• Energy Research

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. 

In the face of mounting climate change challenges, reducing emissions has emerged as a key driver of environmental sustainability and sustainable growth. Despite the fact that research has been conducted on the environmental Kuznets curve (EKC), few researchers have analyzed this in the light of economic complexity. Thus, the current research assesses the effect of economic complexity on CO2 emissions in the MINT nations while taking into account the role of financial development, economic growth, and energy consumption for the period between 1990 and 2018. Using the novel method of moments quantile regression (MMQR) with fixed effects, an inverted U-shape interrelationship is found between economic growth and CO2 emissions, thus validating the EKC hypothesis. Energy consumption and economic complexity increase CO2 emissions significantly from the 1st to 9th quantiles. Furthermore, there is no significant interconnection between financial development and CO2 emissions across all quantiles (1st to 9th). The outcomes of the causality test reveal a feedback causal connection between economic growth and CO2, while a unidirectional causality is established from economic complexity and energy use to CO2 emissions in the MINT nations. Based on the findings, we believe that governments should stimulate the financial sector to provide domestic credit facilities to industrialists, investors, and other business enterprises on more favorable terms so that innovative technologies for environmental protection can be implemented with other policy recommendations.

The number of studies on the relationship between technological innovation and CO2 emissions has gradually increased in recent years, although there is no clear agreement in the literature. Previous research has revealed both positive and negative consequences of technological innovation on the environment. Moreover, most researchers have used linear approaches to explore this connection, which can result in spurious outcomes when nonlinearities exist in the data. According to this background, this research utilizes asymmetric ARDL and spectral causality approaches to assess the asymmetric connection between technological innovation and CO2 emissions in Sweden utilizing data from 1980 to 2018. In addition, the disaggregated asymmetric effects of technological innovation (patent resident and patent nonresident) on CO2 are also captured in this study. The Nonlinear Autoregressive Distributed lag (NARDL) results showed that positive (negative) shocks in economic growth enhance environmental quality in Sweden. Furthermore, a positive (negative) shock in technological innovation causes a decrease (increase) in CO2. Similarly, a positive (negative) shock in patent nonresident and residents leads to a decrease (increase) in CO2 emissions in Sweden. The outcomes from the spectral causality revealed that in the medium and long term, aggregate and disaggregate technological innovation can predict CO2 emissions in Sweden. This study has significant policy implications for policymakers and the government in Sweden. Based on these findings, the study suggests that the government of Sweden should investment in technological innovation since it plays a vital role in curbing environmental degradation.

This research offers a new perceptive of the dynamic connection between CO2 and globalization, technological innovation (TI), economic growth, and renewable energy (REN) consumption in Spain. The current research applied the wavelet tools to assess these interconnection utilizing data stretching from 1980 to 2018. The outcomes of these analyses disclose that the association among the series evolves over frequency and time. The current analysis uncovers notable wavelet coherence and strong lead and lag connections in the frequency domain, whereas the time domain indicates inconsistent correlations among the variables of interest. The outcomes of the wavelet analysis from the economic perspective affirm that in the short and medium term, globalization, economic growth, and TI contribute to environmental degradation; however, in the long term, globalization, economic growth, and TI do not contribute to the degradation of the environment. Moreover, at different frequencies, REN consumption helps mitigate environmental degradation in Spain. Furthermore, the spectral causality test unveiled that in the long term, REN utilization, globalization, TI, and economic growth can predict CO2 emissions in Spain.

The role of renewable energy and globalization on ecological footprint is investigated in the USA by controlling for the effects of financial development and real output using quarterly data from 1985:Q1 to 2014:Q4. We apply the minimum Lagrange multiplier unit root test, multiple structural break cointegration test, and autoregressive distributed lag (ARDL) estimation approach. The empirical evidence suggests that, in the long run, renewable energy and real output exert negative pressure on ecological footprint while financial development and globalization exert positive pressure on ecological footprint. The short-run results indicate that renewable energy, financial development, real output, and globalization are positively linked to ecological footprint. The vector error correction model Granger causality results, in the long run, divulge that ecological footprint, consumption of renewable energy, real output, and globalization Granger-cause financial development while ecological footprint, renewable energy, financial development, and globalization Granger-cause real output. The results also show that, in the short run, renewable energy and globalization cause ecological footprint and real output causes renewable energy, while renewable energy causes globalization. The finding also reveals that the causality between real output and globalization, as well as globalization and financial development, is bidirectional. Therefore, our findings provide insights for policymakers to consider consumption of renewable energy as a surest way to mitigate carbon dioxide emissions.

AbstractThis study examines the impacts of digitalization through information and communication technology (ICT) and environmental taxes on greenhouse gas (GHG) emissions in 23 European Union (EU) countries between 2000 and 2017. Using the Pooled Mean Group estimator, the empirical results provide evidence that ICT development and environmental taxes improve environmental sustainability while research and development investments and income per capita deteriorate environmental sustainability. Furthermore, the results based on the Dynamic Panel Threshold Regression model show that the relationship between ICT and GHG emissions is dependent on the level of environmental taxes. During the period of low environmental taxes, the effect of ICT on GHG emissions is positive and insignificant but once environmental taxes cross the threshold value, the effect of ICT becomes negatively related to greenhouse gas emissions. This suggests that the period of low environmental taxes does not support the environmental friendliness of ICT development in the European region. The policy implication of these findings is that ICT, environmental taxes, and renewable energy can be possibly stirred up to achieve long‐term environmental sustainability in the EU region.

This paper uncover a new perception of the dynamic interconnection between CO2 emission and economic growth, renewable energy use, trade openness, and technological innovation in the Portuguese economy utilizing innovative Morlet wavelet analysis. The research applied continuous wavelet transform, wavelet correlation, the multiple and partial wavelet coherence, and frequency domain causality analyses are applied on variables of investigation using dataset between 1980 and 2019. The result of these analyses disclosed that the interconnection among the indicators progresses over time and frequency. The present analysis finds notable wavelet coherence and significant lead and lag interconnections in the frequency domain, while conflicting relationships among the variables are found in the time domain. The wavelet analysis according to economic viewpoint affirms that renewable energy consumption helps to curb CO2 while trade openness, technological innovation, and economic growth contribute to CO2. The outcomes also proposed that renewable energy consumption decreases CO2 in medium and long run in Portugal. Therefore, policymakers in Portugal should stimulate investment in renewable energy sources, establish restrictive laws, and enhance energy innovation.

AbstractThe excessive use of non-renewable energy in 21st-century economic growth has continued to hurt the environment by accumulating carbon dioxide and other greenhouse gases. However, promoting environmental sustainability requires expanding clean energy utilisation. In this study, we examine the effects of clean energy expansion and natural resource extraction on load capacity factor (LCF) in China from 1970 to 2018. Using the dynamic autoregressive distributed lag simulations approach, we extend the standard load capacity curve (LCC) hypothesis by incorporating clean energy expansion and natural resource extraction as main determinants of the LCF. The empirical outcomes reveal that economic expansion is, although positively associated with the LCF, but its squared term degrades the LCF. This confirms that the LCC hypothesis is not valid for China. Moreover, while clean energy expansion has a positive effect on the LCF, the effect of natural resource extraction is negative. These effects are stronger and statistically significant only in the long run. Therefore, this study highlights the potentials for a sustainable decarbonized economy in China by investing not only in clean energy sources but also efficiently use the available natural resources in the country.