openness has reduced environmental pollution in China and India, while it has increased in South Africa. Lastly, energy intensity has increased environmental pollution in all countries except Russia for both models. Overall, policy-makers should develop policies to reduce energy intensity in BRICS countries.