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Sustainable growth and the reduction of environmental pressures are important priorities that are issues of concern for both developed and developing countries. However, while carbon emissions and ecological footprint are commonly used by researchers in the context of environmental deterioration, a broader and more extensive metric for ecological quality is considered necessary. From this perspective, the load capacity factor provides a more detailed sustainable environment appraisal by simultaneously considering biocapacity and ecological footprint. Limited studies have examined the determinants of load capacity factor (LCAP). This survey attempts to fill the gap, using the case of Japan. Employing the dynamic ARDL approaches, the present research investigates the effect of renewable energy usage, economic growth, economic complexity, financial development, and trade globalization on load capacity factor in Japan for the period between 1980 and 2017. The empirical evidence indicates that economic complexity, economic growth, and financial development adversely impact LCAP, whereas renewable energy usage and trade globalization positively affect LCAP. Hence, we recommend that it is essential for Japan to attain self‐sufficiency in essential goods and minimize its reliance on the rest of the world. Furthermore, policymakers should capitalize on the benefits of trade globalization by adopting additional measures aimed at facilitating trade liberalization. [ABSTRACT FROM AUTHOR]

The pursuit of decarbonization has created an awareness globally in relation to geothermal energy, either for electricity generation or direct usage, since fuel combustion is not needed. Premised on this intriguing detail, this present research scrutinizes the impact of geothermal energy on CO2 emissions in the top seven geothermal energy-consuming nations. Using the quarterly dataset of geothermal and CO2 emissions stretching over the period between 1990 and 2019. The quantile-on-quantile (QQ) approach, which considers the conventional quantile analysis and nonparametric, is utilized in this research to provide more accurate and robust estimations. Furthermore, the QQ approach differentiates the impacts of geothermal energy on CO2 emissions into three quantiles: upper, medium, and lower. Additionally, the nonparametric causality-in-quantiles is used to evaluate the causation in quantiles between geothermal and CO2 emissions. From the outcomes of the QQ approach, we discovered that in several quantiles, geothermal energy mitigates environmental deterioration, wherein CO2 emission is reduced in Italy, Mexico, and New Zealand. However, geothermal energy boosts CO2 emissions in India, the USA, Turkey, and the Philippines. Furthermore, the nonparametric causality-in-quantiles discovered that geothermal energy predicts CO2 emissions in all nations. [ABSTRACT FROM AUTHOR]

The current study evaluates the effect of financial development (FD), economic growth (GDP), trade globalization (TGLO), renewable energy consumption (REC), and human capital (HC) on ecological footprint (ECF) in Italy using data between 1985 and 2018. We further assess the combined impact of trade globalisation and human capital on ecological footprint as well as the combined effect of trade globalisation and human capital on ecological footprint. In order to explore these associations, the present research utilizes autoregressive distributed lag (ARDL) to catch both long and short-run associations between ecological footprint and its drivers. Furthermore, we use dynamic OLS (DOLS) and fully modified OLS (FMOLS) long-run estimators as robustness checks. Lastly, causality at different frequencies is captured using the frequency domain causality test. The outcomes of the ARDL estimator disclose that (a) a surge in ecological footprint is attributed to an increase in economic growth; (b) a decrease in ecological footprint is attributed to an increase in renewable energy, trade globalisation, and human capital; (c) the combined impact of human capital and trade globalisation lessen ecological footprint, and (d) combined effect of trade globalisation and human capital mitigate ecological footprint in Italy. Furthermore, the outcomes of the causality test revealed that all the exogenous variables can significantly predict ecological footprint in the long run with the exemption of financial development. Based on the study's findings, an SDG-focused policy framework is advocated. [ABSTRACT FROM AUTHOR]

Several developing markets, such as Brazil, Russia, India, China, and South Africa (BRICS), are facing challenges in attaining the targets set with regard to the Sustainable Development Goals (SDGs). While previous studies have extensively examined the Environmental Kuznets Curve in BRICS nations, focusing on other proxy of environmental degradation like CO2 emissions and ecological footprint, little attention has been given to the Load Capacity Curve (LCC) hypothesis specifically in relation to emerging economies. Consequently, there exists a gap in the literature regarding the validation of the LCC hypothesis for these economies. To bridge this gap, our research intends to assess the validity of the LCC hypothesis in the context of the BRICS countries. Specifically, we investigate the impact of biomass energy and social globalization on the load capacity factor (a proxy for ecological quality) in the BRICS countries from 1990 to 2018, while considering the roles of economic growth and natural resources. Additionally, we explore the development of an SDG framework tailored for the BRICS nations, which can serve as a blueprint for other emerging economies. To analyze the data, we employ the Method of Moments‐Quantile‐Regression (MMQR) approach along with long‐run estimators. The findings of the MMQR analysis reveal that natural resources, social globalization, and gross domestic product have adverse effects on ecological quality, while biomass energy exhibits a positive influence on ecological quality. Furthermore, our research validates the LCC hypothesis for the BRICS economies. We also observe evidence of causality between the load capacity factor and its determinants. Based on our investigation, we recommend a transition in energy policies from hydrocarbon energy to sustainable energy options by implementing innovative approaches to biomass technology that can enhance conversion efficiency. Implementing these policy changes will not only enhance ecological quality but also align the SDG targets. [ABSTRACT FROM AUTHOR]

Recognizing the paramount importance of health, the United Nations Development Program has outlined sustainable development goals, emphasizing Goal 3, which focuses on ensuring and promoting healthy lives and well‐being for all. Consequently, this study delves into the determinants of healthcare expenditure (HCE), specifically focusing on financial development (FDV), tourism (TOR), technological innovations (TINs), economic growth (EG), and climate change in the United States. The investigation utilizes data spanning from the first quarter of 2000Q1 to the fourth quarter of 2020Q4. To achieve this objective, we employed innovative quantile‐based methodologies, including wavelet quantile regression and quantile‐on‐quantile Granger causality. These approaches facilitated a comprehensive exploration of the dynamic interactions between HCE and its influencing factors across various quantiles and periods. The wavelet quantile regression and quantile‐on‐quantile regression analysis findings consistently indicate a positive impact of CO2, TOR, EG, globalization, FDV, foreign direct investment, and TIN on HCE in the United States. Furthermore, the results obtained from the quantile‐on‐quantile Granger causality demonstrate that CO2 emissions, TOR, EG, globalization, FDV, foreign direct investment, and TIN significantly predict HCE across all quantiles. These insights have informed the formulation and implementation of various policies addressing the complex interplay between healthcare spending and its driving factors. [ABSTRACT FROM AUTHOR]

The G7 nations is a major global consumers of natural resources and energy. These nations are confronted with substantial obstacles in their pursuit of sustainable growth through energy transition, while upholding their status as global economic leaders. As a result, this current study conducted an aggregated and disintegrating analysis on the heterogeneous role of green energy innovation on energy transition in G7 nations. Green energy innovation was disintegrated into hydro, solar and wind energy. Moreover, the heterogeneous effects of green innovation in solar, hydro and wind on energy transition was investigated, an analysis that has not been previously examined. For the econometric estimation, we adopted the Quantile-on-Quantile Regression (QQR) and the quantile causality method. The results of the QQR indicates that the positive role of green energy innovation on energy transition in all of the G7 nations. However, this positive role is more dominant in five G7 nations, namely Italy, Germany, Japan, the UK and the USA. Additionally, the result also highlights that the connection between green energy innovation and energy transition is differs across the various quantiles for different nations. Moreover, the quantile causality analysis indicates that green energy innovation has the potential to predict future values in energy transition within the G7 nations. The study emphasizes various policy considerations for promoting energy transition through green energy innovation in G7 nation, which help realizing sustainable development. [ABSTRACT FROM AUTHOR]

Limiting CO2 emissions is crucial for sustainable development, environmental protection, and climate change mitigation, ensuring a more resilient and cleaner future. Prioritizing sustainable urbanization renewable energy, and energy efficiency is vital for achieving this prosperous and sustainable future. As a result, we adopt the Fourier testing approach for stationary, cointegration, estimator, and causality, to scrutinize the role of renewable energy, energy efficiency, and urbanization on CO2 emissions in Finland over the period between 1990 and 2020, controlling economic growth and trade openness. The empirical analysis of the Fourier ARDL estimator establishes that energy efficiency measures such as gas and oil efficiency exhibit an adverse effect on CO2 emissions, so energy efficiency mitigates CO2 emissions. Similarly, the study also found that urbanization and renewable energy reduce CO2 emissions. Conversely, economic growth and trade openness induce CO2 emissions. Additionally, the Fourier-Toda-Yamamoto method provides robust evidence regarding the long-term implications of the examined factors. Based on this result, the study emphasizes that implementing a regulatory framework to enhance energy efficiency, promote renewable energy adoption, and support sustainable urban development will be an essential strategy in the global effort to attain the net-zero emissions target, which offers valuable insights to other countries seeking to transition towards cleaner and more sustainable energy sources. [ABSTRACT FROM AUTHOR]

Malaysia's commitment to ecological quality is evident in its agendas for achieving a sustainable environment by 2030. However, hindrances like challenges towards energy transition efforts, stable political institutions, unclean economic globalization practices, and transiting to a complex economy could potentially delay the nation's attainment of its environmental goals. Against this backdrop, the current study focuses on examining the roles of political risk, economic globalization, energy transition, and economic complexity on ecological sustainability in Malaysia. In contrast to previous studies, this study innovatively incorporates a dummy variable to account for potential structural breaks that may occur during the study period. Furthermore, this study used an innovative environmental proxy which incorporates both the demand and supply aspect of the environment during computation. Using the time series data from 1984 to 2018 and employed the ARDL estimator method, the empirical results indicate that economic globalization is associated with ecological deterioration in Malaysia in the long run. On the other hand, economic complexity, political stability, and energy transition are shown to promote ecological sustainability in Malaysia in the long run. Moreover, the bootstrap time varying causality method demonstrates that each of the regressors has the capacity to predict the load capacity factor during distinct sub-periods. [ABSTRACT FROM AUTHOR]

Several nations, including Mexico, are encountering problems with accomplishing the targets of sustainable development goals (SDGs). This study addresses how to develop SDG agenda for Mexico, which may also be applied to other emerging markets with comparable profiles. Therefore, this study utilizes a newly developed load capacity factor (LCF, a detailed environmental evaluation tool) that combines biocapacity (supply side) and ecological foot (demand side) to examine the effect of renewable energy consumption and trade openness on LCF while controlling for nonrenewable energy consumption and economic growth in the case of Mexico during 1970–2017. Using the dual adjustment approach, we find evidence of long-run cointegration nexus among the series. In addition, trade openness affects LCF positively, whereas renewable energy consumption, economic growth, and nonrenewable energy consumption impact LCF negatively. Furthermore, results of the frequency domain causality show that all the variables can predict LCF in the long-term. Based on these results, Mexico should focus on promoting public understanding of green energy and environmental preservation measures and participate in the production of nonenergy-consuming and ecologically friendly products while compelling polluting enterprises to migrate to countries with less stringent environmental restrictions. [ABSTRACT FROM AUTHOR]

The present millennium records the most devastating effects of global warming than what was evident in the pre-industrial era. The pervasive effects of global warming have raised concerns about the sustainability of the present and future generations. Hence, researchers are working assiduously towards proffering the most effective method of halting the surging emissions from global, regional, and national angles. This study contributes to the extant literature by providing the first empirical verification of how renewable energy, technological innovations, trade openness, and transport services impact carbon emissions in Germany. The empirical evidence is anchored on annual time series data from 1990 to 2020 estimated using the novel nonlinear ARDL to explore the positive and negative shocks associated with the short and long-run nexus. The wavelet coherence estimator is equally for ascertaining the multiple time scales in the time series and extends the knowledge frontier to the literature. The following findings are eminent from the overall analyses. First, long-run cointegration is supported among the variables of interest Second, only the adverse effects of renewable energy and technology are substantial enough to mitigate carbon emissions. The trade-induced emissions are established with the positive impacts of trade openness on carbon emissions. Transport services contribute significantly to carbon emissions in the long-run and short-run periods. However, mitigating effects of small magnitude are apparent in the long-run due to the perceived transition to green transportation. Policy implications supporting the transition to 100% renewable energy and green transportation are significant steps towards achieving Germany's carbon neutrality target. [ABSTRACT FROM AUTHOR]

Climate change can be mitigated and policies can be catalyzed with the aid of financial institutions. By maintaining and strengthening financial stability, the financial sector's resilience could help mitigate climate‐related risks and uncertainties. Hence, an empirical investigation on the effect of financial stability on consumption‐based CO2 emissions (CCO2E) in Denmark is long overdue. This study investigates the financial risk‐emissions relationship in the presence of energy productivity, energy consumption, and economic growth in Denmark. Furthermore, by adopting an asymmetric approach to analyze the time series data for the period between 1995 and 2018, this study helps bridge this major gap in the literature. By adopting the nonlinear autoregressive distributed lag approach (NARDL), we discovered that the positive variation in financial stability causes a reduction in CCO2E, but the neutral connection was reported between the negative shock in financial stability and CCO2E. The positive shock in economic growth and energy consumption intensifies CCO2E; however, a neutral interaction exists between the negative shock in economic growth and CCO2E. The negative shock in energy consumption has a positive effect on CCO2E, indicating a mitigating implication on environmental degradation. In addition, a positive shock in energy productivity enhances environmental quality, while a negative shock in energy productivity increases environmental degradation. In light of the results, we suggest some robust policies for Denmark and other smaller but wealthy nations. Moreover, in order to develop sustainable finance markets, policymakers in Denmark need to mobilize both public and private finance while maintaining a balance with other economic needs of the nation. The country must also identify and understand potential avenues for scaling up private financing for mitigating climate risk. Integr Environ Assess Manag 2023;19:1485–1494. © 2023 SETAC Key Points: Positive shock in financial stability mitigates consumption‐based CO2 emissions, while the negative shock has neutral effect on consumption‐based CO2 emissions in Denmark.‐. A positive shock in energy productivity enhances the environmental quality, while a negative shock in energy productivity promotes ennvironmental degradation [ABSTRACT FROM AUTHOR]

This research explores the role of green resource productivity, renewable energy, economic globalization, and economic growth towards advancing the pursuits of decarbonization in top energy transition economies. This study achieves this objective by adopting both asymmetric and symmetric econometric methods for the period between 1990 and 2021. This study adopted the Method of Moments Quantile Regression (MMQR) to uncover the asymmetric effect of the regressors on carbon emissions. The MMQR results suggest that in all quantiles, green resource productivity, renewable energy, and economic globalization mitigate CO2 emissions, while economic growth induces CO2 emissions. Additionally, for the robustness analysis, we disaggregated economic globalization into trade and financial globalization and investigated their roles towards achieving decarbonization. We uncovered that financial globalization mitigates CO2 emissions at all quantiles, but at the lower and middle quantiles, trade globalization mitigates CO2 emissions. Moreover, for the symmetric estimation, the following estimators: Fixed effect Ordinary Least Square, Fully Modified Ordinary Least Square, and Dynamic Ordinary Least Square estimators were employed in this study. Their outcome corroborated the findings of this MMQR. For the Granger causality inference, the outcome suggests that there is a bi-directional causality between renewable energy and CO2 emissions. Furthermore, we find a feedback causality association between financial globalization and CO2 emissions, and a one-way causal interconnection is detected from CO2 emissions to trade globalization. Moreover, we detected that there is a causal association flowing from economic globalization to CO2 emissions. Finally, an unidirectional causal interaction is detected from economic growth to CO2 emissions. Consequently, the research's findings provide applicable policy. [ABSTRACT FROM AUTHOR]

In the current sustainable growth framework, the role of renewable energy cannot be overemphasized. Furthermore, several sustainable development targets necessitate the optimal utilization of biomass energy. Their benefits, trade-off dynamics, and implementation vary according to geography, necessitating an in-depth examination to manage their influence. Therefore, we investigated the impact of biomass energy utilization on the ecosystem in the top ten biomass-consuming nations: India, Austria, Brazil, China, Germany, Sweden, Finland, Italy, the United Kingdom, and the United States. To compare the impact of biomass energy utilization on ecological footprint, this study employed a quarterly dataset covering the period between 1970 and 2018. To achieve this objective, we used the Quantile-on-Quantile approach, which suggests that biomass improves environmental quality in six nations (i.e. Austria, Brazil, China, Germany, Sweden, and United Kingdom) but it degrades the environment in the other countries (i.e. Finland, Italy, India, and the USA). Furthermore, the study employed the Granger causality test in quantile, and the results indicate that biomass energy utilization and ecological footprint can predict each other in nine nations (i.e. Austria, Brazil, China, Germany, Sweden, Finland, Italy, UK, and the USA). However, for India, we detected the absence of causality between biomass energy and ecological footprint. Based on this outcome, this study suggests policies such as intensifying and coordinating the transition from traditional to contemporary biomass, which might increase the green impacts of biomass use, hence lowering environmental degradation. This transition will strengthen the energy efficiency of biomass energy generation, providing additional opportunities to revitalize the forest areas. [ABSTRACT FROM AUTHOR]

Despite Portugal's effort to reduce carbon emissions, the country still emits about 1.6% of the European Union's CO2 emissions. Meanwhile, limited empirical studies have been undertaken in the context of Portugal. As a result, this study examines the asymmetric and long-term impact of CO2 intensity of GDP, energy consumption, renewable energy and economic growth on CO2 emissions in Portugal from 1990 to 2019. The nonlinear autoregressive distributed lag (NARDL) is employed to uncover the asymmetric connection. The findings show that there is nonlinear cointegration among the variables. The long-run estimation reveals a positive change in energy consumption positively affects CO2 emissions, while a negative shock in energy consumption has a neutral effect on CO2 emissions. Furthermore, positive shocks of economic growth and CO2 intensity of GDP enhance environmental deterioration by increasing CO2 emissions. Meanwhile, the negative shock of these regressors positively impacts CO2 emissions. In addition, positive shocks in renewable energy enhance environmental quality, while negative shocks in renewable energy increase environmental deterioration in Portugal. Policymakers should focus on reducing per-unit energy usage and CO2 efficiency gains, which would necessitate a significant reduction in CO2 intensity and energy density of GDP. [ABSTRACT FROM AUTHOR]

The present study aims to discover the impact of political risk, globalization and technological innovation on the ecological footprint in the BRICS economies by employing a dataset covering the period between 1990 and 2017 and incorporating non-renewable energy utilization and economic growth as other regressors through the utilization of panel quantile regression. The outcomes established that economic growth, non-renewable energy usage, political risk and technological innovation increase ecological footprint. Conversely, globalization significantly decreases the ecological footprint. The panel ordinary least squares approach serves as a sensitivity test for the robustness of the analysis. Furthermore, the Dumitrescu-Hurlin panel causality test confirmed that a bidirectional causal interaction exists between ecological footprint and the regressors of technological innovation, globalization, non-renewable energy and economic growth, while a one-way causal interconnection runs from ecological footprint to political risk. Notably, the general policy suggestion indicates the need for policymakers to intensively coordinate efforts to combat the serious environmental deterioration in the BRICS economies. [ABSTRACT FROM AUTHOR]

Investigating the drivers of CO2 emissions is essential for limiting global warming, which has sparked widespread concern. This study evaluates the association between economic complexity and CO2 emissions in China, considering the effect of disintegrated energy and financial globalization on the environmental function between 1970 and 2018. This dataset was analyzed using the autoregressive lag model (ARDL) and frequency-domain causality approaches. The ARDL unveiled that urbanization, economic complexity, financial globalization, and economic growth deteriorate the environment while environmental sustainability is achieved through renewable energy utilization. The study also validates the Environmental Kuznets Curve hypothesis. Also, the frequency-domain causality disclosed that all regressors (economic growth, financial globalization, economic complexity, and urbanization) could forecast CO2 emissions in China at different frequencies. Based on these outcomes, policy recommendations are formulated. [ABSTRACT FROM AUTHOR]

This paper bridges the gap in the literature by employing the novel quantile-on-quantile (QQ) approach, the quantile regression approach, and the nonparametric Granger causality test in quantiles to assess the effect of international trade on consumption-based carbon emissions (CCO2e) in Uruguay. Our study incorporates other drivers of CCO2 emissions, such as financial development and renewable energy, into the model. We find that, in the majority of the quantiles, exports, financial development, and renewable energy exert a negative impact on CCO2e, and the influence of imports on CCO2e is positive in all quantiles. Moreover, the quantile regression approach is used as a robustness test for the quantile-on-quantile approach. The causal interaction from the regressors to CCO2e is evaluated using the nonparametric Granger causality test in quantiles. The outcome of the nonparametric Granger causality test in quantiles suggests that imports, exports, renewable energy, and financial development can predict CCO2e at different quantiles. Based on these outcomes, we recommend that the financial sector must strengthen its focus on giving funding to enterprises that embrace environmentally friendly technologies and incentivize them to employ other energy-efficient technologies for manufacturing reasons, thereby preventing environmental deterioration. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Emerging Economies & Policy is the property of JOEEP: Journal of Emerging Economies & Policy and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Globally we are at a crossroad whereby energy production and consumption in themselves is partly blamed for climate change issues and global warming menace. The question that comes to heart is do we stop seeking energy production and consumption? of course no. Thus, there is a need for innovation on part of economies as they seek energy for sustainable development. This country-specific study focuses on South African, which reflects the above highlights menace in no small measure where her economic growth trajectory is plagued with high CO 2 emission. To this end, we explore the nexus between coal energy consumption, economic growth, renewable energy consumption and CO 2 emission between annual periods of 1980–2017. This study applied a battery of econometric techniques to underscore the relationship between the outlined variables. According to the ARDL bounds test to cointegration in conjunction with Kripfganz and Schneider (2018) critical approximation p-values both affirm long-run equilibrium relationship between study variables. Empirical evidence gives credence to the growth-induced pollution emission in South Africa as reported by the Autoregressive distributed lag Method, fully modified ordinary least squares and dynamic ordinary least squares as robustness test for soundness of analysis. This finding suggests that South Africa's economic growth trajectory is not clean. This preposition is resonated with the result of coal energy consumption also dampening environmental quality. Financial development shows strong statistical strength to improve the quality of the environment. These outcomes are indicative for policymakers as there is urgent need to energy transition from conventional energy based on fossil fuel (coal energy) to renewable energy mix which is more environmentally friendly should be pursued in South Africa. [Display omitted] [ABSTRACT FROM AUTHOR]

Following the United Nations Sustainable Development Goals (UN-SDGs), which place emphasis on relevant concerns that encompass access to energy (SDG-7) and sustainable development (SDG-8), this research intends to re-examine the relationship between urbanization, CO2 emissions, gross capital formation, energy use, and economic growth in South Korea, which has not yet been assessed using recent econometric techniques, based on data covering the period between 1965 and 2019. The present study utilized the autoregressive distributed lag (ARDL), dynamic ordinary least square (DOLS), and fully modified ordinary least squares (FMOLS) methods, while the gradual shift and wavelet coherence techniques are utilized to determine the direction of the causality. The ARDL bounds test reveals a long-run linkage between the variables of interest. Empirical evidence shows that CO2 emissions trigger economic growth. Thus, based on increasing environmental awareness across the globe, it is necessary to change the energy mix in South Korea to renewables to enable the use of sustainable energy sources and establish an environmentally sustainable ecosystem. Moreover, the energy-induced growth hypothesis is validated. This result is supported by the causality analysis, which shows a one-way causality running from energy consumption to GDP in South Korea. This suggests that South Korea cannot embark on conservative energy policies, as such actions will damage economic progress. Additionally, a unidirectional causality is seen from CO2 emissions and energy consumption to economic growth. These findings have far-reaching consequences for GDP growth and macroeconomic indicators in South Korea. [ABSTRACT FROM AUTHOR]

CO2 emission is one the major contributor to climate change that the top CO2 emitting countries are always trying to mitigate. In an attempt to fill the gap in energy and environmental literature, this study explores the interaction between economic growth, energy usage, trade and urbanization on CO2 emission for MINT economies using the time coverage from 1980 to 2018, providing new perspectives into the literature by employing panel data analysis. Aiming to create robust outcomes, this paper deployed both conventional and modern econometric techniques. The panel co-integration test revealed evidence of the co-integration between CO2 and its determinants in the MINT economies. In order to explore the linkages between CO2 and its determinants, the ARDL PMG model was utilized in MINT economies. Findings based on the ARDL PMG reveals; (i) positive interconnection between CO2 emissions and energy usage; (ii) no significant link was found between CO2 and economic growth; (iii) urbanization influence CO2 positively while a negative link was found between CO2 and trade. Furthermore, the Dumitrescu-Hurlin Causality test revealed; (i) uni-directional causality from CO2 to urbanization; (ii) GDP growth cause CO2 while CO2 causes energy usage. Based on these findings, recommendations were put forward. [ABSTRACT FROM AUTHOR]

Copyright of EUL Journal of Social Sciences / LAÜ Sosyal Bilimler Dergisi is the property of EUL Journal of Social Sciences and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)