Green innovation, resource price and carbon emissions during the COVID-19 times: New findings from wavelet local multiple correlation analysis

This paper investigates how oil price, COVID-19, and global energy innovation can affect carbon emissions under time-and frequency-varying perspectives. We contribute to the literature by being the first research to document the relationship between these variables in the short and long run (dynamically) at different frequencies in a multivariate context, thus providing a more detailed picture of the forces driving CO2 emissions. For this purpose, we use a novel methodology, i.e., the wavelet local multiple correlation (WLMC) recently developed by Polanco-Martinez et al. (2020). The results provide fresh evidence of long-run asymmetric dynamic correlations, highlighting how the oil price plays a key role in the dynamics of CO2 emissions. Moreover, we find that, during the long period, there is a strong negative co-movement between CO2 and the global energy innovation index, i. e., more investment in clean energy induces less emission. Supported by our findings, this research suggests crucial policy implications and insights for the governments worldwide in their efforts to revive their economies amidst the pandemic and environmental uncertainties.

Role of Green Financing and Eco-Innovation for Energy Efficiency in Developed Countries: Contextual Evidence for Pre- and Post-COVID-19 Era

Following the environmental concerns such as global warming, climate change, and environmental degradation, scholars and policymakers discovered energy utilization as the key factor in these issues. Therefore, economies are paying more attention to green finance and eco-innovation to reduce energy usage and enhance energy efficiency. The prime objective of this study is to explore whether the mentioned variables exhibit any influence on the energy efficiency target achievement. In this sense, the current study explores the association of green finance and eco-innovation with energy intensity in the group of seven economies from 1990 to 2020. By using panel data approaches, this study employs diagnostic tests that confirm the heterogeneous slopes and the existence of panel cross-section dependence. Also, the cointegration tests validate the existence of a long-run equilibrium relationship between the variables. Based on the asymmetric distribution of the data, this study employs the method of moments quantile regression. The empirical results reveal that green finance and eco-innovation significantly reduce energy intensity across the selected quantiles. Control variables such as urban growth and trade openness also adversely affect energy intensity. However, economic growth is the only significant factor that enhances energy intensity. The results are robust as validated by the panel quantile regression and the Granger panel heterogenous causality test. Based on the findings, this study recommends that green finance be promoted and environmental-related technology innovation be encouraged to achieve the goal of energy efficiency in developed economies. This study also provides additional policies appropriate for environmental recovery.

Can tourism sustain itself through the pandemic: nexus between tourism, COVID-19 cases and air quality spread in the 'Pineapple State' Hawaii. (Special Issue: COVID-19 and tourism.)

The COVID-19 pandemic has severely hit the United States of America (USA) with tourism being one of the most directly affected sectors. The effect is even more striking in Hawaii, which has been one of the most popular tourist destinations in the United States since the 1950s. While the state government's early reaction has resulted in a decrease in COVID cases in this state, travel restrictions established in response to the pandemic have wreaked havoc on the state's tourist economy. To quantitatively measure this impact, this paper investigates the nexus between the international tourist arrivals, COVID-19 spread, and air quality in Hawaii. Using the daily data from March 2020 to August 2020, the study employs the robust methodology comprising Wavelet coherence, partial and multiple Wavelet coherence methods. The empirical results reveal a significant coherence between international tourists, COVID-19 cases, and air quality at different time-frequency compositions.

Non-linear spatial linkage between COVID-19 pandemic and mobility in ten countries: A lesson for future wave

Background: Restrictive measures enacted in response to the COVID-19 pandemic have resulted in dramatic and substantial variations in people's travel habits and behaviors worldwide. This paper empirically examines the asymmetric inter-linkages between transportation mobility and COVID-19. Methods: Using daily data from 1st March 2020 to 15th July 2020, this study draws the dynamic and causal relationships between transportation mobility and COVID-19 in ten selected countries (i.e., USA, Brazil, Mexico, UK, Spain, Italy, France, Germany, Canada, and Belgium). To systematically analyze how the quantiles of COVID-19 (transportation mobility) affect the quantiles of transportation mobility (COVID-19), a complete set of non-linear modeling including the quantile-on-quantile (QQ) regression and quantile Granger causality in mean is applied. Results: Our preliminary findings strictly reject the preposition of data normality and highlight that the observed relationship is highly correlated and quantile-dependent. The empirical results demonstrate the heterogeneous dependence between COVID-19 and transportation mobility across quantiles. The findings acclaim the presence of a significant positive association between COVID-19 and transportation mobility in the USA, UK, Spain, Italy, Canada, France, Germany and Belgium, predominantly at upper quantiles, but results are contrasting in the case of Brazil and Mexico. In addition, either lower or upper quantiles of both variables indicate a declining negative effect of transportation mobility on COVID-19. Furthermore, the outcomes of quantile Granger causality in mean conclude a bidirectional causal link between COVID-19 and transportation mobility for almost all sample countries. Unlike them, France has found unidirectional causality that extends from COVID-19 to transportation mobility. Conclusions: We may conclude that COVID-19 leads to a reduction in transportation mobility. On the other hand, the empirical results quantify that excessive transportation mobility levels stimulate pandemic cases, and social distancing is one of the primary measures to encounter infection transmission. Imperative country-specific policy implications pertaining to public health, potential virus spread, transportation, and the environment may be drawn from these findings. (c) 2021 The Author(s). Published by Elsevier Ltd on behalf of King Saud Bin Abdulaziz University for Health Sciences. This is an open access article under the CC BY-NC-ND license (http://creativecommons. org/licenses/by-nc-nd/4.0/).