Face mask is an efficient tool to fight the Covid-19 pandemic and some factors increase the probability of its adoption.

This study examines the dynamic impact of face mask use on both infected cases and fatalities at a global scale by using a rich set of panel data econometrics. An increase of 100% of the proportion of people declaring wearing a mask (multiply by two) over the studied period lead to a reduction of around 12 and 13.5% of the number of Covid-19 infected cases (per capita) after 7 and 14 days respectively. The delay of action varies from around 7 days to 28 days concerning infected cases but is more longer concerning fatalities. Our results hold when using the rigorous controlling approach. We also document the increasing adoption of mask use over time and the drivers of mask adoption. In addition, population density and pollution levels are significant determinants of heterogeneity regarding mask adoption across countries, while altruism, trust in government and demographics are not. However, individualism index is negatively correlated with mask adoption. Finally, strict government policies against Covid-19 have a strong significant effect on mask use.

Social and moral psychology of COVID-19 across 69 countries.

The COVID-19 pandemic has affected all domains of human life, including the economic and social fabric of societies. One of the central strategies for managing public health throughout the pandemic has been through persuasive messaging and collective behaviour change. To help scholars better understand the social and moral psychology behind public health behaviour, we present a dataset comprising of 51,404 individuals from 69 countries. This dataset was collected for the International Collaboration on Social & Moral Psychology of COVID-19 project (ICSMP COVID-19). This social science survey invited participants around the world to complete a series of moral and psychological measures and public health attitudes about COVID-19 during an early phase of the COVID-19 pandemic (between April and June 2020). The survey included seven broad categories of questions: COVID-19 beliefs and compliance behaviours; identity and social attitudes; ideology; health and well-being; moral beliefs and motivation; personality traits; and demographic variables. We report both raw and cleaned data, along with all survey materials, data visualisations, and psychometric evaluations of key variables.

Spillovers and connectedness in foreign exchange markets: The role of trade policy uncertainty.

This paper analyses the directional spillover effects and connectedness for both return and volatility of nine US dollar exchange rates of globally most traded currencies under the influence of trade policy uncertainty. We find two interesting results over the study period ranging from December 1993 to July 2019. First, there exists asymmetric spillovers and connectedness among the considered exchange rates when trade policy uncertainty is present. Second, the volatility spillover is stronger than the return connectedness between exchange rate and trade policy uncertainty. These findings are robust to the presence of economic policy uncertainty effects. Concomitantly, the trade policy uncertainty patterns are also found to be useful for predicting currency market dynamics. Our findings contribute to the debate on the impact of trade policy uncertainty on the global economy and financial sector.

Trust and the stock market reaction to lockdown and reopening announcements: A cross-country evidence.

We conduct a country-level analysis with a sample of 44 countries to examine whether generalised social trust has an impact on the stock market reaction to government announcements of lockdown and reopening during the COVID-19 pandemic. We first conduct an event study to measure the global stock markets' reaction to government announcements of lockdown and reopening, which is measured by each stock market's cumulative abnormal return. We then employ regression analysis to investigate the relationship between generalised social trust and the stock markets' reaction to government announcements of lockdown and reopening. The results show that government announcement of lockdown had a significant negative influence on most of the stock markets, whereas the magnitude of the stock markets' reaction to government announcement of reopening is relatively marginal, indicating a possible negative bias. Moreover, we find that generalised social trust is positively related to the stock markets' reaction to government announcement of lockdown and negatively related to the stock markets' reaction to government announcement of reopening.

Tail risk connectedness in clean energy and oil financial market.

This research investigates the connectedness and the tail risk spillover between clean energy and oil firms, from January 2011 to October 2021. To this, we use the Tail-Event driven NETworks (TENET) risk model. This approach allows for a measurement of the dynamics of tail-risk spillover for each sector and firm. Hence, we can provide a detailed picture of the existing extreme relationships within these markets. We find that the total connection between the markets varies during the period analysed, showing how the uncertainty in oil price plays a critical role in the risk dynamics for oil companies. Also, we find that relationships between energy firms tend to be intrasectoral; that is, each sector receives (emits) risk from (to) itself. These results can have important practical implications for risk management and policymakers.

COVID-19 challenges and firm responses: Analysis of a city-wide census in a developing country.

We use the unique data set of 16,300 firms' responses for the large-scale census survey in an urban area at Ho Chi Minh City (Vietnam) to study how firms perceived their problems and responded to during the COVID-19 pandemic. We provide estimates of 65 cross-associations between a firm's challenges during the pandemic and their responses. We find several firm characteristics that suggest increased likelihood of pandemic response, including some, such as state ownership, which are typically associated with being slow to respond to market conditions. A theoretical model is posited that matches with the rapidly declared survey response.

National identity predicts public health support during a global pandemic.

Changing collective behaviour and supporting non-pharmaceutical interventions is an important component in mitigating virus transmission during a pandemic. In a large international collaboration (Study 1, N = 49,968 across 67 countries), we investigated self-reported factors associated with public health behaviours (e.g., spatial distancing and stricter hygiene) and endorsed public policy interventions (e.g., closing bars and restaurants) during the early stage of the COVID-19 pandemic (April-May 2020). Respondents who reported identifying more strongly with their nation consistently reported greater engagement in public health behaviours and support for public health policies. Results were similar for representative and non-representative national samples. Study 2 (N = 42 countries) conceptually replicated the central finding using aggregate indices of national identity (obtained using the World Values Survey) and a measure of actual behaviour change during the pandemic (obtained from Google mobility reports). Higher levels of national identification prior to the pandemic predicted lower mobility during the early stage of the pandemic (r = -0.40). We discuss the potential implications of links between national identity, leadership, and public health for managing COVID-19 and future pandemics.

When Elon Musk Changes his Tone, Does Bitcoin Adjust Its Tune?

We present a textual analysis that explains how Elon Musk's sentiments in his Twitter content correlates with price and volatility in the Bitcoin market using the dynamic conditional correlation-generalized autoregressive conditional heteroscedasticity model, allowing less sensitive to window size than traditional models. After examining 10,850 tweets containing 157,378 words posted from December 2017 to May 2021 and rigorously controlling other determinants, we found that the tone of the world's wealthiest person can drive the Bitcoin market, having a Granger causal relation with returns. In addition, Musk is likely to use positive words in his tweets, and reversal effects exist in the relationship between Bitcoin prices and the optimism presented by Tesla's CEO. However, we did not find evidence to support linkage between Musk's sentiments and Bitcoin volatility. Our results are also robust when using a different cryptocurrency, i.e., Ether this paper extends the existing literature about the mechanisms of social media content generated by influential accounts on the Bitcoin market.

The impact of COVID-19 on the stock market crash risk in China.

This study investigates the impact of the COVID-19 pandemic on the stock market crash risk in China. For this purpose, we first estimated the conditional skewness of the return distribution from a GARCH with skewness (GARCH-S) model as the proxy for the equity market crash risk of the Shanghai Stock Exchange. We then constructed a fear index for COVID-19 using data from the Baidu Index. Based on the findings, conditional skewness reacts negatively to daily growth in total confirmed cases, indicating that the pandemic increases stock market crash risk. Moreover, the fear sentiment exacerbates such risk, especially with regard to the impact of COVID-19. In other words, when the fear sentiment is high, the stock market crash risk is more strongly affected by the pandemic. Our evidence is robust for the number of daily deaths and global cases.

Feverish sentiment and global equity markets during the COVID-19 pandemic.

This paper proposes a new approach to estimating investor sentiments and their implications for the global financial markets. Contextualising the COVID-19 pandemic, we draw on the six behavioural indicators (media coverage, fake news, panic, sentiment, media hype and infodemic) of the 17 largest economies and data from 1 st January 2020 to 3 rd February 2021. Our key findings, obtained using a time-varying parameter-vector auto-regression (TVP-VAR) model, indicate the total and net connectedness for the new index, entitled 'feverish sentiment'. This index provides us insight into economies that send or receive the sentiment shocks. The construction of the network structures indicates that the United Kingdom, China, the United States and Germany became the epicentres of the sentimental shocks that were transmitted to other economies. Furthermore, we also explore the predictive power of the newly constructed index on stock returns and volatility. It turns out that investor sentiment positively (negatively) predicts the stock volatility (return) at the onset of COVID-19. This is the first study of its kind to assess international feverish sentiments by proposing a novel approach and its impacts on the equity market. Based on empirical findings, the study also offers some policy directions to mitigate the fear and panic during the pandemic.

The nexus between black and digital gold: evidence from US markets.

In the context of the debate on cryptocurrencies as the 'digital gold', this study explores the nexus between the Bitcoin and US oil returns by employing a rich set of parametric and non-parametric approaches. We examine the dependence structure of the US oil market and Bitcoin through Clayton copulas, normal copulas, and Gumbel copulas. Copulas help us to test the volatility of these dependence structures through left-tailed, right-tailed or normal distributions. We collected daily data from 5 February 2014 to 24 January 2019 on Bitcoin prices and oil prices. The data on bitcoin prices were extracted from coinmarketcap.com. The US oil prices were collected from the Federal Reserve Economic Data source. Maximum pseudo-likelihood estimation was applied to the dataset and showed that the US oil returns and Bitcoin are highly vulnerable to tail risks. The multiplier bootstrap-based goodness-of-fit test as well as Kendal plots also suggest left-tail dependence, and this adds to the robustness of the results. The stationary bootstrap test for the partial cross-quantilogram indicates which quantile in the left tail has a statistically significant relationship between Bitcoin and US oil returns. The study has crucial implications in terms of portfolio diversification using cryptocurrencies and oil-based hedging instruments.

Carbon emissions determinants and forecasting: Evidence from G6 countries.

We examine the explanatory and forecasting power of economic growth, financial development, trade openness and FDI for CO2 emissions in major developed economies within the context of the debate on curbing CO2 emissions Post-Paris Agreement (COP21). Using data from G-6 countries from 1978 to 2014 and employing a set of empirical approaches, we find weak evidence of the Environmental Kuznets Curve, while economic growth, capital market expansion, and trade openness are found to be major drivers of carbon emissions. Carbon emissions are also weakly and negatively affected by stock market capitalization and FDI. Moreover, the forecasting performance is quite good, particularly by augmenting the model with energy consumption and oil prices. With respect to climate commitments, our empirical findings reveal important policy implications.

Preventing crash in stock market: The role of economic policy uncertainty during COVID-19.

This paper investigates the impact of economic policy uncertainty (EPU) on the crash risk of US stock market during the COVID-19 pandemic. To this end, we use the GARCH-S (GARCH with skewness) model to estimate daily skewness as a proxy for the stock market crash risk. The empirical results show the significantly negative correlation between EPU and stock market crash risk, indicating the aggravation of EPU increase the crash risk. Moreover, the negative correlation gets stronger after the global COVID-19 outbreak, which shows the crash risk of the US stock market will be more affected by EPU during the epidemic.

Did Congress trade ahead? Considering the reaction of US industries to COVID-19.

During the ongoing COVID-19 pandemic in the US, there has been considerable media attention regarding several US legislators who traded stocks in late January through February 2020. The concern is that these legislators traded in anticipation of COVID-19 having a major impact on the financial markets, while publicly suggesting otherwise. We consider whether these legislator trades were in a time window, and of a nature, that would be consistent with trading ahead of the market. Towards this end, we assess the reactions of US industries to sudden COVID-related news announcements, concomitantly with an analysis of levels of investor attention to COVID. Results suggest that, at an industry-level, for legislator trading to be "ahead of the market" it needed to have been done prior to February 26, and involving the 15 industries we identify as having abnormal returns, especially medical and pharmaceutical products (positive); restaurants, hotels, and motels (negative); as well as services and utilities. These criteria are met by many of the legislator trades. Our results help to both parameterize concerns about this case of legislator trading; as well as provide insight into the reactions and expectations of investors toward COVID-19.

Asymmetric correlation and hedging effectiveness of gold & cryptocurrencies: From pre-industrial to the 4th industrial revolution✰.

This paper examines the long-run and short-run asymmetric effects of gold and cryptocurrency returns on the Thai stock market. Employing daily data on gold prices from 2000 to 2019 and on cryptocurrency (Bitcoin) from 2013 to 2019 in a linear and non-linear Autoregressive Distributed Lag (ARDL) framework, we investigate and contrast the hedging effectiveness of gold and bitcoins for equities. This study also evaluates whether hedging potential of gold or cryptocurrency remains equally strong in bearish and bullish conditions of the stock market. Our key findings on stock and gold returns reveal that the effects of gold on the stock market are asymmetric in most of the cases. Negative asymmetry is more likely to occur regardless of stock market conditions. On the other hand, there is very limited evidence showing the meaningful effect of cryptocurrency. The robustness of the ARDL bounds test of co-integration provides evidence for a strong long-run relationship in all cases. Contrary to the existing literature, our results suggest that neither gold nor cryptocurrency acts as a good instrument for hedging in the stock market. Correlations between stock/gold and stock/cryptocurrency pairs are found to be positive in most cases. Our findings imply that adding gold or cryptocurrency to a stock portfolio does not enhance its risk-adjusted return.

Does culture matter social distancing under the COVID-19 pandemic?

This paper is the first to examine the role of the cultural dimension in practising social distancing across the world. By drawing the data from the Google COVID-19 community mobility reports and the Hofstede cultural factors for 58 countries over the period from 16 February to 29 March 2020, we find that countries with higher 'Uncertainty Avoidance Index' predict the lower proportion of people gathering in public such as retail and recreation, grocery and pharmacy, parks, transit stations, workplaces. However, we do not find any predictive factor in having a relationship with the percentage of citizens staying in their residential areas. Our results are robust by adding the control variable as the wealth status, GDP per capita. Hence, this paper suggests some effective communications to contain the COVID-19 pandemic by emphasizing the role of uncertainties.

This time is indeed different: A study on global market reactions to public health crisis.

This paper studies the differences in stock market reactions to the same kind of disease-related news by analyzing abnormal returns of global stock markets during Public Health Risk Emergency of International Concern (PHEIC) announcements. Drawing the data from 26 stock market indices over the period from 22 April 2008 to 12 March 2020, we compare stock market reactions to all six PHEIC announcements made by the World Health Organization since 2009. Although the PHEIC announcements can be categorized as the same type of event, we found no consistent patterns in market reactions. The markets did not show significant reactions in a 30-day event window, which suggests a relatively low economic impact of the diseases on a global scale during this time, except for Covid-19. Among all diseases included in our study, only Covid-19 had a significant negative effect on stock markets at least lasting 30 days.

Data for understanding the risk perception of COVID-19 from Vietnamese sample.

This data article describes the risk perception of COVID-190 from 391 Vietnamese respondents aged from 15 to 47 years. These data have been used in Huynh (2020). These data include the socioeconomics, media attention, and risk perception of COVID-19 in Vietnam through a survey conducted on February 1, 2020. In addition, our data might serve as a reference source for further in-depth surveys to understand the risk perception and social media communication across countries.