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The coronavirus pandemic has infected more than 100 million people worldwide with COVID-19, with millions of deaths across the globe. In this research, we explored the effects of environmental and weather variables with daily COVID-19 cases and COVID-19 fatalities in Istanbul, Turkey. Turkey has the 8th highest number of COVID-19 cases globally, with the highest infections and deaths in Istanbul. This may be the first study to conduct a comprehensive investigation for environmental quality (air quality pollutants, e.g., PM2.5 and PM10, ozone, nitrogen dioxide, sulfur dioxide, carbon monoxide, etc.), weather parameters (temperature, humidity) and COVID-19 in Turkey. The authors collected meteorological data from 11 March 2020 to 8 February 2021 and COVID-19 data from Istanbul and other regions. The results from empirical estimations, correlation analysis, and quantile on quantile techniques support that air quality and temperature significantly influence COVID-19 deaths in Istanbul. This research may help policymakers and health scientists to take specific measures to reduce the spread of coronavirus across different global cities. The effects of air quality on COVID-19 in Istanbul was investigated. The study applied correlation and quantile on quantile techniques over daily data. Temperature significantly induces the spread of COVID-19 in Istanbul at all quantiles. Air quality and Nitrogen are positively linked with COVID-19 new cases. [ABSTRACT FROM AUTHOR]

The major tourist destinations in the Asian region are promoting and maintaining a conducive tourism environment. The susceptibility of the major tourist destinations in Asia to the uncertainties may encumber the arrival of international tourists. However, to the best of our understanding the research in this area is scant. Further though the tourism‐uncertainty nexus has been widely explored in the literature, the deliberations in a time‐varying and frequency‐domain framework continue to be ignored. Thus, building upon the earlier deficiencies this study, investigates in a time and scale varying framework the tourism uncertainty/risk nexus for Singapore and Malaysia, two major tourist destinations in the Asian region. This article endeavors to investigate the role of world policy uncertainty, US Monetary Policy Uncertainty, geopolitical risk, Global Financial Stress Index and market volatility on international tourist arrivals in Malaysia and Singapore. To the best of our understanding, this study is the foremost to scrutinize the interrelatedness between these variables in a multivariate wavelet causality framework, from January 2000 to April 2020. Our results show that the global uncertainties manifested through different macro‐based indicators affect international tourism demand for the destination countries. During the subprime crisis, Euro‐crisis and the pandemics significant coherencies are perceptible. The major empirical findings of the impact of uncertainty indicators and geopolitical risk on international tourist arrivals over the recent period have important implications for policy makers and practitioners. [ABSTRACT FROM AUTHOR]

While gaining more popularity both as a financial asset and a commodity, a number of cryptocurrencies are emerging with a loosely regulated market microstructure which is a challenge to their efficiency. We have ranked 6 out of the top 10 cryptocurrencies based on their inefficiency ratios, using a novel time‐varying generalised Hurst exponent methodology. All the six crypto markets exhibit a time‐varying efficiency throughout the studied period, thus indicating a varying degree of exploitable profitable trading opportunities. The inefficiency ratio indicates that Bitcoin is the third most inefficient market, while the first and second most inefficient markets are DASH and NEM, respectively, thus they provide the most abnormal profit opportunities. However, the most efficient crypto markets are Ethereum and Ripple according to the order of their rankings. Further research could be performed on the factors affecting the inefficiency index to understand the efficiency determination of these cryptocurrency markets. [ABSTRACT FROM AUTHOR]

This study attempts to explore the causal linkage of the COVID-19 pandemic, economic policy uncertainty, geopolitical risk, and tourism arrivals in the United States taking data from January to November 2020. In order to analyze the above relationship, this study uses a novel time-varying granger causality test developed by Shi et al. (2018) , which incorporates its three causality algorithms such as forward recursive causality, rolling causality, and recursive evolving causality. The findings from forward recursive causality could not confirm any significant causal relationship between COVID-19 and tourism, geopolitical risk (GPR) and tourism, economic policy uncertainty and tourism, and geopolitical risk and COVID-19 but found causality between economic policy uncertainty and COVID-19. The rolling window causality reported bidirectional causality between COVID-19 and tourism and unidirectional causality running from tourism to geopolitical risk. However, the recursive evolving causality identified a significant bidirectional causal relationship between all the variables. Based on the findings, policy implications for the tourism sector are provided. [ABSTRACT FROM AUTHOR]

The world is confronted with a slew of environmental issues, one of which is attenuating the detrimental impacts of carbon dioxide (CO2) emission-induced climate change. The ever-increasing use of energy is eroding natural resources to the point that our economic future may be jeopardized. The Tunisian economic growth indicates the excellent performance in the industrial sector as the minimum required input for these developments which necessitate additional energy consumption, resulting in increased CO2 emissions and environmental degradation. This study explores the role of energy efficiency, urbanization, economic growth, and natural gas energy usage in the industrial sector on the CO2 emissions of Tunisia. The research mainly employs the vector autoregressive model (VAR) to examine the factors driving the evolution of CO2 emissions through the industrial sector from 2000 to 2018. The findings assess that natural gas as an energy source and efficiency is crucial for reducing CO2 emissions. The study has shown the existence of the environmental Kuznets curve (EKC), which demonstrates that economic development in Tunisia has an inverted U-shape connection with CO2 emissions. The findings show that energy consumption and GDP have a considerable impact on CO2 emissions due to large-scale population changes and industrial structure alteration. In contrast, energy efficiency is a key factor in lowering CO2 emissions. Based on the study's results, the article will enable economic decision-makers and relevant authorities to develop an appropriate energy strategy for the industrial sector to safeguard environmental deterioration in the long term by lowering carbon emissions. [ABSTRACT FROM AUTHOR]

This paper explores the impact of an environmental tax on carbon emissions for the G7 nations from 1994 to 2014 and the importance of the major drivers of emissions such as energy use, economic complexity, natural resources rent and economic growth. The study also verifies the Environmental Kuznets Curve Hypothesis for the G7 countries and explores the marginal effects of an environmental tax on traditional energy consumption, natural resources rent and renewable energy consumption. This paper's unique contribution is that it investigates for the first time the moderating role of an environmental tax on renewable and non-renewable energy consumption, natural resources rent and CO 2 emissions. The results suggest that environmental taxes effectively reduce emissions for the G7 countries and confirm that the marginal effects of the environmental tax on traditional energy consumption, natural resources rent and renewable energy consumption rise with the level of taxation in a statistically significant way. The findings indicate that strict environmental tax laws will allow businesses to shift production towards cleaner methods. Finally, the paper proposes that redistributing tax revenues to the research and development of sustainable technology programmes would empower the nations to achieve the United Nations' SDG-7 and SDG-13 goals. Flow Diagram on the nexus between emissions, tax, economic complexity, energy and economic growth. [Display omitted] • The paper analyses the effects of economic complexity on carbon emissions. • Environmental tax affects directly carbon emissions. • Environmental tax lessens the effect of energy consumption and natural resources. • Environmental tax amplifies the effect of renewable energy consumption. • The EKC hypothesis is validated for economic complexity in G7. [ABSTRACT FROM AUTHOR]

This study investigates the role of the import diversification in the renewable energy consumption for a global panel of both developing and developed economies. The study applies panel co-integration and panel quantile regression analysis on the panel data of 138 countries during 1995–2018. For empirical analysis, the authors used Pedroni) cointegration test and panel-quantile regressions. The investigation proves that the import diversification significantly reduces the renewable energy consumption and there is a major need for designing and implementing some revised and synchronized policies of trade with the energy mix and sustainable development goals. The empirical findings claim that the foreign direct investments, natural resources and GDP increase significantly boost the renewable energy demand for both groups of developing and developed countries. Therefore, this study shows that generally the current trade policies might be ineffective and import diversification policies should be reformed to match with the energy regulations, manufacturing, and sustainable development goals. [ABSTRACT FROM AUTHOR]

The prime objective of this article is to examine the heterogeneous impacts of economic complexity on renewable energy demand within a panel of G7 and E7 countries. One of the important contributions of this research is to explore the role of overall structural change and economic factors for renewable and cleaner energy in developed and emerging economies. The existing literature points to scant research about the impacts of economic complexity on energy transformation and renewable energy adoption. During recent years, the G7 and E7 countries have encountered enormous competition in manufacturing and industrialization and are also experiencing global pressure from both climate change and Sustainable Development Goals (SDGs) for the promotion of renewable energy infrastructure. Taking into consideration the heterogeneity of issues, the authors apply the Westerlund cointegration and heterogeneous panel data techniques (FGLS, system GMM, FMOLS, and DOLS) for an in-depth, empirical analysis. Interestingly, empirical findings indicate that economic complexity affects renewable energy demand from G7 and E7 countries. This paper documents that economic complexity is a policy factor for overall energy transformation and greener energy demand. This study recommends that complexity and structural change policies should be observed for cleaner and greener growth and overall greener energy promotion. [ABSTRACT FROM AUTHOR]