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The discussion concerning whether and how economic complexity (ECI) affects ecological footprint (EFP) has gained researchers' consideration, while there are slight empirical evidence to support the subject matter. In the support of theoretical argument, this study provides empirical evidence by investigating the impact of ECI on EFP along with the role of disaggregated energy consumptions by using a panel dataset of G-7 economies between 1996 and 2019. To this end, we applied panel techniques of Fully-Modify OLS and Dynamic-OLS models for cointegration analysis. The results obtained from Fully-Modify OLS and Dynamic-OLS models reveal that ECI deteriorates environmental quality by increasing EFP, while renewable energy reduces ecological pollution by decreasing EFP. In addition, the increasing demand for non-renewable energy and economic growth both degrades environmental quality in G-7 countries. More interestingly, the non-linear (ECI 2 ) relationship between ECI and EFP confirms a U-shaped association (EKC hypothesis), which suggests that after achieving a certain threshold level, economic complexity mitigates environmental degradation in G-7 economies. The empirical results also suggest that other control variables such as population growth, inflation rate, foreign direct investment, and total trade intensity lead to environmental degradation by increasing ecological footprint. Based on empirical results, the following important policy implications are drawn; first, G-7 economies should speed up the level of economic complexity along with renewable energy consumption to protect environmental quality and maintain sustainable growth and development. Secondly, the governments of G-7 countries should introduce greener technologies and promote production that are environmental friendly for drastic reduction in environmental unsustainability., (© 2022. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

This work analyzed the long-run (LR) and short-run (SR) effects of renewable and non-renewable energy (RE and NRE) usage, economic development (ED), agricultural value-added (AVA), and forestry area (FA) on the environmental quality (EQ) in China spanning from 1990 to 2015. The autoregressive distributed lags (ARDL) bounds testing method and the Johansen cointegration approach are applied to produce empirical estimates. The empirical results of the ARDL and the fully modified ordinary least square (FMOLS) estimators established that renewable energy usage and forest area reduce CO 2 emissions and improve the environmental quality, while non-renewable energy consumption, economic development, and agricultural output increase the level of CO 2 emissions in China. The robustness of outcomes is checked through the Granger causality test, impulse response function (IRF), and variance decomposition method (VDM) suggesting that fossil fuel usage in the agriculture production process is mainly accountable for China's CO 2 emissions. These findings have inherent policy implications for the central and local Chinese government, which are exhibited in the "Conclusions" section., (© 2021. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Since the development of the service sector and renewable energy reduce fossil-based energy consumption which mitigates CO 2 emissions and this nexus provides a better understanding of the environmental sustainability. Considering the substantially increasing contribution of service sector and tremendous potential for renewable energy in ASEAN5 countries, leaning forward from ASEAN's energy and growth nexus, this study examines the impact of service sector contribution and renewable energy on the environmental quality of ASEAN5 using annual data from 1990 to 2018. The results of the fully modified ordinary least squared, dynamic ordinary least squared, and canonical co-integrating regressions depicted that the service sectors of Thailand, the Philippines, and Singapore augment CO 2 emissions; however, the service sectors of Malaysia and Indonesia could reduce CO 2 emissions. The increasing share of renewable energy can enhance environmental quality, but its magnitude varies in ASEAN5 economies; non-renewable energy, population, and economic development deteriorate the environment. Our results confirm the existence of environmental Kuznets curve in all the ASEAN5; the Gregory-Hansen test confirmed that results are robust. Finally, the Granger causality designated that economic development and non-renewable energy have a significant causal relationship with CO 2 emission of ASEAN5 countries. These findings suggest that the ASEAN5 economies need to optimize their economic structure for promoting sustainable development in the long run.Graphical abstract., (© 2021. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Energy acts as a catalyst to boost the human development index (HDI) in a country. However, the overuse of energy leads to environmental deterioration, which is a byproduct of economic development. Due to the utilization of non-renewable energy sources for a long time, worldwide environmental conditions have become alarming. This study investigates the relationship between renewable and non-renewable energy consumption, economic growth, environmental sustainability, and the human development index (HDI) in Pakistan. The investigation incorporates population growth and technology variables to form a multivariate framework. We use a fully modified ordinary least squares (FMOLS) approach to time-series data from 1990-2017. To check the robustness of estimations, we apply the Gregory-Hansen test with a causality test under the VECM to confirm this association's directions. Our findings confirm that non-renewable energy sources have a positive association with economic growth and CO 2 emissions. However, human development, technology, and renewable energy boost economic development and reduce environmental pollution in Pakistan. The co-integration results confirmed the long run connectivity among all variables. The causality outcomes support the bidirectional causality between renewable and non-renewable energy consumption, economic growth, and CO 2 emissions, both in the short and long run. These outcomes suggest that Pakistan should focus on energy shifts and gradually increase the share of renewables in its energy mix under the China Pakistan Economic Corridor (CPEC). Additionally, the government should increase human and technological development to enhance economic and environmental sustainability.

The primary objective of this research was to determine the impact of renewable energy, alternative and nuclear energy, urbanization, energy use, and fossil fuel energy consumption on Romanian economic development. To investigate the relation between variables, we employed the Autoregressive Distributed Lag (ARDL) technique in conjunction with FMOLS (Fully Modified Least Squares) and CCR (Canonical Cointegrating Regression). Long-run and short-run findings suggest that alternative and nuclear energy, as well as fossil fuel consumption, has a positive association with economic growth, but renewable energy, urbanization, and energy usage have an adversative relationship with economic growth. Similarly, FMOLS and CCR statistics indicate that alternative and nuclear energy and fossil fuel consumption have a favorable impact on economic development. Renewable energy consumption, urbanization, and energy use, on the other hand, revealed a negative connection with economic progress. Conservative solutions are necessary to implement appropriate policies to address energy consumption concerns in Romania in order to improve economic development. [ABSTRACT FROM AUTHOR]