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This research paper attempts to investigate both the long-run and causality relationship among electric power consumption (EPC), technological transfer, financial development (FD), and environmental quality for the Saudi Arabia (KSA) economy from 1980 to 2019. In doing so, we propose a carbon emission function tested by incorporating multi-steps techniques such as autoregressive distributed lag (ARDL) has been exploited to determine the existence of cointegration or no; while vector error correction model (VECM) has been applied to decide the direction of causality. In this paper we have proposed two proxies of technological transfer, namely imported technology (MT) and Technical cooperation grants (TCG). The results indicate the existence of cointegration between the concerned series. Besides, the existence of a feed-back effect among variables (except TCG) in the long-run. However, in the short run feed-back effect exists among EPC and EnvQ; MT and EnvQ; EPC and MT. Thus, the paper provides original visions for policy makers to encourage the technological transfer by financing and supporting the electric energy sector which constitutes the main locomotive to improve the environment quality for the KSA.JEL classification : C32, C52, O11, Q43

One of the most critical problems of today is the environmental policies with the focus on economy. Despite the many efforts of global organizations, environmental pollution is the subject of human beings. For this, the most polluting countries attract the attention of researchers. Many studies produce economy-centered environmental policies for the USA. However, the asymmetric effect of natural resources on environmental pollution has been neglected in the literature. In this paper, the effects of economic growth, renewable energy, biocapacity, and natural resources on the ecological footprint are addressed within the framework of the Environmental Kuznets Curve hypothesis over the period 1980-2017. Empirical findings confirm that economic growth and biocapacity increase environmental degradation, while renewable energy consumption helps reduce environmental damage. More specifically, when the results are analyzed in terms of natural resources, positive shocks in natural resources contribute to reducing environmental damage, while negative shocks in it negatively affect the environmental quality. The paper presents important policy implications for economy-centered environmental issues.

Although there have been many studies, focusing on basic determinants of carbon dioxide emissions (CO2), the effect of higher education, which has the potential to be an important determinant of CO2, has been neglected. The paper aims to display the potential mechanisms between higher education and CO2 and expand the environmental economics literature. In the paper, the trade-off between higher education and CO2 is tested by autoregressive distributed lag (ARDL) during the period 1983-2017 in Turkey. Results denote that cointegration exists and an increase in higher education negatively affects CO2. We also find that economic growth and energy consumption positively affect CO2 both in the long run and short run. Vector error correction model (VECM) reveals that higher education, economic growth, energy consumption, trade openness, and exchange rates are the causes of CO2 in the long run. Also, energy consumption and economic growth are the causes of CO2 in the short run. Therefore, higher education can be used to overcome environmental problems.

The nexus of remittances and CO2 emission is very important and gathers a significant place in empirical research. This paper tries to find out the asymmetric relationship between carbon emissions, remittances, and financial development in India for the period 1980-2014. Based on the theoretical linkages, we develop a nonlinear ARDL model with the use of time series data in this study. The results of the NARDL bound test suggest that there is long-run cointegration among the variables. The findings show that positive shock in remittances causes an increase in CO2 emissions, where negative shock reduces it. The coefficient for financial development is positive but becomes statistically insignificant. Empirical results also support the existence of asymmetric long-run relationship among the variables. Based on the findings, the paper recommends the proper channelization of remittances and financial development towards environment-friendly energy sources and projects without compromising economic growth.

This paper investigates the CO2 emissions–economic growth relationship in Kazakhstan for the period 1992–2013. Johansen, ARDLBT, DOLS, FMOLS, and CCR cointegration methods are used for robustness purpose. We start with the cubic functional form to rule out any misleading results that can be caused by misspecification. Although the estimation results suggest “U”-shaped relationship, the turning point of income is out of the period. It means that the impact of economic growth on CO2 is monotonically increasing in the long run indicating the Environmental Kuznets Curve (EKC) hypothesis does not hold for Kazakhstan. Moreover, we calculate that the income elasticity of CO2 is about unity. The paper concludes that the Kazakhstani policymakers should focus on less energy-intensive sectors as well as using more renewable energy in order to avoid higher pollution effects of economic growth. They may also set new policy regulations for CO2 reduction.

The paper revisits the dynamic effect of trade openness on environmental quality in South Africa by employing a fresh proxy of trade openness suggested by Squalli and Wilson (The World Economy 34:1745–1770, 2011) over the period 1960–2016. Contrary to the previous literature, the new proxy is constructed to take into consideration both South Africa’s trade share of its GDP and its relative size of trade in relation to the world trade in a specified period of time. Adopting this novel approach to capture openness, the study applies the autoregressive distributed lag (ARDL) bounds test for cointegration approach to investigate the long-run association between trade openness and environmental quality. Our findings show that the results of the long run are materially different from those of the short run. While trade openness has a significantly beneficial impact on CO2 emissions in the short run, it has a measurably detrimental consequence on it in the long run. These findings are new to the literature and contrast with the previous studies. While confirming the existence of an inverted U-shaped curve that validates the existence of environmental Kuznets curve (EKC) hypothesis for South Africa, our results are further supported by the non-linear ARDL model, which reveals evidence of asymmetric pass-through effects of changes in trade openness on CO2 emissions. This paper suggests that South Africa’s policymakers must continue to improve trade policy reform with complementary policies to create a less carbon-intensive environment and promote lasting value for reductions of greenhouse gas (GHG) emissions and constantly support the establishment of greener technologies that ultimately lower CO2 emissions.

For the last three decades, both China and India are considered as the largest emerging market economies in the world. Both of these economies play an essential role in the global economy in terms of economic output and CO2 emissions. Hence, these countries are expected to play an important role in setting up environmental and sustainable development policies. Therefore, our paper aims to examine the role of natural gas and renewable energy consumptions on CO2 emissions and economic growth during 1965-2016 within a multivariate framework. The autoregressive distributed lag bounds testing approach to cointegration and vector error correction model (VECM) is employed to explore the long-run and causal nexus among the natural gas consumption, renewable energy consumption, coal and petroleum consumption, CO2 emissions, and economic growth, respectively. The empirical results show existence of long-run equilibrium association among the variables. The Granger causality results indicate that the short-run bidirectional causality between renewable energy consumption and economic growth in India, while no causality is found between these two variables in China. However, natural gas consumption causes economic growth in China whereas no causality is confirmed in India in the short-run. The findings further suggest that there is long-run bidirectional causality among the considered variables in both countries. Our paper addresses several important policy implications.

WOS: 000445273500091, PubMed: 30141168, This paper explores the direct impact of new technology on the energy intensity in China. The autoregressive distributed lag (ARDL) bounds test approach to cointegration is utilised over the extended period of 1985-2013. The variables found cointegrated and confirm the long-run association among all the underlying vectors. Furthermore, the results of long- and short-run analysis reveal that new technology spurs energy intensity in China. A 1% increase in technological innovation boosts energy intensity by 0.4% and 0.03% in the long and short run, respectively. The findings suggest that the establishment of smart grids and solar energy parks followed by the reforms in energy sector is yet to achieve plausible efficiency in China. The existing investment and innovation policy reforms are insufficient to assist the energy sector to cope up with the country's exceptional economic growth trend. Unlike other studies, this paper accommodates structural break in the series. During sensitivity analysis, the model is found stable. Hence, the findings possess important policy implications for China and open up new discussion in the field.

This paper provides the evidence on the short- and the long-run effects of the export product concentration on the level of CO2 emissions in 19 developed (high-income) economies, spanning the period 1962-2010. To this end, the paper makes use of the nonlinear panel unit root and cointegration tests with multiple endogenous structural breaks. It also considers the mean group estimations, the autoregressive distributed lag model, and the panel quantile regression estimations. The findings illustrate that the environmental Kuznets curve (EKC) hypothesis is valid in the panel dataset of 19 developed economies. In addition, it documents that a higher level of the product concentration of exports leads to lower CO2 emissions. The results from the panel quantile regressions also indicate that the effect of the export product concentration upon the per capita CO2 emissions is relatively high at the higher quantiles.

This paper investigates the relationship between CO2 emissions, energy consumption, economic growth, and foreign direct investment for a sample of Asia-Pacific Economic Cooperation Countries (APEC) countries from 1981:Q1 to 2021:Q1 employing panel data methodology. We identify cross-sectional dependence and hence utilize the cross-sectional augmented Dickey-Fuller panel unit root test for appropriate estimation. The cointegration test developed by Westerlund (2008) reveals a long-run equilibrium between CO2 emissions, energy consumption, economic growth, and foreign direct investment. Long-run parameter estimates based on Common Correlated Effect Mean Group indicate that an increase in FDI inflows has a negative impact on air quality, supporting the pollution haven hypothesis. The cointegration test results also show that the impact of Gross Domestic Product (GDP) on CO2 emissions varies by country in the estimation sample. In contrast to the mixed evidence on the effects of other variables, the increase in energy consumption is positively and significantly affecting CO2 emissions in all APEC countries. Emirmahmutoglu and Kose Econ Model 28:870-876, (2011)'s panel causality test results show a bidirectional relationship between FDI and CO2 emissions in Japan. Furthermore, there is a bidirectional causal relationship between GDP and energy consumption in Australia, China, Japan, and Singapore. Overall, empirical evidence suggests that APEC countries should adhere to strict regulations and invest in environmental-friendly clean technologies to attract foreign direct investment.

The economic structure of countries can influence economic growth, energy demand, and environmental footprints. However, the literature on economic complexity and ecological footprint (EFP) nexus is scarce. Besides, democracy is an important factor that may affect environmental policies and environmental sustainability. Hence, this paper investigates the effect of democracy, economic complexity, and renewable energy technology budgets on the EFP in G7 countries controlling income and financial development from 1985 to 2017. The findings from Westerlund (J Appl Econ 23:193-233, 2008) and other cointegration methods depict cointegration among variables. The long-run estimates from the continuously updated fully modified method unfold that economic complexity contributes to reducing the EFP. However, greater democratic accountability boosts the EFP figures rather than reducing them. On the flipside, renewable energy technology budgets and financial development are evidenced to mitigate EFP. Moreover, the study unveils a U-shaped linkage between economic growth and EFP, which indicates that an increase in income level will boost EFP. Further, the study found causality from economic complexity, democracy, and renewable energy budgets to EFP. Based on these findings, it is pertinent for the G7 countries to increase the manufacturing of sophisticated and complex products. In addition, enhancing renewable energy technology budgets is essential to ensure environmental well-being.

This paper explored the asymmetrical relationships between green and sustainable technology research and environmental sustainability among the BRICS states from 1990 to 2018. The data was analyzed by second- and third-generation economic techniques such as slope heterogeneity and cross-section independence test, unit root test, structural break unit root test, panel cointegration with structural breaks cointegration tests, cross-section autoregressive distributed lags technique, augmented mean group, and Dumitrescu-Hurlin panel causality test. First, the results validated a long-run cointegration among variables. Second, the results showed that renewable energy consumption and positive shocks to green and sustainable technology research are proper to mitigate carbon dioxide emissions (short- and long-run). Third, gross domestic product, foreign direct investment, exports, and negative shocks to green and sustainable technology research increase carbon dioxide emissions. Fourth, the nexus between green and sustainable technology research and carbon dioxide emissions was counter-cyclical during economic expansion and contraction periods. Fifth, the impact of positive shocks to green and sustainable technology research on carbon dioxide emissions was more than the impact of negative shocks to green and sustainable technology research on carbon dioxide emissions.

Many economies are seeking new ways to improve environmental quality through international collaboration in environmental-related technology development (ICERTD). Cost reduction, green market penetration, and green technology development are central to global partnerships for sustainable development, even though no empirical study explains the ICERTD-carbon dioxide (CO2) emissions nexus. The paper fills this knowledge gap in the environmental economics literature by examining the relationship between ICERTD and CO2 emissions in the U.S. from 1990Q1 to 2018Q4 using domestic environmental innovation, trade openness, renewable energy consumption, and gross domestic product per capita as control variables. Fully modified ordinary least squares, dynamic ordinary least squares, and correlated component regression methods were employed for testing the long-run nexus among the variables. The present study revealed that (i) a long-run cointegration existed among ICERTD, domestic environmental innovation, trade openness, renewable energy consumption, gross domestic product per capita, and CO2 emissions; (ii) ICERTD, domestic environmental innovation, and renewable energy consumption benefited the U.S. in lowering CO2 emissions in the long run; and (iii) trade openness and gross domestic product per capita were positively associated with CO2 emissions. This study recommends important policy recommendations for increasing ICERTD for decarbonization.

This paper examines the effect of climate change and financial development on agricultural production in ASEAN-4, namely Indonesia, Malaysia, the Philippines, and Thailand from 1990 to 2016. Further, we explore the role of renewable energy, institutional quality, and human capital on agricultural production. Since the shocks in one country affect another country, we use second-generation modeling techniques to find out the relationship among the variables. The Westerlund (2007) cointegration tests confirm long-run relationship among the variables. The results from cross-sectionally augmented autoregressive distributed lag (CS-ARDL) model reveal that climate change negatively affects agricultural production; on the other hand, renewable energy, human capital, and institutional quality affect positively agricultural production. Moreover, renewable energy utilization, human capital, and intuitional quality moderates the effect of carbon emission on agricultural production. In addition, a U-shaped relationship exists between financial development and agricultural production, suggesting that financial development improves agricultural production only after reaching a certain threshold. Hence, this study suggests that ASEAN-4 countries must adopt flexible financial and agricultural policies so that farmers would be benefitted and agricultural production can be increased.

In this paper, the behavior of precious metals and oil is examined using a fractionally integrated and cointegrated modeling approach. Using daily data from January 2015 to December 2020 and using both endogenous and exogenous structural breaks, we examine the behavior of the related series before and during the COVID-19 pandemic with the aim of investigating whether the degree of persistence has changed since the onset of COVID-19. We found that precious metals and oil exhibit long memory and are mean reverting regardless of the sample considered as the fractional parameter d 0.5. Both cointegration techniques alongside the parameter stability tests lend support to the existence of a persistence and stable long-run relationships among the series irrespective of the sample period considered. Attendant policy recommendations for investors and policymakers are recommended.

Unlike the previous study, this paper employs panel cointegration and Granger causation approaches to discuss the associations among carbon dioxide (CO2) emissions, GDP growth, clean energy generation, and industrial growth for the top ten industrial countries spanning the period 1980-2014. The primary empirical outcomes show a two-way long-run association between environmental indicator, GDP growth, and clean energy generation, while one short-run causation from clean energy generation to CO2 emissions and from industrial growth to clean energy generation. The computed coefficients elasticity's under FMOLS, DOLS, and CCR estimates revealed that the clean energy generation statistically contributes to declining emissions of CO2 in Australia, Austria, and Chile while statistically increase emissions of CO2 in Denmark and the Netherlands. Industrial growth statistically contributes to reducing emissions of CO2 in Denmark and Norway but increases emissions in Chile, France, and Sweden. For the global panel, industrial growth leads to mitigate the rate of emissions while clean energy generation raises CO2 emissions in the long period. Investing in clean energy is needed to stimulate the growth of the industrial sector and then reduce the rate of emissions.

This paper made the first attempt to summarize the rules from a regional perspective and use panel data to explore the carbon Kuznets curve (CKC) between e-commerce and carbon dioxide emissions. The impact of online shopping on carbon emission has mixed conclusions. No CKC tests set mainly focuses on the e-commerce sector, which can help this research determine the relationship between e-commerce and carbon emissions. From a macro point of view, we examine both developed and developing regions by testing the CKC hypothesis. We try to explain it by exploring the econometric relationship between e-commerce and CO2 emissions. At first, we attempt to accurately measure the CO2 emissions by carefully distinguishing the carbon emission increments caused by the primary energy resulting from the secondary energy. Then, we use panel data collected from different Chinese cities during 2001-2017. The analyzed variables are stationary at their first differences with the LLC test, IPS test, Fisher-ADF test, Fisher-PP test, CADF, and CIPS unit root tests. The analyzed variables are cointegrated by employing the Pedroni panel cointegration test, the Kao panel cointegration test, and the Westerlund panel cointegration test. Using the DOLS, we also find that increases in trade openness decrease carbon emissions while increases in foreign direct investment (FDI) and market size contribute to the level of emissions. The quadratic-shape CKC hypothesis is supported for China, Eastern China, and Western China, and it is an inverted "U" shape. The cubic-form CKC is supported for Central China, and it is an "N" shape. Our study provides important insights for enacting regional and country-level e-commerce regulations and reducing carbon dioxide emissions.

In this paper, we examine the impact of globalization on ecological footprint within the framework of the environmental convergence hypothesis for 130 countries over 1980-2016. To do so, we follow a two-stage empirical procedure. First, we test the overall convergence in ecological footprint across countries and identify possible convergence clubs using the nonlinear time-varying factor model developed by Phillips and Sul (2007). Then, we perform panel unit-root and panel cointegration tests used under the presence of cross-sectional dependence to analyze the impact of globalization and economic growth on the ecological footprint both for the full panel sample and convergence clubs. Finally, we estimate long-run coefficients using the Common Correlated Effects Mean Group (CCE-MG) and Augmented Mean Group (AMG) techniques. The club clustering algorithm identifies five convergence clubs, each converging to a different ecological footprint level. The results show cointegration between variables for the full panel sample and two of the five convergence clubs. Furthermore, there is no significant relationship between ecological footprint and globalization, whereas economic growth is significantly and positively related to the ecological footprint for full panel sample and one of the five convergence clubs. In other words, the impact of globalization and economic growth on ecological footprint differs across full panel sample and convergence clubs.

The foremost theme of the paper is to explore the asymmetric/symmetric impact of energy consumption on the carbon dioxide emission of G7 countries (Germany, Canada, USA, Italy, France, Italy, UK, and Japan). The nonlinear autoregressive distributed lag is used to measure asymmetric/symmetric cointegration by using annual data of G7 countries from 1965 to 2019. The augmented Dickey-Fuller and structural break unit root test is employed to measure the stationarity in variables while the Brock, Dechert, and Scheinkman test is used for measuring nonlinearity and the Wald test is used to figure out short- and long-run asymmetries/symmetries, respectively. The estimated findings of the nonlinear autoregressive distribution lag model show a significant effect of energy use on the ecological footprint. The asymmetric causality test provides evidence of unidirectional, bidirectional, and asymmetrical/symmetrical causality among the variables of G7 nations. The finding of the study suggested policy for the government of Canada and France to use coal instead of oil and gas while the USA, Germany, Italy, UK, and Japan are required to consume gas as compared to oil and coal. Similarly, the study also suggests using modern technology, renewable energy, and preventive measurement for ensuring environmental betterment.

This research paper examines the causal relationships among carbon dioxide emissions, economic growth, and renewable and non-renewable energy consumption, for a panel of 68 developing countries over the period 1990 - 2014. We use the multivariate panel cointegration framework and apply a battery of conventional (Pedroni 1999, 2004; and Kao 1999) as well as newly developed methodologies accounting for heterogeneity and cross-sectional correlation (Westerlund's ECM panel cointegration (2007) and panel bootstrap cointegration (2007) tests). The pooled mean group (PMG), mean group (MG), and dynamic fixed effects (DFE) methodologies were further applied to trace out the short-run dynamics. The results support evidence of significant dynamic linkages among the involved variables and reveal possible differences in the magnitude of the impacts from renewable and non-renewable energy consumption on environmental quality. The issue of distinguishing by source and determining the magnitude of the detected effects could provide valuable information for a sustainable economic and environmental development, substantially helping policy makers to designate more efficient policy measures.

The study analyzes the impact of economic growth, energy consumption, foreign direct investment inflows, population, population density, labor force, and trade openness on carbon dioxide emissions in seven emerging Asian economies over the period 1991-2017. To this end, it uses cross-section dependence test, second-generation unit root test, panel cointegration, and the bound test for cointegration and the autoregressive distributed lag estimations. The findings of the study are as follows: first, the kinked exponential growth is estimated for all the variables on the individual data set of seven countries. Second, the study finds a positive association of economic growth, energy consumption, population, and population density on carbon dioxide emissions. Third, it finds that the foreign direct investment inflows are negatively associated with carbon dioxide emissions. The paper also suggests potential implications and some future research avenues.