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The COVID-19 pandemic has brought significant challenges to healthcare systems worldwide, prompting governments to allocate substantial resources toward public health spendings (PHS). However, the uncertainties surrounding the pandemic have raised questions about the effectiveness and sustainability of such expenditures. This research analyzes the nonlinear link between pandemic uncertainty (PNU) and PHS in countries with highest PNU (USA, India, France, Germany, UK, Saudi Arabia, South Korea, Indonesia, Japan, and China). Previous studies have employed panel data methodologies to establish consistent findings regarding the relationship between pandemics and health spendings, regardless of the fact that several countries have not autonomously recognized this connection. In contrast, this current research adopts a distinctive tool called "quantile-on-quantile," which enables the examination of time series dependency within each economy, providing both international and country-specific perspectives on the relationship between the variables. The estimations indicate that PNU leads to an increase in PHS in the vast majority of economies chosen by us, focusing on definite segments of the data distribution. Moreover, the data demonstrates that there are differences in the asymmetry between the variables across various nations. This underscores the need for policymakers to take careful deliberation when formulating policies related to health spendings and addressing the challenges posed by pandemic uncertainty.

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Uncertainties have grown around the world during the last few decades. Pandemic uncertainty has a substantial impact on economic activities, which may have a big influence on energy consumption. The goal of this investigation is to appraise the asymmetric influence of pandemic uncertainty on nonrenewable and renewable energy consumption in the top 10 energy consumer economies of the European Union (Germany, Poland, Spain, Netherlands, France, Italy, Belgium, Sweden, Czech Republic, and Finland). Previously, panel data approaches were utilized to obtain reliable outcomes on the pandemic-energy consumption nexus, regardless of the fact that various nations did not autonomously exhibit similar relationship. This investigation, on the other hand, implements a special technique "Quantile-on-Quantile" that supports us to appraise time-series interdependence in each economy by providing international yet nation-specific perceptions of the connection among the variables. Estimates show that pandemic uncertainty reduces both nonrenewable and renewable energy consumption in most selected nations at stated quantiles of the data distribution. Nonrenewable energy consumption is much more influenced by pandemic uncertainty than renewable energy consumption. Furthermore, the rank of asymmetries across our variables differentiates by the economy, emphasizing the need for decisionmakers to pay much attention to pandemics-related uncertainty and the energy sector.

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This research intends to evaluate the asymmetric relationship between pandemic uncertainty and public health expenditures in selected European Union nations (Germany, France, Sweden, Belgium, Austria, Netherlands, Denmark, Spain, Finland, and Portugal). Earlier studies used panel data methodologies to get consistent results about the pandemic-health expenditures nexus, irrespective of the reality that numerous economies did not identify such a link independently. By contrast, the present research utilizes a unique technique, quantile-on-quantile, that explores time-series dependency in every nation by offering worldwide yet country-related insight into the linkage between the variables. Estimations reveal that pandemic uncertainty increases public health expenditures in most of the selected economies at specified quantiles of data. Additionally, the data indicate that the level of asymmetries among our variables varies by country, stressing the significance of policymakers paying special attention while executing policies concerning health expenditures and pandemic uncertainty.

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Backgrounds: COVID-19 is difficult to end in a short time and people are still facing huge uncertainties. Since people's lives are gradually returning to normal, the sense of control and intolerance of uncertainty, which were mainly focused by past studies, are not specific to COVID-19 and will be more influenced by some factors unrelated to the pandemic. Therefore, they may be difficult to accurately reflect the individuals' perceptions of uncertainty. Besides, past research just after the outbreak mainly investigated people in high levels of uncertainty, we don't know the impact of uncertainties on individuals' psychological states when people gradually recovered their sense of control. To solve these problems, we proposed the concept of "pandemic uncertainty" and investigated its impact on people's daily lives. Methods: During October 20, 2021 to October 22, 2021, this study obtained data about uncertainty, depression, positive attitude, pandemic preventive behavior intentions, personality, and social support from 530 subjects using convenient sampling. The subjects were all college students from the Dalian University of Technology and Dalian Vocational and Technical College. According to the distribution of uncertainty, we divided the dataset into high and low groups. Subsequently, by using uncertainty as the independent variable, the grouping variable as the moderating variable, and other variables as the control variables, the moderating effects were analyzed for depression, positive attitude, and pandemic preventive behavior intentions, respectively. Results: The results showed that the grouping variable significantly moderate the influence of uncertainty on positive attitude and pandemic preventive behavior intentions but had no significant effect on depression. Simple slope analysis revealed that high grouping uncertainty significantly and positively predicted positive attitude and pandemic preventive behavior intentions, while low grouping effects were not significant. Conclusion: These results reveal a nonlinear effect of pandemic uncertainty on the pandemic preventive behavior intentions and positive life attitudes and enlighten us about the nonlinear relationship of psychological characteristics during a pandemic.

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This study aims to examine the impact of the world pandemic uncertainty index on the German stock market index (DAX index) for the 1996Q1 to 2020Q3 period while controlling real effective exchange rate, industrial production index, and consumer price index. The present study performs the Fourier Augmented Dickey-Fulle Unit Root, Fourier Engle-Granger Cointegration, Bayer-Hanck Cointegration, and Markov switching regression tests. The outcomes disclose that there is a long-run cointegration association between the stock market index and world pandemic uncertainty index, real effective exchange rate, industrial production index, and consumer price index in Germany, indicating that the combination of these factors significantly affects the German stock market index in the long-run. Moreover, in both high and low volatile regimes, the world pandemic uncertainty index and real effective exchange rate negatively affect the German stock market index while industrial production and consumer price indices impact positively.

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Uncertainty is an overarching aspect of life that is particularly pertinent to the present COVID-19 pandemic crisis; as seen by the pandemic's rapid worldwide spread, the nature and level of uncertainty have possibly increased due to the possible disconnects across national borders. The entire economy, especially the tourism industry, has been dramatically impacted by COVID-19. In the current study, we explore the impact of economic policy uncertainty (EPU) and pandemic uncertainty (PU) on inbound international tourism by using data gathered from Italy, Spain, and the United States for the years 1995-2021. Using the Quantile on Quantile (QQ) approach, the study confirms that EPU and PU negatively affected inbound tourism in all states. Wavelet-based Granger causality further reveals bi-directional causality running from EPU to inbound tourism and unidirectional causality from PU to inbound tourism in the long run. The overall findings show that COVID-19 has had a strong negative effect on tourism. So resilient skills are required to restore a sustainable tourism industry.

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Since the outbreak of the COVID-19 pandemic, a growing body of literature has focused on the impact of the uncertainty of the world pandemic (WPU) on commodity prices. Using the quarterly data from the first quarter of 2008 to the second quarter of 2020, we run the TVP-SVAR-SV model to study the time-varying impact of WPU on China's commodity prices. Specifically, we select minerals, non-ferrous metals, energy and steel commodities for a categorical comparison and measure the impact of WPU accordingly. The findings are as follows. First, WPU has a significant time-varying impact on China's commodity prices, and the short-term effect is greater than the long-term effect. Second, compared with the global financial crisis in the fourth quarter of 2008 and China's stock market crash in the second quarter of 2015, WPU had a greatest impact on Chinese commodity prices during the COVID-19 pandemic event in the fourth quarter of 2019. Third, significant differences exist in the impact of WPU on the four major commodity prices. Among them, WPU has the largest time-varying impact on the price of minerals but the smallest time-varying impact on that of steel.

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The recent COVD-19 pandemic has been a major shock, affecting various macroeconomic indicators, including the environmental quality. The question of how the pandemics-related uncertainty will affect the environment is of paramount importance. The study analyzes the asymmetric impact of pandemic uncertainty on CO2 emissions in top-10 polluted economies (China, USA, India, Russia, Germany, Japan, Iran, South Korea, Indonesia, and Saudi Arabia). Taking panel data from 1996 to 2018, a unique technique, 'Quantile-on-Quantile (QQ)', is employed. CO2 emissions are used as an indicator of environmental quality. The outcomes define how the quantiles of pandemic uncertainty impact the quantiles of carbon emissions asymmetrically by providing an effective paradigm for comprehending the overall dependence framework. The outcomes reveal that pandemic uncertainty promotes environmental quality by lowering CO2 emissions in our sample countries at various quantiles. However, Japan shows mixed findings. The effect of PUN on CO2 is substantially larger in India, Germany, and South Korea and lower in Russia and Saudi Arabia. Furthermore, the magnitude of asymmetry in the pandemic uncertainty-CO2 emissions association differs by economy, emphasizing that government must pay particular caution and prudence when adopting pandemics-related uncertainty and environmental quality policies.

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The COVID-19 pandemic provides a once-in-a-lifetime opportunity to learn more about how businesses are affected by and adapt to large-scale, unforeseen shocks. Our research examines the worries of a sample of Italian publicly traded companies about the spread of COVID-19. The information was gathered from a dataset employing text-based estimates of the main concerns listed companies have about the development of COVID-19 and other pandemic diseases. These data can be used to determine whether companies stand to earn or lose money because of a particular outbreak. We concentrate on the data for Italy, which allows us to quantify which of the sample's Italian enterprises are more exposed and thus affected, the severity of risk perception, and the firm's attitude towards​ the shock exposure. We attempt to explain how firm perceptions of the COVID-19 crisis are correlated with various types of indicators related to economic and financial status, such as financial position (total debt exposure and short-term exposure), ROI, and ROE during the COVID-19 crisis, i.e. the main firms' responses to such a large shock.

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It is well known that pandemic-related uncertainty affects various macroeconomic indicators, including environmental quality. Due to pandemic outbreaks, the reduction in economic activities affects the environmental quality in many economies. The study explores the impact of pandemic uncertainty on environmental quality in East-Asia and Pacific countries. Most past research use only CO2 emissions, which is an inappropriate measurement of environmental quality. Besides CO2 emissions, we have utilized other pollutants like N2O and CH4 emissions along with ecological footprint. The traditional econometric approaches ignore cross-sectional dependence and heterogeneity and give biased outcomes. Hence, we have employed a new method, "Dynamic Common Correlated Effects (DCCE)," which can excellently deal with the problems mentioned above. The short-run and long-run DCCE estimations show a negative and significant influence of pandemic uncertainty on ecological footprint, CO2 and CH4 emissions in whole and lower-income group of East-Asia and Pacific region. Moreover, pandemic uncertainty has a negative relationship with all indicators of environmental quality in higher-income economies. The study provides a unique opportunity to examine how pandemic uncertainty through anthropogenic activities affects environmental quality and serves as a significant resource for policymakers in planning and estimating the effectiveness of environmental quality measures. It is necessary to carry out sustainable environmental policies in East-Asia and Pacific region according to the vulnerabilities and resilience to global pandemic uncertainty.

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Fiscal policy implications become an important tool to soften the negative consequences of the COVID-19 pandemic. Given this backdrop, this paper analyses the drivers of corporate tax rates during the COVID-19 pandemic (i.e., in 2020 and 2021). The results from 113 advanced and developing economies show that a higher level of the COVID-19-related uncertainty is positively associated with the corporate tax rates. Similarly, the country size (measured by total population) increases the corporate tax rates. Per capita income is negatively related to the corporate tax rates, but this evidence is insufficient to consider different estimation techniques. The paper also discusses potential fiscal policy implications for the driving mechanism of corporate tax rates for the post-COVID-19 era.

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The COVID-19 pandemic has affected various macroeconomic indicators. Given this backdrop, this research investigates the effects of the pandemics-related uncertainty on household consumption. For this purpose, we construct a simple theoretical model to study the effects of the pandemics-related uncertainty on household consumption. To estimate the theoretical model, we consider the panel dataset of 138 countries for the period from 1996 to 2017. We also use the Pandemic Uncertainty Index to measure the pandemics-related uncertainty. The theoretical model and the empirical findings from the Feasible Generalized Least Squares (FGLS) estimations indicate that the gross fixed capital formation, government consumption, balance of trade, and the Pandemic Uncertainty Index negatively affect household consumption. The results are also valid in the panel dataset of 42 high-income economies and the remaining 96 emerging economies.

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Fiscal support measures have different implications for public finances in the near term and beyond the COVID-19 pandemic. For this purpose, this paper examines the determinants of governments' fiscal support in response to the COVID-19 pandemic. The empirical analysis is based on the cross-sectional data estimations from 129 developed and developing countries. The estimation results indicate that a higher level of uncertainty related to COVID-19 (measured by the World Pandemic Uncertainty Indices) is positively related to fiscal support. Besides, countries with a higher total population and population over 65 years and older provide higher fiscal support. These results are valid when considering the developed countries separately. Policy implications for public finances during the COVID-19 pandemic are also discussed.

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