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The United States is the world's second-largest polluter, generating 4.7 billion metric tons of CO2 in 2020. To combat it, the US is targeting a precise goal of 50–52 percent decrease in net CO2 emissions from 2005 levels by 2030. Hence, it is vital to determine the critical factors contributing to Sustainable Development Goals (SDGs). With this motivation, this study examines dynamic link between green energy transition, eco-innovation, economic policy uncertainty, energy use, economic growth, and sectoral CO2 emissions (SCO2) in the United States from 1980 to 2020 by using novel Quantile-On-Quantile Regression (QQR) and Granger causality in quantile approaches. The results show that the quantiles of the green energy transition are positively related to all SCO2 quantiles. While eco-innovation and SCO2 are marginally favorable in the lower to higher quantiles, positive slope coefficients showcase the effect of economic policy uncertainty on SCO2 in the 0.2–0.95 quantiles. Similarly, SCO2 and the energy use showed positive and negative results across quantiles, whereas QQR slope coefficients between SCO2 and economic growth are positive and negative throughout the quantiles. Suggests that investment in green energy and eco-innovation also reduces economic policy uncertainty by delivering energy for all sectors is vital if SDG-7 is executed by 2030.

Globally, economies have become complex and new technologies have transformed and facilitated the modernization of economies. In the previous literature, economic complexity approach has become one of the popular tools in the development and innovation studies of economic geography. Researchers have found that green technology and eco-innovation approaches should be used to decisively reduce the effects of carbon emission on the environment. However, debates about the impact of economic complexity on environment remain unsettled since some emerging production technologies have far-reaching pollution effects. This study explored the impacts of economic complexity on environmental sustainability in Turkey using the novel Fourier-based approaches, namely: Fourier Augmented Dickey-Fuller (FADF) and Fourier autoregressive-distributed lag (FARDL) models. The Fourier-based approaches indicated that all variables (economic complexity index (ECI), GDP, energy consumption, and CO2emission (CO2E)) are cointegrated in the long run. Additionally, the FARDL model implied that (i) in the long run, the effect of ECI (as a proxy for economic complexity), GDP (as a proxy for economic growth), and energy consumption on CO2E (as a proxy for environmental quality) is important; (ii) economic complexity decreases environmental degradation in Turkey; and (iii) economic growth and energy consumption negatively affect environmental quality. The results also showed that economic complexity could be used as a policy tool to tackle environmental degradation. The findings also revealed that the fossil fuel-based economy will continue to expand and undermine Turkey's efforts to meet its net zero emission target by 2053. Therefore, policy-makers should take actions and establish diversified economic, environmental, and energ strategies. For policy insights, the Turkish governments can use the combination of tax exemptions and technical support systems to support knowledge creation and the diffusion of environmentally friendly technologies The governments can also impose strict environmental regulations on the knowledge development phases.

AbstractClimate change traps heat, affecting a variety of species in already dry areas. Severe storms, earthquakes, plagues, and food delivery problems are all exacerbated by climate change caused by emissions of greenhouse gases. The United States, the world’s largest economy and second-largest carbon emitter is expertly planning to reduce its environmental difficulties and help the accomplishment of the United Nations Sustainable Development Goals (SDGs) 7 and 13. Given that, the study explores the renewable energy transition, ecological innovation, economic policy uncertainty, and globalization from 1990 to 2019 by using novel econometric approaches augmented ARDL and gradual shift causality. The results show that variables are cointegrated, particularly in the long and short term; renewable energy transition and economic policy uncertainty reduce carbon emissions, while ecological innovation contributes to long-run depletion in CO2emission. Globalization significantly accelerates emissions in the long and short term. Furthermore, gradual shift causation reveals that renewable energy transition and globalization are unidirectional, but economic policy uncertainty is bidirectional. Finally, the conclusion implies that transitioning from fossil to renewable energy, adequate use of technology, efficient management of policy uncertainties and globalization may contribute to the United States meeting SDGs 7 and 13.

Pakistan is in a terrifying and devastating energy crisis. Recently, the prediction for energy consumption has intensified compared to its production capacity, which is problematic for Pakistan's social and economic stability. Hence, it is vital to examine the link between power consumption, power prices, urban transition, other electricity use, and economic expansion from 1970 to 2018 in Pakistan. For analysis, the second-generation econometric technique of Lee and Strazicich (2013), novel Augmented Autoregressive Distributed Lag (AARDL), and Frequency Domain Causality (FDC) is useful to detect the long-medium and short-run association among the variables. The results show that power consumption stimulates economic expansion in the short and long-run, though the rise in power prices declines economic activity in the short and long-run. Also, urban transition and other electricity use are a substantial positive and negative impact on economic expansion in the short and long-run. The outcome suggests that efficient energy supply, low-cost power prices, proper urban transition management, and other energy use could be useful for policymakers to achieve SDGs 7 and 11 in Pakistan.