Asymmetric impact of renewable energy consumption and technological innovation on environmental degradation: designing an SDG framework for developed economy.

Many European nations, including Spain, are having difficulties achieving their Sustainable Development Goals (SDGs) objectives. Resultantly, the current research discusses the development of an SDG framework for Spain, which can be utilized as a model for other EU nations. This research examines whether GDP growth, technological innovation, and energy sources (renewable and non-renewable) have any effect on CO2 emissions utilizing data from 1980 to 2018. The study applied the non-linear ARDL (NARDL) to investigate these interrelations. The outcomes from the NARDL revealed that positive (negative) shocks in renewable energy improve environmental quality in Spain. Furthermore, positive (negative) shocks in technological innovation lead to a decrease (increase) in CO2. Lastly, positive (negative) shocks in energy consumption lead to an increase (decrease) in CO2. The results reveal that Spain is on the right path towards decarburization. This research has important policy ramifications for the policymakers and government of Spain as well as neighbouring countries.

Asymmetric nexus between technological innovation and environmental degradation in Sweden: an aggregated and disaggregated analysis.

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.

The asymmetric effects of renewable energy consumption and trade openness on carbon emissions in Sweden: new evidence from quantile-on-quantile regression approach.

With the passage of time, the continued burning of fossil fuels is proving to be one of the world's most serious issues. In response, the current research aims to assess the critical linkage between carbon emissions and renewable energy, trade openness, and economic growth in Sweden utilizing a dataset from 1965 to 2019. The study applied the novel quantile-on-quantile regression (QQ) approach to assess this relationship. The main objectives are to address the following questions: (i) What are the effects of trade openness on CO2 emissions in each quantile? (ii) Does renewable energy consumption mitigates CO2 emissions in each quantile? What is the impact of economic growth on CO2 emissions in each quantile? The outcomes from the QQ approach revealed that at low and medium quantiles (0.1-0.6), the effect of trade openness on CO2 emissions is negative. Furthermore, at lower and higher quantiles (0.1-0.90) of combination of renewable energy consumption and CO2 emissions, the effect of renewable energy consumption on CO2 emissions is negative. Finally, at majority of the quantiles, the effect of economic growth on CO2 emissions is negative. Moreover, the present study applied the quantile regression (QR) approach as a robustness check. The findings of the QR validate the findings of the QQR approach. The study proposes that policy-makers in Sweden should place greater emphasis on raising public awareness regarding the issues of renewable energy since it mitigates environmental degradation.

Wavelet analysis of impact of renewable energy consumption and technological innovation on CO2 emissions: evidence from Portugal.

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.

The role of economic complexity in the environmental Kuznets curve of MINT economies: evidence from method of moments quantile regression.

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.

Dominance of Fossil Fuels in Japan's National Energy Mix and Implications for Environmental Sustainability.

Despite the drive for increased environmental protection and the achievement of the Sustainable Development Goals (SDGs), coal, oil, and natural gas use continues to dominate Japan's energy mix. In light of this issue, this research assessed the position of natural gas, oil, and coal energy use in Japan's environmental mitigation efforts from the perspective of sustainable development with respect to economic growth between 1965 and 2019. In this regard, the study employs Bayer and Hanck cointegration, fully modified Ordinary Least Square (FMOLS), and dynamic ordinary least square (DOLS) to investigate these interconnections. The empirical findings from this study revealed that the utilization of natural gas, oil, and coal energy reduces the sustainability of the environment with oil consumption having the most significant impact. Furthermore, the study validates the environmental Kuznets curve (EKC) hypothesis in Japan. The outcomes of the Gradual shift causality showed that CO2 emissions can predict economic growth, while oil, coal, and energy consumption can predict CO2 emissions in Japan. Given Japan's ongoing energy crisis, this innovative analysis provides valuable policy insights to stakeholders and authorities in the nation's energy sector.