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Life expectancy can reflect both health benefit and implementation cost of climate policy. Nevertheless, little research has quantified the relation between life expectancy and climate policy in literature. In this paper, we attempt to narrow the research gap by studying how life expectancy is related to the Chinese nationwide emission trading scheme (CNETS). To achieve this research target, a Computable General Equilibrium (CGE) model is employed to simulate the operation of the economic system and the policy shock from emission abatement. The CGE model results show that life expectancy is prolonged by GDP but shortened by emissions, and the GDP impact on life expectancy is larger than the emission impact. Climate policy has dual effects on life expectancy because it relieves both negative emission impacts and positive GDP impacts on lifespan; its net effect on life expectancy is positive. Life expectancy positively impacts GDP, and this impact is moderated by climate policy; specifically, climate policy reinforces the positive impact of life expectancy on GDP. Life expectancy minimally affects carbon emissions during climate policy implementation; in other words, it has minimal impacts on emission abatement. These findings imply that climate policy and life expectancy complement each other; the government could implement climate policy to increase lifespan or prolong life expectancy to facilitate policy implementation. [ABSTRACT FROM AUTHOR]

Sustainable Development Goal 9 targets (SDG 9 targets) are mainly tracked through the indicators of penetration of internet and mobile broadband subscription, logistic performance index, quality and ranking of the universities, investment in research and development initiatives, industrial reforms and emission control, and connectivity to rural areas. The attainment of many of these targets and tracking of indicators is confronted by challenges of poor awareness, funding issues, distorted policies, and implementation failures. This systematic review on achievements, challenges, and future scope in attaining SDG 9 consolidates the literature from the Web of Science, related to SDG 9 and indicators, since 2017; develops bibliometric patterns; conducts thematic analysis by focusing the leading indicators of SDG 9; and develops agenda for future research. The major limitations of this study include focusing on selected indicators and limited literature availability. This review recommends policymakers, researchers, and administrators to focus on promising themes such as tackling the digital divide and ensuring digital justice and digital equality; clean fuel and technology adoption; enhancing internet and mobile broadband subscription with reduced negative impacts, logistic sector reforms; industrial policy reforms and technology integration; improving the quality and sustainability of universities; and increasing funding and support for research and development initiatives and improving the rural connectivity. [ABSTRACT FROM AUTHOR]

This paper studies the relationship among carbon emissions, GDP, and logistics by using a panel data model and a combination of statistics and econometrics theory. The model is based on the historical data of 10 typical provinces and cities in China during 2005-2014. The model in this paper adds the variability of logistics on the basis of previous studies, and this variable is replaced by the freight turnover of the provinces. Carbon emissions are calculated by using the annual consumption of coal, oil, and natural gas. GDP is the gross domestic product. The results showed that the amount of logistics and GDP have a contribution to carbon emissions and the long-term relationships are different between different cities in China, mainly influenced by the difference among development mode, economic structure, and level of logistic development. After the testing of panel model setting, this paper established a variable coefficient model of the panel. The influence of GDP and logistics on carbon emissions is obtained according to the influence factors among the variables. The paper concludes with main findings and provides recommendations toward rational planning of urban sustainable development and environmental protection for China. [ABSTRACT FROM AUTHOR]

The reduction in oil prices might make crude oil a cheaper alternative to renewable energy (RE). Given this, the present paper examines the effect of fluctuation of oil prices on the use of RE in the United States (US) during the period 1970 to 2018. We constructed two nonlinear autoregressive distributed lag (NARDL) models to examine the effect of the positive and negative oil price shocks on the use of RE in the US. The RE consumption is taken as the dependent variable and the gross domestic product (GDP), Brent crude prices, population density, trade openness, and price index as independent variables. The result revealed that the rise in crude oil price, GDP, and population density will increase RE use in the short run and in the long run as well. Moreover, the study finds that any decrease in oil prices will decrease RE use in the short run and its effect will eventually diminish in the long run. On the policy front, it is suggested that US should raise its energy security by reducing its dependency on imported crude oil and increase the role of RE through the imposition of taxes on oil and increase the base of production and consumption through a series of measures. [ABSTRACT FROM AUTHOR]

The study explores the inter-relations between green and renewable energy and carbon risk. Key market participants with varying time horizons include traders, authorities, and other financial entities. This research examines these relationships and frequency dimensions from February 7, 2017, to June 13, 2022, using novel multivariate wavelet analysis approaches, such as partial wavelet coherency and partial wavelet gain. The multiple coherencies between green bond, clean energy, and carbon emission futures imply that these regions were situated at low frequencies (relating to approximately 124-day frequency) and run from the beginning of 2017 to the beginning of 2018, in the first half of 2020, and from the beginning of 2022 to the end of the sample. The relationship between the solar energy index, envitec biogas, biofuels, geothermal energy, and carbon emission futures, is significant in the low-frequency band starting from early 2020 to middle 2022 and in the high-frequency band starting from early 2022 to middle 2022. Our research demonstrates the partial coherencies between these indicators during the Russia-Ukraine conflict. The partial coherency between the S&P green bond index and carbon risk suggests that carbon risk pushes anti-phase connectedness. The partial phase difference S&P global clean energy index and carbon emission futures (from early April 2022 to the end of April 2022) recommend that indicators are in-phase with carbon risk pushing and the phase (from early May 2022 to middle June 2022), suggesting that carbon emission futures are in-phase with S&P global clean energy index pushing. [ABSTRACT FROM AUTHOR]

In recent years, the concept of sustainable development has enriched numerous scientific researches. Therefore, the combination of economic growth and the environment has been the subject of numerous econometric and statistical models. They demonstrated that there is a two-way relationship between economic growth and pollution. So, we use data from the World Bank database (1971–2014) to assess the possibility that a change (positive or negative) in pollution in India generates a gross domestic product acceleration. Through a Machine Learning approach via artificial neural network analysis, empirical findings show that a deep neural network can predict the outcome under study. The novelty of this paper is to have determined the results through a model based on a comparison with a highly developed country (Japan). The results obtained show that in a country like India, 76% of the time, a change in pollution evolves into a change in the acceleration of the economic growth. [ABSTRACT FROM AUTHOR]

The aim of this paper is to examine the relationship between CO2 emissions and its possible determinants and their direction of causality for Pakistan over the period of 1972 to 2017. The survey of literature guides us that the most frequently discussed factors are real GDP per capita, energy consumption, urbanization, trade openness, and financial development. Testing of environmental Kuznets curve (EKC) hypothesis is the most common in environment literature so we also incorporated the real GDP per capita squared term in the model. Autoregressive distributed lag (ARDL) bound testing approach to cointegration with structural break and error correction method (ECM) are applied to the selected time series to investigate the long-run relationship between CO2 emissions and real GDP per capita, real GDP per capita squared term, energy consumption, urbanization, trade openness, and financial development. The empirical evidence confirms the cointegration among the variables and EKC holds for Pakistan support H1 of the study, which though contradictory to the previous studies conducted on Pakistan but all of previous work faces the exclusion bias and their findings were skewed. The findings also suggest that energy consumption and urbanization have a positive effect on CO2 emissions, supporting H2 and H3. However, H4 and H5 rejected as trade openness and financial development found positively significant. Moreover, bidirectional Granger causality was exists only between CO2 emissions and trade openness. The findings suggests that Pakistan need to settle the economic agenda of the nation through the resolution of economic controversies, energy mix need to tilt toward clean and renewable energy, and rural-urban migration need to manage for better air, water, and living. [ABSTRACT FROM AUTHOR]

How do digitalizing businesses help them achieve sustainable growth? This research examines the mediating function of green technology innovation in answering this question by defining sustainable development performance in terms of corporations' financial and environmental success. The educational system in China is examined to see how much of an impact it has on eco-innovation, as well as the relationship between green technology and innovation. The IFE test was utilized to determine whether or not the associations between variables such as GDP per capita, urbanization, green technology, higher education, and carbon dioxide emissions will continue to exist between 2004 and 2020 in China. The data for this analysis came from 30 of China's provinces. The findings of both the short-term and long-term CS-ARDL estimations demonstrated a positive link between eco-innovation and GDP per capita, green technology, higher education, and CO2 emissions. On the other hand, a negative correlation was found between urbanization and eco-innovation. The next topic covered in the research was how the effects of green technology might be seen in areas such as GDP per capita, higher education, and carbon dioxide emissions. The findings might provide valuable knowledge that developing economies can use to construct a feasible, sustainable path. [ABSTRACT FROM AUTHOR]

One of the greatest challenges facing humanity in the current millennium is the need to mitigate climate change, and one of the most viable options to overcome this challenge is to invest in renewable energy. The study dynamically examines the links between renewable energy consumption, non-renewable energy consumption, climate change, and economic growth in five emerging Asian countries during the period 1975–2020. Variables selected in the model have long-term cointegration, as explored by the Pedroni cointegration test and the Westerlund cointegration test. The long-term estimated parameters of the augmented mean group (AMG) method show that renewable energy consumption significantly reduces climate change, while non-renewable energy consumption significantly promotes climate change. The results also show that GDP, investment in transport infrastructure, and urbanization can significantly contribute to climate change in selected emerging Asian countries. Moreover, the results validate the inverted U-shaped EKC hypothesis for emerging Asian economies. Country-specific analysis results using AMG estimates shows that renewable energy consumption reduces climate change in selected emerging Asian countries. Non-renewable energy consumption and investment in transport infrastructure have had significant progressive impacts on climate change in all countries. Urbanization contributes significantly to climate change, with the exception of Japan, which does not have any significant impact on climate change. GDP contributes significantly to climate change in all countries; however, GDP2 has significant adverse effects on climate change in India, China, Japan, and Korea, validating the inverted U-shaped EKC assumption for all countries except Bangladesh. Moreover, the Dumitrescu and Hurlin causality test confirmed a pairwise causal relationship between non-renewable energy consumption and GDP, supporting the feedback hypothesis. The results suggest that the best option for climate change mitigation in selected emerging Asian countries is to transition from non-renewable to renewable energy sources. [ABSTRACT FROM AUTHOR]

The contribution of this research is to provide empirical evidence that investing in green technology innovation (GTI) can reduce the ecological footprint in Turkey, which can lead to sustainable economic growth and environmental quality. The research also highlights the importance of controlling energy consumption, GDP, trade openness, and urbanization, as these variables have a positive or negative effect on ecological footprint. The findings of this research can be useful for the Turkish government, policymakers, and environmentalists to promote the implementation of GTI and eco-friendly resources, which can reduce the impact of climate change and contribute to economic prosperity. Overall, this research provides important information for decision-makers to adopt policies that prioritize green innovation and environmental protection in Turkey. [ABSTRACT FROM AUTHOR]

This study aims to identify macroeconomic indicators that can be used as predictors of waste management on the European continent. The study was conducted taking in account the intensification of urbanizations, the increase of standard of leaving that fuels to consumerism phenomenon, and imposed challenges for waste management. The research focuses on the interval from 2010 to 2020 for 37 European countries grouped according to EU15/EU28/non-EU and EU/non-EU members. As macroeconomic indicators, human development index (HDI), GDP/capita. GNI/capita, general government expenditure with environment protection, people at risk of poverty or social exclusion, population by educational attainment level, sex, and age (%)—less than primary, primary and lower secondary education (levels 0–2) were used. A multilinear regression model with collinearity diagnosis was applied to find out the direction and intensity of the contribution of independent variables and to hierarchy the predictors of waste management.. For multiple comparison between and inside of each grouping of countries, statistical inference methods were used: one-way ANOVA with Bonferroni post hoc test multiple comparisons and independent samples Kruskal–Wallis test with Dunn's post hoc test. The main conclusions of the study are that EU15 countries have the highest average values for most indicators of waste management, comparative with EU28 and with non-EU countries, followed by a group of EU28 countries. For indicators of recycling rate of packaging waste by type of packaging—metallic and recycling rate of e-waste, the non-EU countries have the highest values of mean compared with the EU15 and EU28 groups of countries. This can be explained by the high level of development of the some non-euro area countries (Iceland, Norway, Switzerland, Liechtenstein) that have intense concerns about waste recycling and have the necessary financial strength to carry out complex environmental protection programs. [ABSTRACT FROM AUTHOR]

There has been a steady decline in carbon dioxide emissions in the world's 19 most industrialized nations even as GDP has increased. These nations' efforts to reduce emissions of carbon dioxide, therefore, to reduction of CO2 and development of renewable energy are the objective of this research. With the years 1995–2019 as a point of reference, we have selected gross domestic product, GDP, RE, industrial upgrading, and import and export as our independent variables. A panel nonlinear autoregressive distributed lag (NARDL) method is utilized to investigate the links between carbon dioxide emission and these independent variables. For the purpose of determining the direction of causation, the panel heterogeneous causality test is used. RE and standards of export and import were shown to be contributing variables in the decrease of carbon dioxide emissions. The environmental Kuznets curve hypothesis was validated by the estimated findings. Increased carbon dioxide emissions are countered by the positive impulses of technological progress, such as R&D development spending and standards of import and export index. Industrial upgrading and emissions of carbon dioxide, gross domestic product and RE, and industrial upgrading and emissions of carbon dioxide, all have a bidirectional causal link. In particular, a one-way causality between gross domestic product and emissions of carbon dioxide, standards of imports and exports, and industrial upgrading, and industrial upgrading and standards of imports and exports is demonstrated. Following the results, policy suggestions are put out. [ABSTRACT FROM AUTHOR]

Among the most fundamental problems today are environmental problems. As people earn higher incomes as a result of getting a good education, their sensitivity to environmental problems increases. As the income level of both the consumers who have received quality education and the producers who make conscious production increases, their demand for environmental quality and their sensitivity to environmental problems will also increase so it is thought that educational expenditures and policies can affect the number and cost of environmental problems. On the other hand, economic activities comprehensively consume natural resources and impact the ecological quality adversely. Therefore, GDP and the educational expenditures variables are used in the model. The aim of this study is to analyze the relationship between environment, education, and economy during the period of 1998–2017 from selected EU countries (Austria, Italy, the Netherlands, Norway, Poland, Portugal, Romania, and Slovakia). As a result of the panel data analysis, according to the Durbin-Hausman cointegration test result, a long-run relationship between the variables was determined at the level of 1%. According to the results of the Dumitrescu-Hurlin causality test, a unidirectional causality relationship from educational expenditures to ecological footprint at the level of 5%, a unidirectional causality relationship from ecological footprint to renewable energy at the level of 1%, and a bidirectional causality relationship at the level of 1% between ecological footprint and GDP were determined. According to the results of Granger causality test based on the VEC model, a unidirectional causality relationship from ecological footprint to educational expenditures at the level of 5%, and bidirectional causality relationship between ecological footprint and renewable energy (from ecological footprint to renewable energy at the level of 10%; from renewable energy to ecological footprint at the level of 1%) were determined. Based on the findings, it can be concluded that economic and educational policy makers should be aware that they have important consequences on environment. [ABSTRACT FROM AUTHOR]

The study investigates the symmetric and asymmetric impact of agriculturalization on CO2 emissions in a sample of selected Asian economies for time period 1985 to 2019. For empirical analysis, the study adopted panel linear and nonlinear autoregressive distributed lag (ARDL) approaches. The long-run findings of panel ARDL reveal that agriculturalization contributes to environmental quality by mitigating CO2 emissions. The panel nonlinear results clearly indicate that the effects of agriculturalization on CO2 emissions are asymmetric. The findings demonstrate that agriculturalization improves environmental quality and de-agriculturalization mitigates environmental quality. Our empirical results are also robust to alternative model specifications. Based on these findings, the study recommends that the relevant authorities should formulate reforms in the agriculture sector that controls and reduces carbon emissions in Asian economies. [ABSTRACT FROM AUTHOR]

Environmental pollution has intensified significantly in the last few decades. Policymakers have considered this issue due to its direct influence on human lives throughout the globe. This study explores the asymmetric determinants of consumption-based and production-based CO2 emissions for China, for time horizon 1990–2019. ARDL and NARDL regression approaches have been adopted for empirical investigation. The ARDL regression method reveals that GDP does not produce any impact on production-based and consumption-based CO2 emissions, while energy use contributes as an increasing determinant of consumption-based and production-based CO2 emissions in the long-run. The NARDL regression method reveals that a positive shock in GDP is beneficial for a decline of consumption-based CO2 emissions, while it does not reduce production-based CO2 emissions in the long-run. However, negative shock in GDP contributes as an increasing determinant of consumption-based CO2 emissions. Results also report that positive shock in energy use behaves as an increasing agent of consumption-based and production-based CO2 emissions in the long-run, while negative shock in energy use produces a decline in production-based CO2 emissions in the long-run. Thus, policymakers should adopt such demand and supply sides' management policies that contribute to controlling CO2 emissions. [ABSTRACT FROM AUTHOR]

Environmental quality and economic activity have a strong relationship. Carbon emissions remain one of the world's most dangerous environmental issues. Both international and local governments are developing initiatives to address this problem. Capitalizing on the limitations of the existing literature, this article investigates the dynamic nexus of financial development, economic growth, and globalization on carbon dioxide emissions in Vietnam for 1990–2020 using the quantile-on-quantile regression. The findings unveil a positive feedback link between globalization and carbon dioxide emissions at the middle and high quantiles. In addition, there is a negative nexus between financial development and carbon emissions at most quantiles, while CO2 emissions and economic growth have a positive association at all quantiles. More importantly, our empirical results also provide the bidirectional causality between financial development, economic growth, globalization, and carbon dioxide emissions in Vietnam at different quantile levels. The consistency of the outcomes uncovers that the findings are trustworthy and appropriate for guiding policy to reduce CO2 emissions in Vietnam. Therefore, they can help policymakers understand how financial development and globalization can achieve sustainable economic growth and tackle environmental issues in this country. [ABSTRACT FROM AUTHOR]

In this study, we want to test the impact of financial inclusion on the economic growth and the environmental quality of OBOR economies. We have selected four different proxies of financial inclusion, two from the perspective of the supply side and two from the perspective of the demand side. For empirical analysis, we have applied 2SLS and GMM methods. In the economic growth model, among the variables of financial inclusion, only the variable of ATMS is positively significant in the 2SLS approach; however, when we apply the GMM approach, two variables, i.e., ATMS and branches, are positively significant implying that supply-side financial inclusion is vital for economic growth in OBOR countries. On the other side, the variables of financial inclusion, whether supply side or demand side, exerted a positive impact on the CO2 emissions irrespective of the estimation techniques, i.e., 2SLS and GMM. These findings imply that financial inclusion, in general, causes CO2 emissions to rise. [ABSTRACT FROM AUTHOR]

It is evident that there is nexus among electricity consumption, foreign direct investment and aggregate economic activity. Unfortunately, the causal relationship among the three variables in Nigeria based on modern econometric methods, recent time-series data and ways that sufficiently cater for inflation and population growth has not been adequately investigated. This study, among other things, used a trivariate vector error correction model, autoregressive distributed lag bounds test for cointegration and Granger causality test to analyse the causal relationship among electricity consumption, foreign direct investment and aggregate economic activity based on time-series data from 1970 to 2018. The study found the presence of neutral causality between electricity consumption and aggregate economic activity in the short run as well as unidirectional causality from aggregate economic activity to electricity consumption in the long run. The study also found the presence of unidirectional causality from foreign direct investment to electricity consumption as well as neutral causality between foreign direct investment and aggregate economic activity in both the short run and the long run. It is therefore recommended that steps should be taken to adequately increase foreign direct investment and aggregate economic activity in ways that will guarantee an optimal increase in electricity consumption in Nigeria. [ABSTRACT FROM AUTHOR]

This study analyzes the causal associations between economic growth (GDP) and biomass energy consumption (BIO) in the US, UK, and BRICS countries for the period 1990 to 2020 in time–frequency space. The use of wavelets is what distinguishes our approach, i.e., cross wavelet transform, wavelet coherence, and the wavelet-based Granger causality method proposed by Olayeni (2016), which quantifies the causal associations in the time–frequency space. The results uncover that the causal relationships between GDP and BIO are not uniform across time and frequency. In fact, there is a positive relationship between GDP and BIO indicators in the BRICS countries in the medium and long term and in the USA and UK in the short term throughout the research period. In addition, a bidirectional causal effect between GDP and BIO exists in China, Brazil, and India, while there is no long-run causal relationship between GDP and BIO in India and South Africa. The causal impacts of economic growth on biomass energy usage are more pronounced in these countries than in the opposite direction, especially over longer time horizons. The key conclusion is that these countries should boost their biomass energy consumption to promote economic growth and reduce energy reliance. [ABSTRACT FROM AUTHOR]

This current study seeks to investigate the policy implication of Turkey's recent energy policies on its sustainable development. This study uses Turkey's country-specific data and series of 1974 to 2018 for effective investigation and justification of the findings of this study with emphasis on both short-run and long-run implications. Three models were fitted to achieve study objectives to accommodate both environmental sustainability and economic impacts. Ecological footprint was considered better measure and used as proxy for the environment related model. In summary, with environment models, the selected series (per capita GDP, industrialization, agriculture, coal as a single energy use, and mixed energy use) except per capita GDP2 were found positively and significantly related to ecological footprint in both short run and long run which translates to poor performance of Turkey's environment. Also, using economic growth model, the selected series (industrialization, energy use, and agriculture) were all confirmed positively and significantly related to the economic growth (per capita GDP). Additionally, environmental Kuznets curve (EKC) was established for Turkey's environment and economic performance. Furthermore, using Granger causality as robust check to these findings, a nexus was found among the series confirming the validity of the cointegration (short- and long-run policies) estimations and results. In congruence with literature and hypotheses, the results from cointegration estimation shows that the twin polices may be good to the economic performance but will spark off adverse effect on environment. [ABSTRACT FROM AUTHOR]

The current research investigates the role of public-private partnership investment (PPPI) and ecological innovation (ECO) along with economic growth on the environmental abatement (i.e., carbon dioxide emission, particulate matters 2.5) in the USA. Quantile autoregressive lagged (QARDL) method was employed during the study period of 1990–2015. The study findings confirm that under long-run estimation, GDP and PPPI are causing more environmental abatement in the form of CO2 emission and haze pollution like PM2.5. The factors like ecological innovation and GDP2 are playing their role towards lowering the CO2 emission and PM2.5 under different quantiles. Furthermore, it is observed that under short-run estimation, past values of the carbon emissions and PM2.5 have their significant and positive relationship with their current values. Besides, the findings through Wald test estimation confirm that parameter constancy of the speed of adjustment parameter is rejected at 1% significance level for the CO2 emission and haze pollution like PM2.5 in USA. Besides, present study also provides some policy implications. [ABSTRACT FROM AUTHOR]

Against the background of energy shortages and severe air pollution, countries around the world are aware of the importance of energy conservation and emission reduction; China is actively achieving emission reduction targets. In this study, we use a symbolic regression to classify China's regions according to the degree of influencing factors and calculate and analyze the inherent decoupling relationship between carbon emissions and economic growth in each region. Based on our results, we divided the 30 regions of the country into six categories according to the main influencing factors: GDP (13 regions), energy intensity (EI; 7 regions), industrial structure (IS; 3 regions), urbanization rate (UR; 3 regions), car ownership (CO; 2 regions), and household consumption level (HCL; 2 regions). Then, according to the order of the average carbon emissions in each region from high to low, these regions were further categorized as Type-EI, Type-UR, Type-GDP, Type-IS, Type-CO, or Type-HCL regions. The decoupling coefficient of the Type-UR region was the smallest with an expansive coupling and weak decoupling, whereas the other regions showed expansive negative decoupling, expansive coupling, and weak decoupling. Among them, the reduction rate of the decoupling coefficient in the Type-EI region was the largest at 6.65%. EI and GDP regions were the most notable contributors to emissions, based on which we provide policy recommendations. [ABSTRACT FROM AUTHOR]

The study explores the association between economic complexity index (ECI), tourism (TR), gross domestic products (GDP), gross domestic products per capita (GPC), and energy prices indices (EPI) on CO2e using the top 18 economic complexity index countries data from 1990 to 2019. We employ the second-generation cointegration methods and cross-sectionally augmented autoregressive distributed lag (CS-ARDL) to analyze the short- and long-term association also Dumitrescu and Hurlin Granger causality test applied. The results of Pesaran and Yamagata slope heterogeneity and Pesaran CD test confirm the presence of cross-sectional unit relationship and slope heterogeneity across countries, while positive long- and short-term associations were found among ECI, GDP, and CO2e. Also, TR, GPC, and EPI decrease carbon emissions both in the long and short term. Moreover, Augmented Mean Group (AMG) techniques verified and support these findings. The outcomes of the Dumitrescu and Hurlin Granger causality test showed that any policy aim at ECI, TR, GDP, GPC, and EPI has a considerable impact on CO2e. Based on the rigorous empirical analysis, we suggest that economic complexity, tourism, GDP, GPC, and energy prices would help alleviate high economic complexity countries' environmental degradation challenges. [ABSTRACT FROM AUTHOR]

Energy consumption is an indispensable element for the purpose of achieving economic growth. Clean energy sources must be put into use to achieve a sustainable environment. The aim of this study is to investigate the relationship among growth, energy consumption, employment, education, and inflation with PVAR, FMOLS, and DOLS analysis in BRICS countries. The study that covers the 2001–2018 observation period included growth as the dependent variable in the equation. The only common result of the three coefficient estimates is that there is no significant relationship between education and growth. However, the increase in income has a decreasing effect on the level of education. The direction of causality between the two variables is from growth to education. Contrary to the PVAR estimate, according to FMOLS and DOLS, energy consumption and employment have a positive contribution towards growth. However, according to PVAR regression results, income growth has a positive effect on employment. Moreover, a unidirectional causal relation from energy consumption to growth and a bidirectional relation between growth and employment have been determined. This one-way relationship between energy consumption and GDP depicts that the growth hypothesis is valid. Furthermore, an energy poverty problem does not exist in BRICS countries. According to FMOLS, DOLS, and PVAR forecasts, the relationship between inflation and growth is complex. In accordance with PVAR estimates, the increase in growth reduces inflation, and the causality from growth to inflation also supports the PVAR results. According to the outcome of the research, energy poverty is not observed in the panel countries. It would be wise for BRICS countries to increase their energy consumption and employment levels in order to increase growth. However, considering the air pollution caused by fossil fuel consumption, it is key that they employ renewable energy sources. [ABSTRACT FROM AUTHOR]

Since the nonlinear ARDL approach is introduced in advanced econometric, some old relationships are getting new empirical attention. Therefore, we examine the asymmetric macroeconomic determinants of carbon dioxide (CO2) emission in China, covering the time from 1971 to 2019 and using a nonlinear ARDL model. The study results show that GDP and industrialization have an asymmetric effect on CO2 emission in long-run in direction and magnitude, while agriculturalization has also an asymmetric effect on environmental pollution in magnitude, but not in the direction. In short, GDP and industrialization have also asymmetric response on CO2 emissions in the short term only in magnitude, but agriculturalization has an asymmetric response in magnitude and direction in short-run. Therefore, this empirical research is more applicable for policymakers in China. [ABSTRACT FROM AUTHOR]

Carbon neutral is among the possible ways of solving the problem of climate change. Many scholars have utilized different single indicators such as CO2 and methane with different variables to mitigate the possible ways of solving the problem of global warming. The present study employs a specific country (UAE) approach to investigate the possible way of solving climate change. The author utilized 1980–2018 annual data of the UAE to investigate the possibility of carbon neutral in the UAE as to suggest ways of limiting climate change. Both linear and non-linear (squared) foreign direct investment (FDI) and GDP per capita were added to the study and considered as the variables of interest and other control variables (energy use and population). Among the findings of this study are inverted U-shaped relationship between economic growth (GDP per capita) and ecological footprint which confirms EKC for the UAE, positive relationship between energy use and ecological footprint, negative relationship between FDI and ecological footprint in all stages which established a flat pattern of relationship, and a positive relationship between the population and ecological footprint. Findings from causal analyses exposed a two-way direction or feedback (bidirectional) between economic growth (GDP) and urban population, and between energy use and urban population both in the short and long run. Also, a one-way transmission (unidirectional) is found transmitting from ecological footprint and FDI to population both in the short run and long run; from the ecological footprint, energy use, and FDI to economic growth; from the ecological footprint and FDI to energy use in the long run; and from ecological footprint to FDI and energy use in the short run. The policy focus should be towards the improvement on the urban population. FDI pattern suggests the pollution halo hypothesis which is a pointer towards its (FDI) crucial contribution to environmental performance. Hence, FDI should be encouraged through relaxing of some laws that are preventive in nature towards FDI so as to maintain this positive trend towards sustainable development. [ABSTRACT FROM AUTHOR]

Global warming is currently the biggest problem. China is the world's highest CO2 emitter. The Chinese authorities agreed to overcome global pollution per the current Paris treaty and have shown deep concern regarding global warming. Hence, policymakers are paying attention to economic policy uncertainty. Motivated by this issue, the study examines the effect of energy use, economic policy uncertainty, and economic growth on China's CO2 emissions from 1970 to 2018 by employing a novel dynamic ARDL simulation model. The findings show that energy use and economic growth have statistically substantial long-run and short-run positive effects on CO2 emissions. However, economic policy uncertainty has a statistically insignificant effect on CO2 emissions, due to firms' sustainability policies. Energy use can have valuable policy consequences, particularly for environmental sustainability. Therefore, based on the empirical findings, the crucial partnership and feedback on China's carbon emission policy should be carried forward. [ABSTRACT FROM AUTHOR]

The study intends to explore the following objectives: initially, to examine the non-linear connection between globalization, renewable energy consumption, and environmental degradation. Secondly, to evaluate the role of globalization in increasing or decreasing the carbon emission at the threshold level for different income countries. Panel smooth transition regression (PSTR) is an econometric technique that has been applied for estimation utilizing the data from 1995 to 2017. Results signify that the globalization and environmental degradation have non-linear connection and depends on different regimes. Moreover, on the basis of estimation, it is considered that the effect beyond the threshold level can be damaging, whereas less than the threshold level globalization is positively related to carbon emission. Hence, the inverted U-shaped relation denotes that at a specific level, the rise in globalization reduces carbon emission, but later, a specific level globalization accumulates carbon emission. Carbon emission has non-linear and regime-dependent relation to economic development and renewable energy consumption. The study provides recommendations that can assist policymakers. [ABSTRACT FROM AUTHOR]

This study explores the linkage between globalization and CO2 emissions in Singapore by using long-term data obtained during 1970–2014. The Zivot-Andrew unit root test corroborates that gross domestic production, economic globalization, political globalization, social globalization, square of economic growth, and carbon dioxide emissions have a unit root at I(0) and stationary at I(1). In this study, the application of auto-regressive distributed lag model finds a significant linkage between the estimated variables. Short- and long-run coefficients confirm that social globalization and economic globalization will be responsible for reduction in carbon dioxide emissions in the future for Singapore. Moreover, this research confirms the presence of environmental Kuznets curve in Singapore. It is proved that a 1% increase in political globalization will increase 2.06% emissions in the long term. The stability of the model is confirmed by diagnostic tests. In addition, policy implications to reduce air pollution are presented in this study. [ABSTRACT FROM AUTHOR]

This study presents a country-specific analysis for three developing countries (Pakistan, India, and Bangladesh) to determine the interaction effect of institutional quality and economic growth along with other control variables (foreign direct investment and renewable energy) on CO2 emissions. This research uses an auto regressive distributed lag (ARDL) model for quarterly data ranging from 1996Q1 to 2016Q4. The findings show that the interaction cause of economic growth and institutional quality on CO2 emissions is not homogeneous in developing countries. In India and Bangladesh, the modifying role of institutional quality is evident to reducing CO2 emissions but in Pakistan, this interacting effect increases CO2 emissions. The findings confirm an inverted U-shaped EKC in Pakistan and Bangladesh but not significant in India. The independent role of GDP and institutional quality significantly reduces CO2 emissions in Pakistan and Bangladesh. [ABSTRACT FROM AUTHOR]

The study aims to analyze two objectives: first is to explore the non-linear relationship between tourism development, economic growth, urbanization, and environmental degradation, and also to analyze the threshold level of the contribution of tourism development on environmental degradation in top tourist arrival destinations. We applied the newly proposed econometric method panel smooth transition regression (PSTR) framework with two regimes on yearly panel data from 1995 to 2017. Findings suggest that the relationship between tourism development and environmental degradation is non-linear and regime dependent. Furthermore, the findings indicated that the relationship above the threshold level is negative and significant, while below the threshold, tourism development is positive and significant effect on environmental degradation. Tourism development and environmental degradation also exhibit the inverted U-shape relationship meaning that at a particular point, increase in tourism development increases in environmental degradation but after a particular point, increase in tourism development decreases the environmental degradation. The economic growth and urbanization also portray a non-linear and regime-dependent relationship with environmental degradation. The study assists policies and empirical information. [ABSTRACT FROM AUTHOR]

In less than two decades, the global tourism industry has overtaken the construction industry as one of the biggest polluters, accounting for up to 8% of global greenhouse gas emissions as reported by the United National World Trade Organization (UNWTO 2018). This position resonates the consensus of the United Nations Framework Convention on Climate Change (UNFCCC). Consequently, research into the causal link between emissions and the tourism industry has increased significantly focusing extensively on top earners from the industry. However, few studies have thoroughly assessed this relationship for small island economies that are highly dependent on tourism. Hence, this study assessed the causal relationship between CO2 emissions, real GDP per capita (RGDP) and the tourism industry. The analysis is conducted for seven tourism-dependent countries for the period 1995 to 2014 using panel VAR approach, with support from fully modified ordinary least square and pooled mean group–autoregressive distributed lag models. Unit root tests confirm that all variables are stationary at first difference. Our VAR Granger causality/block exogeneity Wald test results show a unidirectional causality flowing from tourism to CO2 emission, RGDP and energy consumption, but a bi-directional causality exists between tourism and urbanization. This implies that in countries that depend on tourism, the behaviour of CO2 emission, RGDP and energy consumption can be predicted by the volume of tourist arrivals, but not the other way around. The impulse response analysis also shows that the responses of tourism to shocks in CO2 appear negative within the 1st year, positive within the 2nd and 3rd years but revert to equilibrium in the fourth year. Finally, the reaction of tourism to shocks in energy consumption is similar to its reaction to shocks in RGDP. Tourism responds positively to shocks in urbanization throughout the periods. These outcomes were resonated by the Dumitrescu and Hurlin causality analysis where the growth-induced tourism hypothesis is validated as well as feedback causality observed between tourism and pollutant emission and urbanization and pollutant emission in the blocks over the sampled period. Consequently, this study draws pertinent energy and tourism policy implications for sustainable tourism on the panel over their growth trajectory without compromise for green environment. [ABSTRACT FROM AUTHOR]

Turkish place in industrial activities is strategic, and its involvement in oil and gas importation because of high energy utilization in manufacturing sector is susceptible to high emission. For this, it is required that the economy be researched towards its involvement in both emission inducement and abatement globally. The author adopts ecological footprint and offshored economic activities as proxies to both environment and foreign direct investment (FDI) in ascertainment of Turkish involvement in global emission and decarbonization. Structural break analysis, autoregressive distributed lag–bound testing, and Granger causality were utilized for the effective analysis of the offshore implication of environmental performance in Turkey. The author's findings are as follows: a positive relationship between economic performance (GDP per capita) and ecological footprint, hence giving credence to growth-induced pollution. Also, a positive relationship is established among foreign offshored economic activities (FDI), energy use, and ecological footprint which shows that both energy use and foreign offshored economic activities are positively related to the ecology which established unfavorable impact on the environment. This supports the pollution haven hypothesis (PHH) which is among the theoretical backgrounds of this study. Among the findings established in this study is from Granger causality method which supports the pollution haven hypothesis. They are as follows: a feedback causal transmission between FDI and the ecological footprint, and a one-way causal relationship passing from energy use to ecological footprint. With these findings, it can be said that the environmental implication of foreign offshored economic activities in Turkey is unfavorable. Policy implication of Turkey should be towards moderation of economic growth and the activities of foreign investors for sustainable energy, environment, and growth. [ABSTRACT FROM AUTHOR]

In this modern era, environmental pollution is the biggest problem attached to industrialization. This study tries to ensure the relationship between industrialization and CO2 emissions in Pakistan for the time period 1980–2018 by using nonlinear ARDL model while controlling for urbanization, GDP, and human capital variables as a likely factor of CO2 emissions. Our foremost study objective is to examine whether or not the outcome of industrialization on CO2 emissions is symmetric or asymmetric for Pakistan that is one of the core suppliers to CO2 in South Asia, as the emissions were 0.82 million tons in 2018. Our result approves the presence of an asymmetric effect of industrialization shocks on CO2 emissions both in the short run and long run. The results reveal that industrialization increases emissions and deindustrialization decrease emissions, in short as well as long run, in Pakistan. Moreover, our finding also advises that urbanization and GDP variables have exerted a positive impact on CO2 emissions. Based on the findings, some policy suggestions are proposed for Pakistan. [ABSTRACT FROM AUTHOR]

The study's main purpose is to investigate the complex interaction between innovation, renewable energy consumption, and CO2 emissions (CO2e), under the Kuznets curve framework, for BRICS economies from 1980 to 2016. The empirical estimates drwan from the CCEMG technique highlighted the heterogeneous role of innovation. The results indicated that innovation activities have failed to disrupt CO2e in China, India, Russia, and South Africa, except for Brazil. Second, the data showed that renewable energy consumption has mitigated CO2e in the BRICS panel, Russia, India, and China, excluding South Africa. Third, the existence of the EKC hypothesis was confirmed in all the BRICS economies, excluding India and South Africa. Fourth, the causality estimations reflected a two-way causality between innovation and CO2e; innovation and GDP per capita; innovation and renewable energy consumption; and between CO2e and income, thereby confirming the acceptance of income-led emission hypothesis in for BRICS economies, and vice versa. [ABSTRACT FROM AUTHOR]

This study aims at exploring the impact of corruption control on energy efficiency in 60 countries categorized by income: lower middle (LMI), upper middle (UMI), and high (HI). Panel methodology was utilized taking the period of 2000–2017. As cross-sectional dependence is confirmed among the tested equations, the Pesaran (J Appl Econ 22(2):265–312, 2007) unit root test and the augmented mean group estimator proposed by Eberhardt and Teal (2010) were utilized to overcome this matter. The results in general indicate that the lower the corruption is, the more the energy efficiency for all income group economies. Moreover, renewable energy reduces energy efficiency in lower-middle income and high-income economies while its effect is positive in middle-income economies. In addition, the environmental Kuznets curve (EKC) found to be present in all income group economies. Lastly, causality relationships among energy efficiency, corruption, and GDP were present mostly in upper-middle income and high-income economies. From the results, it was recommended that the countries from all income groups should increase their corruption control for the purpose of enhancing energy efficiency. [ABSTRACT FROM AUTHOR]

This study aims to test the EKC (Environmental Kuznets Curve) hypothesis for the ten states, having the highest levels of carbon dioxide emissions in the USA, through the independent variables of real GDP, population, and renewable energy and fossil energy consumptions. To this aim, the panel estimation method with cross-sectional dependence is applied to data from 1980 to 2015. The empirical findings of the study indicate that the EKC (inverted U-shaped) hypothesis is valid only for Florida, Illinois, Michigan, New York, and Ohio. Interestingly, the negative impacts of fossil energy consumption on CO2 emission levels in Texas are not detected statistically although this state is the leading oil-producing state. Furthermore, the positive impacts of renewable energy consumption in Florida, officially known as "Sunshine State", are considerably low when compared with the other states. [ABSTRACT FROM AUTHOR]

This study has been conducted to examine the impact of trade, economic growth, and renewable energy on environmental degradation in G7 countries. The data consist of the years 1991-2016. We employed the panel unit root test and co-integration test, along with cross-sectional dependence and cross-sectionally augmented IPS unit root test by Pesaran (J Appl Econ 22:265-312, 2007). We also employed dynamic ordinary least squares, fully modified ordinary least squares, and fixed effect ordinary least squares regression. The result concluded that all the variables are co-integrated in the long run and all the variables create a significant effect on CO2 emission. This study implies that economic growth and trade increases the CO2 emission in the long run whereas the renewable energy consumption reduces the CO2 emission in the long run. The result also provides support for the Environmental Kuznets curve hypothesis in G7 countries. [ABSTRACT FROM AUTHOR]