The symmetrical and asymmetrical effects of foreign direct investment and financial development on carbon emission: evidence from Nigeria

Understanding the interplay of GDP, renewable, and non-renewable energy on carbon emissions: Global wavelet coherence and Granger causality analysis

This study examines the causality of Per Capita Gross Domestic Production (PGDP), Renewable Energy Consumption (REC), and Non-Renewable Energy Consumption (NREC) on Carbon dioxide (CO2) emissions at the global level utilising data gathered from 1995 to 2020 across various countries categorised based on income levels as High, Low, Upper Middle and Lower Middle and analysed through wavelet coherence. The findings reveal both bidirectional and unidirectional causality between the variables which have evolved. Globally, a bi-directional relationship is observed with a positive correlation between PGDP and NREC and in contrast, a negative correlation with REC. Furthermore, the analysis highlights varying causalities between CO2 emissions and PGDP, except for high-income and lower-middle-income country categories, all other shows one-way causality in different periods in the short term. Moreover, CO2 and REC, show unidirectional causality throughout the short-term, exceptionally medium & long term have both unidirectional and bidirectional causalities across all country categories with a positive correlation. In contrast, CO2 and NREC depict similar causalities to REC, however, with a negative correlation. A cross-country analysis was performed between CO2 and PGDP, CO2 and REC, and CO2 and NREC using Granger causality which shows mixed relationships. The findings hold significant implications for policymakers, providing valuable insights into the trade-offs between economic growth, energy consumption, and carbon emissions.

Linking energy-based circularity with environment in high-income economies

A circular economy is a regenerative approach that emphasizes resource efficiency, waste reduction, and the reuse of materials for a sustainable world. By adopting circular practices, we can reduce the negative impact of traditional linear economic models on the environment. According to the International Renewable Energy Agency (IRENA), the world is generating only 26% of total energy production from circular practices, which positively impacts environmental health. Therefore, this study aims to evaluate the empirical estimation of circular practices regarding energy on the environment. The current study focuses on the association between the circular economic index, economic growth, trade, digitization, energy use, and the financial development index on the environment in 29 high-income countries from 1990 to 2019. The study employs the second-generation econometric technique Driscoll-Kraay to empirically estimate the association among the variables of interest after confirming cross-sectional dependency within the data set. The study findings reveal that circular practices improve high-income countries' environmental conditions. Furthermore, the study confirms the association between economic growth, financial development index, energy use, trade, and digitization on the environment, and it leads to a more sustainable situation. Policies are drawn based on findings for policymakers toward a sustainable world.

Empowering renewable energy consumption through public-private investment, urbanization, and globalization: Evidence from CS-ARDL and NARDL

This study examines the interrelationship among public-private investment, urbanization, globalization, and renewable energy consumption in the BIMSTEC nations for 1995-2021. The study implemented linear and nonlinear frameworks to document the magnitudes of explanatory variables on REC. Referring to the study findings with CSD, CIPS, CADF, and PCT disclosed the presence of cross-sectional dependency; variables are integrated after the first difference, i.e., I (1), and long-run association. According to symmetric and asymmetric coefficients, Public-private partnerships and globalization have emerged as significant catalysts for developing renewable energy sources. At the same time, urbanization is exposed to an adverse tie with REC, especially in the long-run. Based on the abovementioned findings, the study presents crucial policy recommendations to facilitate the expeditious transition to renewable energy within the BIMSTEC nations. Policymakers should prioritize the cultivation of robust public-private partnerships, the provision of incentives for investments in renewable energy, and the formulation of comprehensive regulatory frameworks.

Exploring the optimal threshold of FDI inflows for carbon-neutral growth in Africa

This study investigates the relationship between foreign direct investment (FDI) and CO2 emissions in Africa, primarily emphasizing carbon-neutral growth. Employing advanced econometric methods like the Generalized Method of Moments (GMM), fixed effect, and Two-Stage Least Squares (2SLS), we identify critical threshold values for key variables, including economic growth, trade openness, human capital, financial development, inflation, and population growth. Our findings indicate that GDP significantly influences the FDI-CO2 emissions relationship as economies expand, shifting from negative to positive, potentially leading to increased carbon emissions. Higher trade-to-GDP ratios are associated with reduced CO2 emissions due to cleaner technologies and greener production practices. Additionally, financial development plays a pivotal role, enabling investment in sustainable technologies. Nations with a more skilled workforce are more likely to adopt sustainable practices. The influence of population growth on CO2 emissions is complex, balancing increased demand with investments in clean technologies. The study recommends that African policymakers prioritize FDI aligned with carbon-neutral growth by promoting sustainability, investing in human capital, and carefully balancing population growth with sustainability.

Asymmetric impact of technological innovation, foreign direct investment and agricultural production on environmental degradation: evidence from Pakistan

The present study analyzes the asymmetric effects of technical innovation, foreign direct investment, and agriculture productivity on Pakistan's environmental degradation from 1990 to 2020. A non-linear autoregressive model (NARDL) has been used for the analysis. The asymmetric effects have been computed for both the long and short run. The empirical results show that there is equilibrium long-run relationship among the variables. Moreover, it is found that the effect of FDI on CO2 emission is positive regardless of whether there are positive or negative shocks to FDI in the long run. The short-run results are similar except for the positive shocks to FDIat lag one, which reduces environmental degradation in Pakistan. However, in the long run, population growth and positive (negative) shocks to technical innovation have a negative and significant impact on CO2, whereas agriculture productivity is the main source of environmental degradation in Pakistan. The asymmetric tests show that FDI and agriculture productivity have strong asymmetric effects on the CO2 emissions in the long run, whereas there is weak evidence of, in the short and long run, asymmetric effects of technical innovations in Pakistan. These results are statistically significant, valid, and stable as per most of the diagnostic tests conducted and reported in the study.

Evaluating the total-factor efficiency of E3 in oil-producing countries, with emphasis on education

Global warming is one of the greatest challenges of the contemporary world. Overcoming this problem requires a global determination in energy management and a significant reduction in the use of fossil fuels worldwide. The objectives of this article are to investigate the role of education in economic growth and to evaluate the total-factor energy, economic and environmental efficiency (E3) of oil-producing countries and productivity changes between 2000 and 2019. These countries were divided into two categories of middle- and high-income ones. The panel data model was used to estimate the role of education in the countries' economic growth, and the data envelopment analysis (DEA) method was used to measure their total-factor efficiency (E3). The findings indicate that education has a positive role in economic growth. In general, Norway proved to be efficient in all indicators of e1, e2, e3, and E3. The worst performance in e1 belonged to Canada (0.45) and Saudi Arabia (0.45); in e2, to Algeria (0.67) and Saudi Arabia (0.73); in e3, to the USA (0.04) and Canada (0.08); and in E3, to Canada (0.46), Saudi Arabia (0.48), and the USA (0.64). The average total-factor efficiency of all indicators for the selected countries was low. Average changes in total-factor productivity and technological changes for all the selected countries had decreased in e1 and e3 but improved in e2 and E3 during the studied period. The changes in technical efficiency also decreased during the period. Moving towards a low-carbon economy, developing creative and environment-friendly technologies, more investment in clean and renewable energy, and creating diversity in production, especially for OPEC and countries with single-product economies, are some of the ways suggested for improving E3 efficiency in the countries.

The impact of foreign direct investment on China's industrial carbon emissions based on the threshold model

In recent years, the number of countries concerned about environmental protection continues to increase. With a continuous expansion of economic scale, many emerging markets are also sustainably enhancing their management for industrial carbon emissions in foreign direct investment (FDI). Therefore, the impact of FDI on the host country's industrial carbon emissions has been a hot topic of researches. This study selects panel data of 30 medium and large cities in China from 2006 to 2019. Combined with dynamic panel GMM estimation and panel threshold model, this study empirically analyzes the impact factors of FDI on the host country's industrial carbon emissions. This study is based on the perspective of dual environmental management systems. This study draws the following conclusions: When taking the dual environmental management system factors as threshold variables into the empirical research process, only the FDI in Beijing, Tianjin, and Shanghai shows a certain inhibitory effect on Chinese industrial carbon emissions. The FDI in other cities increases the scale of industrial carbon emissions. At the same time, in the formal environmental management system, FDI has no significant impact on China's industrial carbon emissions. It indicates that the formal environmental management system of each city is not effective in policy formulation or implementation. In addition, the corresponding role of environmental management systems, such as innovation compensation and mandatory emission reduction, is not played. With the exception of Beijing and Shanghai, informal environmental management systems in other cities help curb the scale of industrial carbon emissions brought by FDI.

The impact of natural resource rent, financial development, and urbanization on carbon emission

There is a shred of evidence of environmental degradation in the form of carbon emissions to behave differently when tested with different macroeconomic variables. This paper aims to examine the long-run and short-run association between natural resource rent, financial development, and urbanization on carbon emission from the context of the USA during 1995-2015 with the help of a contemporary and innovative approach named quantile autoregressive distributed lagged model (QARDL). The stated approach is applied due to the fact that non-linearity is observed for the study variables. The findings indicated that the higher financial development (0.304), natural resource rent (0.102), and urbanization (0.489) have a positive impact on the environmental degradation in the region of USA during long-run estimation in the stated quantiles of the study. This would indicate that higher financial development, urbanization, and natural resources are putting more environmental pressure on the economy of the USA. Similarly, the findings under short-run estimation confirm that past and lagged values of carbon emission, financial development, natural resource rent, and urbanization are significantly determining the current values of the carbon emission. For this reason, it is suggested that the government requires some immediate steps of the USA to control the harmful effect of such financial development, more urbanization, and higher natural resource rent as well. This would indicate the reflection of some green strategies in all three explanatory variables to generate some fruitful environmental outcomes.

An econometric evaluation of the effects of economic growth, energy use, and agricultural value added on carbon dioxide emissions in Vietnam

Global climate change caused by Greenhouse Gases (GHGs), particularly carbon dioxide (CO₂) emissions, poses incomparable threats to the environment, development and sustainability. Vietnam is experiencing continuous economic growth and agricultural advancement, which causes higher energy consumption and CO₂ emissions. Understanding Vietnam’s sensitivity to climate change is becoming more crucial for governments trying to reconcile climate change mitigation and sustainable development. Analyzing pollution-development trade-offs can help minimize environmental degradation in Vietnam. Therefore, the present study empirically investigated the nexus between economic growth, energy use, agricultural added value and CO₂ emissions in Vietnam. To investigate the short-run and long-run relationships between the variables, this study employed the autoregressive distributed lag (ARDL) technique and the Vector Error Correction Model (VECM) using the time series data from 1984 to 2020 for Vietnam. The empirical findings indicated that economic growth and energy use trigger environmental degradation by increasing CO₂ emissions, whereas enhancing agricultural added value improves Vietnam’s environmental quality by reducing CO₂ emissions in both the long-run and short-run. The estimated results are robust compared with alternative estimators such as dynamic ordinary least squares (DOLS), fully modified least squares (FMOLS), and canonical cointegrating regression (CCR). This research contributes to the existing literature by shedding light on the potential of agricultural added value to reduce emissions in Vietnam and provides policy recommendations in areas of low-carbon economy, promoting renewable energy, and sustainable agriculture that can reduce CO₂ emissions in Vietnam.

Does foreign direct investment asymmetrically influence carbon emissions in sub-Saharan Africa? Evidence from nonlinear panel ARDL approach

In recent decades, the relationship between foreign direct investment (FDI) and carbon emissions has garnered the extensive attention by researchers and governments across the globe. Also, for most part, empirical studies on this nexus have assumed a symmetric relationship through the imposition of linear specifications. However, such relationships do not account for asymmetries in the impact of FDI on carbon emissions. In the case of sub-Saharan Africa, such relationships are crucial and need more careful analysis given the important role FDI plays in the development of the sub-region. Thus, this paper examines the asymmetric effect of FDI on carbon emissions in 41 selected sub-Saharan African countries spanning from 1996 to 2018. In order to decompose FDI into positive and negative partial sum and examine possible asymmetric effects of the variables on carbon emissions, we used the panel nonlinear autoregressive distributed lag (NARDL) approach. This method accounts for cross-sectional variances. Our results show that in the long run, a positive shock in FDI increases carbon emissions while a negative shock lowers them. Our results also show that carbon emissions respond asymmetrically to changes in FDI. It is recommended that comprehensive investment policies aimed at encouraging clean technology and environmentally friendly investments be implemented to ensure environmental sustainability.

The nexus between remittances, natural resources, technological innovation, economic growth, and environmental sustainability in Pakistan

Globally, the issues about sustainable development are on the increase. Moreover, these issues are rising every day in Pakistan, as remittances are increasing, technology innovation is ambiguous, natural resources are degraded, and economic expansion might pose serious challenges to the environment. Thus, this research looks at how remittances, natural resources, technological innovation, and economic growth affect carbon dioxide (CO₂₎ emissions in Pakistan by controlling energy consumption and urbanization from 1990 to 2019. The Bayer and Hanck test of combined cointegration discloses a cointegration between remittances, natural resources, technological innovations, economic growth, and CO₂ emissions. Moreover, the autoregressive distributive lag model (ARDL) proposes a significant positive association between remittances and CO₂ emissions in the long run, indicating that the increase in remittances distresses the environmental performance of Pakistan. Our study confirms that natural resources decrease CO₂ emissions while technological advancement, economic progress, energy use, and urbanization increase CO₂ emissions. In addition, the results of robustness checks by employing fully modified ordinary least squares and dynamic ordinary least squares are parallel to the conclusions of ARDL estimations. Furthermore, the frequency causality test results show that remittances, natural resources, technological innovation, economic growth, energy use, and urbanization cause CO₂ emissions at different frequencies. Therefore, to achieve the sustainable development goals, appropriate policy repercussions can be developed toward advanced and environmentally sustainable sources of energy.

A path towards carbon mitigation amidst economic policy uncertainty in BRICS: an advanced panel analysis

Continuing economic progress with less environmental damage and achieving a sustainable environment require switching from fossil fuels to green energy. However, alleviating environmental damage of growth has become a major challenge for BRICS where economic progress amidst rising urbanization pollutes the environment. In this context, the fight against climate change and actions towards environmental sustainability are greatly affected by rising economic policy uncertainty. Hence, this study assesses the role of green energy, urbanization, and economic growth in CO2 emissions in the presence of economic policy uncertainty in BRICS (excluding South Africa) from 1997 to 2020. The study used the cross-sectionally augmented auto-regressive distributive lag technique for revealing the short- and long-run effects of the analyzed variables on environmental quality. The empirical evidence suggested that the environmental Kuznets curve exists according to the recent framework of Narayan and Narayan Energy Policy 38:661-666, (2010) because even though economic growth increases CO2 emissions, its long-run effect is less than the short-run effect. Economic policy uncertainty boosts CO2 not only in the short-run but also in the long-run, evidencing that a sustainable environment requires decreasing the levels of policy uncertainty. For BRICS, switching towards green energy is a vital option to decrease environmental deterioration owing to the negative connection between green energy and CO2. The findings indicated that rapid urbanization is among the causes of high CO2. Furthermore, economic policy uncertainty influences both green energy and economic growth levels. Finally, policies are recommended to mitigate environmental deterioration.

Linking shadow economy and CO2 emissions in Nigeria: Exploring the role of financial development and stock market performance. Fresh insight from the novel dynamic ARDL simulation and spectral causality approach

First and foremost, the present study seeks to traverse the informal sector characterized by a shadow economy in the presence of financial development, economic growth, and stock market performance on environmental pollution in Nigeria from 1981 to 2019. The dynamic autoregressive distributed lag (DARDL) approach was used to measure the short- and long-run elasticities, while spectral causality is applied to categorize the causal directions. Findings from the study revealed that the structural break unit root test revealed that all variables are stationary at first difference. The ARDL bound test confirmed the existence of long-run association among the used variables. The ARDL long-run results reveal that economic growth, financial development, and stock market performance are significantly responsible for carbon emission in Nigeria, while the shadow economy significantly improves environmental quality in Nigeria. Findings from the spectral causality results show a unidirectional causal relationship between financial development, economic growth, trade, stock market performance, and shadow economy to carbon emission in Nigeria. The empirical findings of this study provide some perceptive policy recommendations to overcome the adverse effect of carbon emissions in the environment.

Quantile relationship between globalization, financial development, economic growth, and carbon emissions: evidence from Vietnam

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.

Environmental sustainability and public-private partnerships investment in energy in Bangladesh

The current paper examines the effect of public-private partnerships investment in energy (PPIE) on CO₂ emissions while taking economic growth (GDP), foreign direct investment (FDI), and trade openness (TOP) into consideration for Bangladesh from 1997 to 2019. This paper utilizes Bayer and Hanck cointegration approach, fully modified ordinary least squares, dynamic ordinary least squares, canonical regression, and frequency domain causality technique. The outcome of this paper reveals that (i) the cointegrating association among PPIE, GDP, FDI, TOP, and CO₂ emissions is verified; (ii) PPIE, GDP, and TOP affect environmental sustainability negatively; (iii) in the long term, PPIE, FDI, and TOP Granger-cause CO₂ emissions in Bangladesh. This research suggests technical development for a greener production procedure and public-private partnership funding in green energy. Therefore, as a policy endorsement, this study proposes to invest in the latest technological advancements to manufacture environmentally sustainable goods via public-private partnerships.

Foreign Direct Investment, Environmental Pollution and Economic Growth—An Insight from Non-Linear ARDL Co-Integration Approach

The paper examines the impact of foreign direct investment and environmental pollution on economic growth in an emerging economy. We used annual data covering the period of 1986–2020 and the non-linear autoregressive distributed lag (NARDL) to analyze the positive and negative co-integrated variables, and our findings support the asymmetric relationship between foreign direct investment, environmental pollution and economic growth in both the short and long run, as well as a long-run relationship between environmental pollution and economic growth. A one-percent increase in environmental pollution leads to a positive change in economic performance by 0.662 percent. Adversely, a one-percent decrease in environmental pollution leads to a negative change in economic performance by 0.212 percent. Vietnam is an emerging market, and capital needs for economic activities are essential. However, the research results show that a disproportionate impact of foreign direct investment on economic growth is recorded in the long run, and a disproportionate impact of environmental pollution on the economy occurs in both the short and long term. Therefore, the government needs to have policies to attract foreign investment to develop a green and sustainable economy.

The asymmetric effect of renewable energy and trade on consumption-based CO2 emissions: The case of Italy

Although numerous studies in the literature have been conducted to model CO₂ emissions, there is a lack of empirical knowledge of consumption-based CO₂ emissions, which are adjusted for international trade, specifically. Therefore, the present study aims to close this gap in the literature in the case of Italy, while capturing the asymmetric effect of trade, renewable energy, and economic growth on consumption-based CO₂ emissions. The present study uses the Gregory-Hansen test for cointegration with regime shifts, Markov switching regression, nonlinear autoregressive distributed lag (NARDL), and frequency domain causality test. The study's outcomes reveal that (1) the asymmetric effect of import on consumption-based CO₂ emissions is positive, implying that rising import is associated with declining consumption-based environmental quality; (2) export, renewable consumption, and economic growth reduce consumption-based CO₂ emissions in Italy. Moreover, these outcomes are supported by the outcomes of the frequency domain causality test. These innovative insights may prompt policy-makers to implement eco-friendly methods, such as renewable energy distribution and environmental innovation, to achieve a greener future. Integr Environ Assess Manag 2022;18:784-795. © 2021 SETAC.

Environmental pollution and agricultural productivity in Pakistan: new insights from ARDL and wavelet coherence approaches

The most serious challenge to the global facade is figuring out how to mitigate pollution levels without compromising agricultural productivity. The spillover effect of environmental change is predicted to be very high, although it will differ by region and crop. Considering this view, this study tries to address this issue by adopting comprehensive methodologies to assess the influence of carbon dioxide (CO₂) emissions, agricultural labor, land, feeds, and fertilizers on agricultural productivity in Pakistan from 1961 to 2018. The autoregressive distributive lag (ARDL) and wavelet transform coherence (WTC) approaches are applied to estimate the long-run and short-run elasticity estimates. The empirical findings discover that CO₂ emissions, agricultural land, labor, feed, and fertilizers exert high pressure on agricultural productivity which is backed up by the WTC findings. Furthermore, the gradual shift causality test results reveal the presence of a unidirectional causality relationship between all regressors and agriculture productivity, demonstrating that all the factors significantly influence agriculture productivity. Moreover, these findings are robust to different robustness tests that we perform to test the reliability/accuracy of our core results. From policy perspectives, regulations must be developed to explore a practicable expansion strategy that includes the use of efficient fertilizers and feed at optimal levels, as well as environmental protection through public-private investment in the agricultural sector.

Dynamic impacts of energy use, agricultural land expansion, and deforestation on CO2 emissions in Malaysia

This study empirically investigates the nexus among energy use, agricultural land expansion, deforestation, and carbon dioxide (CO₂) emissions in Malaysia. Time series data from 1990 to 2019 were utilized using the bounds testing (ARDL) approach followed by the Dynamic Ordinary Least Squares (DOLS) method. The DOLS estimate findings show that the energy usage coefficient is positive and significant with CO₂ emissions, indicating a 1% increase in energy consumption is related to a 0.91% rise in CO₂ emissions. In addition, the coefficient of agricultural land is positive, which indicates that agricultural land expansion by 1% is associated with an increase in CO₂ emissions by 0.84% in the long run. Furthermore, the forested area coefficient is negative, which means that decreasing 1% of the wooded area (i.e., deforestation) has a long-term effect of 5.41% increased CO₂ emissions. Moreover, the pairwise Granger causality test results show bidirectional causality between deforestation and energy use; and unidirectional causality from energy use to CO₂ emissions, agricultural land expansion to CO₂ emissions, deforestation to CO₂ emissions, agricultural land expansion to energy use, and deforestation to agricultural land expansion in Malaysia. The empirical findings reveal that increased energy use, agricultural land expansion, and deforestation have a negative impact on environmental quality in Malaysia. Thus, the effective implementation of policy measures to promote renewable energy, climate-smart agriculture, and sustainable management of forest ecosystems could be useful for reducing environmental degradation in Malaysia.

Mitigating human-induced emissions in Argentina: role of renewables, income, globalization, and financial development

Achieving environmental sustainability has become a global initiative while addressing climate change and its effects. However, the role of energy production and consumption in economic development remains critical amidst environmental pollution. Thus, the need for innovation and clean energy alternatives is critical while pursuing sustainable development. This country-specific study focuses on Argentina, where economic growth trajectory is embedded with high CO₂ emissions. This study assesses the long-term and causal impact of financial development and renewables on environmental pollution while accounting for the role of economic development and globalization using yearly data spanning 1980 to 2017. A battery of econometric methods is applied to underscore the interaction between the parameters of interest. The findings of Maki and ARDL tests of cointegration alongside Kripfganz and Schneider critical approximation p-values affirm long-run equilibrium interaction between variables. The outcomes of autoregressive distributed lag, fully modified, and dynamic ordinary least squares demonstrate that while economic expansion dampens environmental quality-globalization and renewables improve the environment. This finding suggests pollution-driven economic growth trajectory in Argentina with high dependence on fossil fuels. Besides, the gradual shift causality test finds evidence of one-way causality from renewable energy consumption, economic growth, and globalization to CO₂ emissions. Argentina's pathway in achieving sustainable development requires gradual and inclusive economic shift towards green growth.

Financial development, human capital development and climate change in East and Southern Africa

Africa is currently experiencing both financial and human development challenges. While several continents have advocated for financial development in order to acquire environmentally friendly machinery that produces less emissions and ensures long-term sustainability, Africa is still lagging behind the rest of the world. Similarly, Africa's human development has remained stagnant, posing a serious threat to climate change if not addressed. Building on the underpinnings of the environmental Kuznets curve (EKC) hypothesis on the nexus between economic growth and environmental pollution, this study contributes to empirical research seeking to promote environmental sustainability as follows. First, it investigates the link between financial development, human capital development and climate change in East and Southern Africa. Second, six advanced panel techniques are used, and they include (1) cross-sectional dependency (CD) tests; (2) combined panel unit root tests; (3) combined panel cointegration tests; (4) panel VAR/VEC Granger causality tests; and (5) combined variance decomposition analysis based on Cholesky and generalised weights. Our finding shows that financial and human capital developments are important in reducing CO₂ emissions and promoting environmental sustainability in East and Southern Africa.

Role of political risk to achieve carbon neutrality: Evidence from Brazil

The current research assesses the impact of political risk on carbon dioxide (CO₂) emissions in Brazil while controlling the role of financial development, GDP growth, trade openness, and technological innovation. In doing so, the quarterly dataset from 1990 to 2018 is utilized with Bayer and Hanck cointegration, dynamic ordinary least square (DOLS) and canonical correlation regression (CCR), and frequency-domain causality tests. The cointegration test revealed a long-run association amongst the variables of interest. Furthermore, the outcomes from the DOLS and CCR revealed that increasing financial development, technological innovation, trade openness, and real growth increase CO₂ emissions while a better political environment reduces environmental pollution.

The environmental sustainability effects of financial development and urbanization in Latin American countries

The present study assesses the impact of urbanization, economic growth, energy consumption, and financial development on CO₂ emissions in Latin American countries using a dataset spanning between 1980 and 2017. The current paper employs utilized panel econometric techniques such as CIDF, panel unit test, the Westerlund panel cointegration, fully modified ordinary least squares (FMOLS), dynamic ordinary least squares (DOLS), and Dumitrescu Hurlin panel causality test to assess these associations. The outcomes from the FMOLS and DOLS estimation reveal that (i) economic growth impacts CO₂ emissions positively, (ii) energy consumption exerts a positive impact on CO₂ emissions, and (iii) urbanization impacts CO₂ emissions positively. Furthermore, the outcomes of the causality test reveal that energy consumption and economic growth can predict CO₂ emissions in Latin countries. The findings highlight the importance of policymakers actively coordinating strategies to address Latin America's severe environmental degradation.

Economic performance of Indonesia amidst CO2 emissions and agriculture: a time series analysis

To minimize the awful situation confronting the entire globe, the global warming danger has raised the intensity of consciousness from all areas of life. Therefore, the research assesses the impact of CO₂ emissions and energy use on economic performance and considers trade openness, urbanization, and agriculture in Indonesia utilizing data covering the period from 1965 to 2019. The current research employed the dynamic ordinary least square (DOLS) and autoregressive distributed lag (ARDL) tests to capture the long-run association between these economic indicators. Furthermore, the gradual shift and wavelet coherence tests are utilized to capture the direction of causality. The ARDL bound test discloses a long-run interconnection among the variables of interest. The outcomes of the ARDL and DOLS depict that CO₂ emissions, agriculture, energy use, and urbanization trigger economic growth. Moreover, the wavelet coherence test findings revealed a positive correlation between economic growth and urbanization, CO₂ emissions, agriculture, and energy consumption. Furthermore, there is evidence of a weak and positive correlation between economic growth and trade openness. The gradual shift causality test outcomes disclosed that economic growth can predict urbanization and energy consumption, while agriculture can predict economic growth. These outcomes have far-reaching significance for economic growth and the selected variables in Indonesia.

How do trade and economic growth impact environmental degradation? New evidence and policy implications from the ARDL approach

Due to various environmental degradation and natural resource depletion around the world, researchers' and policymakers' attention has turned to what causes environmental degradation. The pursuit of a healthy environment has become a global challenge, a problem that affects more than one nation. Climate change is causing severe weather conditions in every world, disrupting economies and affecting the lives of many people. Hence, the study analyzes how trade and economic growth impact environmental degradation in Belgium, the USA, and Canada using panel data from 1995 to 2016. The study utilized the autoregressive distributed lag approach to provide new evidence and policy implications. The outcome confirmed the presence of cointegration among the selected variables. However, it was observed that economic growth decreases environmental degradation in the long run while trade openness shows a positively insignificant relationship with carbon emission. Nevertheless, a positive short-run relationship was observed between economic growth and carbon emissions whereas a negatively insignificant relationship was observed for trade and carbon emission. The findings prompted policy implications that more trading could be done between the countries. When countries trade more, their economies will flourish, ensuring global prosperity and minimizing environmental degradation.

Can CO2 emissions and energy consumption determine the economic performance of South Korea? A time series analysis

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.

Determinants of consumption-based carbon emissions in Chile: an application of non-linear ARDL

In recent years, a growing number of scholars have employed various proxies of environmental degradation to understand the reasons behind rising environmental degradation. However, very few studies have considered consumption-based carbon emissions, even though a clear understanding of the impact of consumption patterns is essential for redirecting the pattern to more sustainable consumption. Thus, this study takes a step forward by using consumption-based carbon emissions (CCO2) as a proxy of environmental degradation using the novel non-linear ARDL technique for Chilefrom 1990 to 2018. To the best understanding of the investigators, no prior studies have investigated the drivers of consumption-based carbon emissions utilizing non-linear ARDL. The study employed ADF and KSS (non-linear) tests to check the data series' stationary level. Additionally, the symmetric and asymmetric ARDL approaches are utilized to explore cointegration and long-run linkages. According to the results, there is no symmetric cointegration among the variables; however, the empirical estimates reveal a long-run asymmetric connection between the indicators and CCO2 emissions. The novel results from the asymmetric ARDL indicate that negative and positive changes in economic growth deteriorate the quality of the environment. Interestingly, a reduction in economic growth makes a more dominant contribution to environmental degradation. Moreover, positive changes in renewable energy usage improve the quality of Chile's environment, inferring that the country can achieve a reduction in environmental degradation by boosting renewable energy consumption. Surprisingly, the study found that technological innovation is ineffective in reducing consumption-based carbon emissions, which implies that Chile's technological innovation is not directed towards manufacturing green technology. Finally, the policy implications are discussed with respect to reducing consumption-based carbon emissions.

Do CO2 emissions, energy consumption and globalization promote economic growth? Empirical evidence from Japan

In the empirical literature, there is no agreement on the linkage between environmental deterioration and economic growth. Thus, this paper aims to explore the long-run and causal effects of CO₂ emissions, globalization energy usage, trade openness and urbanization on economic growth in Japan by employing new econometric techniques. The paper uses a dataset spanning from 1970 to 2015 and employs recent econometric techniques. To the best of the investigator's understanding, no prior studies have examined this linkage utilizing the wavelet coherence technique for Japan. The novelty of the wavelet is that it can capture the causality and long-run linkage between economic variables at different frequencies and periods. Thus, the study's aim is to address the following questions: (i) Is there a long-run and causal linkage between economic growth, energy usage, urbanization, CO₂ emissions, trade openness and globalization? (ii) What is the interaction between economic growth and the regressors at various frequencies and periods? The paper utilizes the ARDL, DOLS and FMOLS to catch the long-run effects, whereas the wavelet coherence technique is employed to capture the causal effects among the indicators. The outcomes of the ARDL show that urbanization, CO₂ emissions, globalization and energy usage trigger economic growth, while no significant linkage is found between trade openness and economic growth. The wavelet coherence approach reveals (i) positive co-movements between economic growth and the regressors and (ii) a one-way causality from CO₂ emissions and energy usage to economic growth.

Modeling CO2 emissions in Malaysia: an application of Maki cointegration and wavelet coherence tests

One of humanity's most significant problems in the twenty-first century revolves around how to balance the mitigation of environmental pollution while achieving sustainable economic development. Despite increased awareness and dedication to climate change, the planet is still seeing a drastic decrease in the volume of pollutant emissions. This study explores the long-run and causal impact of economic growth, financial development, urbanization, and gross capital formation on Malaysia's CO₂ emissions based on the STIRPAT framework. The current paper employs recently developed econometric techniques such as Maki co-integration, auto-regressive distribution lag (ARDL), fully modified OLS (FMOLS), dynamic ordinary least square (DOLS), and wavelet coherence and gradual shift causality tests to investigate these interconnections. The advantage of the gradual shift causality test is that it can capture the causality in the presence of a structural break(s). The findings from the Maki co-integration and ARDL bounds tests reveal evidence of cointegration among the variables. The ARDL test reveals that economic growth, gross capital formation, and urbanization exert a positive impact on CO₂ emissions. Furthermore, the wavelet coherence test reveals that there is a significant dependency between CO₂ emissions and economic growth, gross capital formation, and urbanization. The Toda Yamamoto and Gradual shift causality tests reveal that there is a (a) unidirectional causality from urbanization to CO₂ emissions, (b) unidirectional causality from economic growth to CO₂ emissions, and (c) unidirectional causality from gross capital formation to CO₂ emissions.

The Imperativeness of Environmental Quality in China Amidst Renewable Energy Consumption and Trade Openness

It is widely accepted that CO2 emissions are the primary cause of climate change and environmental destruction. China, the world’s biggest carbon emitter, is the subject of this research. Utilizing the wavelet tools (wavelet correlation, wavelet coherence, multiple wavelet coherence, and partial wavelet coherence), the present study intends to capture the time-frequency dependence between CO2 emissions and renewable energy, economic growth, trade openness, and energy usage in China between 1965 and 2019. The advantage of the wavelet tools is that they can differentiate between short, medium, and long-run dynamics over the period of study. Furthermore, the study utilized the gradual shift causality test to capture the causal interconnection between CO2 emissions and the regressors. The findings from Bayer and Hanck showed a long-run relationship among the variables of interest. Furthermore, the findings from the wavelet coherence test revealed a positive relationship between CO2 emissions and economic growth and energy usage at all frequencies. Although there is a weak negative relationship between renewable energy and CO2 emissions in the short run, there is no significant co-movement between CO2 emissions and trade openness. The outcomes of the partial and multiple wavelet coherence also give credence to the outcomes of the wavelet coherence test. Lastly, the gradual shift causality test revealed a one-way causality from energy usage and economic growth to CO2 emissions. Based on the findings, suitable policy suggestions were proposed.

Investigating the Linkage between Economic Growth and Environmental Sustainability in India: Do Agriculture and Trade Openness Matter?

This paper assesses the linkage between CO2 emissions and economic growth while taking into account the role of energy consumption, agriculture, and trade openness in India. Using data covering the period between 1965 and 2019, the Bayer and Hanck cointegration and Gradual shift causality tests are applied to assess these economic indicators relationships’. Furthermore, we employed the wavelet coherence test. The advantage of the wavelet coherence test is that it differentiates between short-, medium-, and long-run dynamics over the entire sampling period. To the best of the authors’ understanding, the present paper is the first to apply wavelet analysis to investigate this relationship by incorporating agriculture as a determinant of environmental degradation. The empirical outcomes show that all variables appear to be highly correlated with CO2 emissions with the exemption of trade openness. This is further affirmed by the Gradual shift causality test, which shows that agriculture and energy consumption are crucial determinants of CO2 emissions in India. Accordingly, adequate policy measures are proposed based on these findings.

Do Public–Private Partnership Investment in Energy and Technological Innovation Matter for Environmental Sustainability in the East Asia and Pacific Region? An Application of a Frequency Domain Causality Test

Environmental sustainability is an important issue for current scholars and policymakers in the East Asian and Pacific region. The causal and long-run effects of technological innovation, public–private partnership investment in energy, and renewable energy consumption on environmental sustainability in the East Asian and Pacific regions have not been comprehensively explored while taking into account the role of economic growth using quarterly data for the period 1992–2015. Therefore, the present study aims to close this literature gap using econometric approaches, namely Bayer–Hanck cointegration, autoregressive distributed lag (ARDL), dynamic ordinary least square (DOLS), and fully modified ordinary least square (FMOLS) tests. Furthermore, the study utilizes the frequency domain causality test to capture the causal impact of public–private partnership investment in energy, renewable energy consumption, technological innovation, and economic growth on CO2 emissions. The advantage of the frequency domain causality test is that it can capture the causality between short-term, medium-term, and long-term variables. The outcomes of the ARDL, FMOLS and DOLS show that renewable energy consumption and technological innovation mitigate CO2 emissions, while public–private partnership investment in energy and economic growth increase CO2 emissions. Moreover, the frequency causality test outcomes reveal that technological innovation, public–private partnership investment in energy, and renewable energy consumption cause CO2 emissions, particularly in the long-term. Thus, as a policy recommendation, the present study recommends promoting renewable energy consumption by focusing more on technological innovation in the East Asia and Pacific regions.

Investigating the Causal Relationships among Carbon Emissions, Economic Growth, and Life Expectancy in Turkey: Evidence from Time and Frequency Domain Causality Techniques

It is not a gainsaying that challenges to both healthy living and the environment are the result of deteriorating environmental quality with the attendant effect on environmental sustainability. To provide a solution to the issue, our study uses long time-series data from 1960 to 2018, and employs an overlapping generational model, the Bayer–Hanck cointegration test, wavelet coherence, Fourier Toda–Yamamoto, and Breitung–Candelon frequency-domain spectral causality tests to investigate the causal relationships among carbon emissions (CO2), economic growth (GDP), and life expectancy (LE) in Turkey. Different from the literature, we find a positive co-movement between life expectancy and CO2 and a positive correlation between LE and GDP at different scales; CO2 has a causal relationship with LE and a bidirectional causal relationship between LE and GDP, as well as short, medium, and long-run causal relationships with LE; GDP has medium and long-run causal relationships with LE, and LE has short, medium, and long-run causal relationships with GDP. Our findings guide policymakers on their policy decision-making that will address the energy consumption, environmental degradation, human health, environmental hazards, and allocation to science and technology in Turkey with the aim of ensuring overall sustainable development.