Renewable energy consumption and CO2 emissions nexus in the USA: the role of technical innovation.

Using the QARDL approach and data from January of 2010 to May of 2022, we explore how renewable energy consumption affects CO2 emissions in the USA. Long-term analysis reveals a negative link between these variables, while only lower quantile levels show short-term statistical significance. Integrating technical innovation (measured by patents) in our QARDL model shows substantial reduction in CO2 emissions, with varying effects over time. Interestingly, only renewable energy consumption, not technical innovation, significantly impacts CO2 emissions at lower quantile levels. These findings emphasize the crucial role of renewable energy in reducing both short-term and long-term CO2 emissions and offer policymakers valuable insights for shaping effective energy strategies to combat emissions and promote sustainability in the USA.

Does tourism market diversification matter for CO2 emissions? evidence from Singapore.

This research analyzed the effect of tourism market diversification on Singapore's CO2 emissions by measuring the level of concentration of source countries in a foreign tourist basket of Singapore using a Herfindahl-Hirschman index. Our results indicated that the index fell over the period 1978-2020, which means the diversification of source countries of Singapore's foreign tourists increased. By applying the recent bootstrap and quantile ARDL models, we found that tourism market diversification and inward FDI act as stumbling blocks to CO2 emissions. In contrast, economic growth and primary energy consumption increase CO2 emissions. Policy implications are presented and discussed.

Assessing the EKC hypothesis by considering the supply chain disruption and greener energy: findings in the lens of sustainable development goals.

This paper investigates the effect of the supply chain disruption, greener energy consumption, and economic growth on carbon emissions in advanced economies and emerging markets from 1997 to 2021 using panel quantile autoregressive distributed lags (QARDL) and the panel quantile regression (QR). The results of the two models confirm, on the one hand, the validity of the environmental Kuznets curve (EKC) hypothesis and, on the other hand, the role of renewable energy consumption in mitigating carbon emissions in advanced and developing economies. Furthermore, the finding shows that the supply chain disruption for the long run is positive at all quantiles, indicating the evidence of association at the extreme low and high quantiles than at the intermediate quantile. In addition, the effect of the supply chain decreases at the lower quantile. It turns negative at the upper 90th quantile in the short run, indicating that the supply chain disruption reduces the environmental degradation under the bearish market conditions. In the future, the increasing supply chain disruptions due to the Russia-Ukraine conflict and further COVID-19 worldwide can consider sluggish economic growth and play an essential role in promoting renewable energy abundance and reducing CO2 emissions. Practical implications are reported in the lens of carbon neutrality and structural changes.

Investigating the existence of asymmetric environmental Kuznets curve and pollution haven hypothesis in China: Fresh evidence from QARDL and quantile Granger causality.

This study aims to analyze the asymmetric long-run relationship between economic growth (EG), foreign direct investment (FDI), and carbon emissions (CO2) within the context of the environmental Kuznets curve (EKC) and the pollution haven hypothesis (PHH) in China. Employing the quarterly data from 1982Q1 to 2018Q4, we have used novel techniques to meet the stated objectives of our study, named quantile ARDL and quantile Granger causality. The study provides novel outcomes using the advanced quantile ARDL and quantile Granger causality tests. The significant implication of this method is that it provides locational asymmetry. We find strong evidence of the EKC and PHH for China based on the empirical results of linear and nonlinear ARDL models. Similarly, findings of quantile Granger causality validate the bidirectional relationship among all variables in upper and lower quantiles. Moreover, the results of the Wald test confirm the asymmetric long-run relationship between FDI and carbon emissions (CO2). Thus, legal measures must be enhanced, accepted, rigorously imposed, and monitored in all provinces to assure a further reduction in carbon emissions. This study will be conducive for the policymakers to combat environmental contamination concerning economic growth and FDI inflow in China.

The potency of eco-innovation, natural resource and financial development on ecological footprint: a quantile-ARDL-based evidence from China.

Given the alarming deterioration of the environment, the present analysis investigates the role of eco-innovation, natural resources and financial development in influencing the environmental degradation of China. Applying the novel method of quantile ARDL, the current research is beneficial in portraying the dependence patterns of the variables with special emphasis on the nexus of eco-innovation and ecological footprint across numerous quantiles of the distribution which has not been examined so far in the literature. The empirical findings reveal that in the long run, eco-innovation reduces the level of ecological deterioration in China across all quantiles. On the other hand, the results suggest that the increase in credit to the private sector and natural resource rents augments environmental degradation. The outcomes imply that the over-dependence on natural resources and financial development can worsen the goals of sustainable development in China if the strategies of conservation and management are ignored. Moreover, witnessing the favorable role of eco-innovation, competent policies and regulations can be made toward sustainable efficient technologies and eco-friendly energy sources to halt global warming.

The asymmetric effect of temperature, exchange rate, metals, and investor sentiments on solar stock price performance in China: evidence from QARDL approach.

The study investigates the asymmetric effect of temperature, exchange rate, metals (rare metals and electrical conductors), and investor sentiments on solar stock price performance in China. The novel econometric techniques, i.e., QARDL (quantile autoregressive distributive lag) approach and Granger causality-in-quantiles to analyze the results. In both short- and long-run estimations, the findings suggest that rare metals (cadmium, germanium, indium, and selenium) and electrical conductors (silver, aluminum, and copper) have significant and positive linkage with solar energy stocks at different quantiles based on bullish, bearish, and normal market conditions. On the other hand, negative effects are found for temperature, RMB exchange rate, and investor sentiments in both the short- and long-run. In the short run, the effect of exchange rate varies across different quantiles but it confines to only lower quantiles (bearish market condition) in the longer run. Solar stocks are more prone to investor sentiments under higher quantiles (bullish market conditions). Lastly, we find that temperature is not merely a behavioral anomaly for the solar energy market as it spreads across middle quantiles (normal market conditions) in the longer run. The findings of Granger causality in quantiles further confirm the results of QARDL.