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Anderson and colleagues discuss the need to mitigate the longer term effects of the covid-19 pandemic in an equitable way.1 Plans for the United Kingdom need to tackle the triple public health challenge it faces from covid-19, climate change, and Brexit. The pandemic and measures to control it are exposing interwoven relationships between wellbeing, inequalities, the economy, the environment, and society as …

AbstractThe role of heating, ventilation, and air conditioning systems (HVAC) in spreading SARS-CoV-2 is a complex topic and has not been studied thoroughly. There are some existing strategies and technologies for health and high performance buildings; however, applications to other types of buildings come at large energy penalty: cost; design, regulations and standards changes, and varied public perception. In the present work, different factors and strategies are reviewed and discussed and suggested mitigations and solutions are provided including the required air flowrates with the presence of infectors with and without mask and disinfection techniques including ultraviolet (UV) light. Experimental and numerical research in open literature suggests that the airborne transmission of SARS-CoV-2 is sufficiently likely. However, in situ detailed experimental studies are still needed to understand the different scenarios of the virus spread. Displacement ventilation, underfloor air distribution, chilled beams, radiant ceiling panels, and laminar flow systems have varied effectiveness. High-efficiency particulate arrestance (HEPA) filters and UV light can clean viruses but at high energy cost. Suggested solutions to reduce the infection probability include recommended levels of ventilation and a combination of virus sampling technologies including cyclones, liquid impinger, filters, electrostatic precipitators, and water-based condensation.

PurposeOver the last decade, investments in green energy companies have witnessed noticeable growth rates. However, the glacial pace of the world economic restoration due to COVID-19 pandemic placed a high degree of uncertainty over this market. Therefore, this study investigates the short- and long-term relationships between COVID-19 new cases and WilderHill New Energy Global Innovation Index (NEX) using daily data over the period from January 23, 2020 to February 1, 2023.Design/methodology/approachThe authors utilize an autoregressive distributed lag bounds testing estimation technique.FindingsThe results show a significant positive impact of COVID-19 new cases on the returns of NEX index in the short run, whereas it has a significant negative impact in the long run. It is also found that the S&P Global Clean Energy Index has a significant positive impact on the returns of NEX index. Although oil has an influential effect on stock returns, the results show insignificant impact.Practical implicationsGovernments have the chance to flip this trend by including investment in green energy in their economic growth stimulation policies. Governments should highlight the fundamental advantages of investing in this type of energy such as creating job vacancies while reducing emissions and promoting innovation.Originality/valueFirst, as far as the authors are aware, the authors are the first to examine the effect of oil prices on clean energy stocks during COVID-19. Second, the authors contribute to studies on the relationship between oil prices and renewable energy. Third, the authors add to the emerging strand of literature on the impact of COVID-19 on various sectors of the economy. Fourth, the findings of the paper can add to the growing literature on sustainable development goals, in specific the papers related to energy sustainability.

Abstract This paper examines the time-frequency return and volatility spillovers between major commodity futures (copper, crude oil, gold, and wheat) and currency markets (British pound, Canadian dollar, Euro, Japanese yen, Swedish krona, and Swiss franc) using the methodologies by Diebold and Yilmaz (2012) and Barunik and Křehlik (2018). The results show that the spillover between markets under investigation is time-varying, asymmetric, and crisis-sensitive. Furthermore, short-term return spillovers dominate the intermediate- and long-term spillovers. In contrast, long-term volatility spillovers constitute the principal proportion of the total volatility spillovers. COVID-19 and GFC intensify more the long-term volatility spillovers than short- and medium-terms. Wheat is the better portfolio diversfier among the four commodities irrespective of the investment horizons. Liquidity shocks show a stronger impact on the return and volatility spillover strengths than the economic policy uncertainty and volatility index. The effect of liquidity shocks on return is a sizable increase in connectedness in the short-term than in both medium- and long-terms. Our findings have significant implications for currency investors and policymakers.

Stock market price prediction is considered a critically important issue for designing future investments and consumption plans. Besides, given the fact that the COVID-19 pandemic has adversely impacted stock markets worldwide, especially over the past two years, investment decisions have become more challenging for risky. Hence, we propose a two-phase framework for forecasting prices of oil, coal, and natural gas in India, both for pre-and post-COVID-19 scenarios. Notably, the Autoregressive Integrated Moving Average, Simple Exponential Smoothing, and K- Nearest Neighbor approaches are utilized for analyses using data from January 2020 to May 2022. Besides, the various outcomes from the analytical exercises are matched with root mean squared error and mean absolute and percentage errors. Overall, the empirical outcomes show that the Autoregressive Integrated Moving Average method is appropriate for predicting India's oil, coal, and natural gas prices. Moreover, the predictive precision of oil, coal, and natural gas in the pre-COVID-19 period seems to be better than in that the post-COVID-19 stage. Additionally, prices of these energy resources are forecasted to increase through the year 2025. Finally, in line with the findings, significant policy recommendations are made.

Since markets are undergoing severe turbulent economic periods, this study investigates the information transmission of energy stock markets of five regions including North America, South America, Europe, Asia, and Pacific where we differentiated the regional energy markets based on their developing and developed state of economy. We employed time-frequency domain from Jan 1995 to May 2021 and found that energy stocks of developed regions are highly connected. The energy markets of North America, South America, and Europe are the net transmitters of spillovers, whereas the Asian and Pacific energy markets are the net receivers of spillovers. The results also reveal that the connectedness of regional energy markets is time and frequency dependent. Regional energy stocks were highly connected following the Asian financial crisis (AFC), global financial crisis (GFC), European debt crisis (EDC), shale oil revolution (SOR), and COVID-19 pandemic. Time-dependent results reveal that high spillovers formed during stress periods and frequency domain show the higher connectedness of regional energy stock markets in the short run followed by an extreme economic condition. These results have significant implications for policymakers, regulators, investors, and regional controlling bodies to adopt effective strategies during short run to avoid economic downturns and information distortions.

Abstract In this study, we examine oil price extreme tail risk spillover to individual Gulf Cooperation Council (GCC) stock markets and quantify this spillover’s shift before and during the COVID-19 pandemic. A dynamic conditional correlation generalized autoregressive heteroscedastic (DCC- GARCH) model is employed to estimate three important measures of tail dependence risk: conditional value at risk (CoVaR), delta CoVaR (ΔCoVaR), and marginal expected shortfall (MES). Using daily data from January 2017 until May 2020, results point to significant systemic oil risk spillover in all GCC stock markets. In particular, the effect of oil price systemic risk on GCC stock market returns was significantly larger during COVID-19 than before the pandemic. Upon splitting COVID-19 into two phases based on severity, we identify Saudi Arabia as the only GCC market to have experienced significantly higher exposure to oil risk in Phase 1. Although all GCC stock markets received greater oil systemic risk spillover in Phase 2 of COVID-19, Saudi Arabia and the United Arab Emirates appeared more vulnerable to oil extreme risk than other countries. Our empirical findings reveal that investors should carefully consider the extreme oil risk effects on GCC stock markets when designing optimal portfolio strategies, minimizing portfolio risk, and adopting dynamic diversification process. Policymakers and regulators should also enact awareness, oversight, and action plans to minimize adverse oil risk effects.

We study time-scale co-movement of returns and implied volatilities of oil, gold, wheat, and copper in a multivariate setting using the wavelet local multiple correlation (WLMC) approach. Daily data cover January 03, 2007 – August 08, 2022, including the global financial crisis, COVID-19 pandemic, and Russia-Ukraine war. The results show that the correlations across the commodities are heterogeneous, less stable in the short-term, and more pronounced in the long-term, and vary in sign and magnitude. Despite market instability, contagion is not clearly seen in either return or volatility, reflecting noise trading and the importance of the individual characteristics of commodities. ; No Full Text