Assessing the nexus between COVID-19 pandemic-driven economic crisis and economic policy: lesson learned and challenges.

This study examines China's budgetary policy during the COVID-19 pandemic as a result of China's insufficient ability to deal with a new crisis when the epidemic struck in March 2020 and as a result of the economic crisis that began in China in March 2020. In order to better comprehend China's economic status during COVID-19, the study relies on secondary data. The fiscal response of emerging market economies like India is less than in advanced economies. However, it is generally considered to be in line with the average for emerging market economies. As a result of the Disaster Management authority imposing a rigorous lockdown, unemployment rose, the trade cycle was interrupted, and manufacturing and service activities were affected. According to the study's findings, China's economic policies, namely its fiscal policy, responded in the years leading up to 2019 by increasing health expenditure, income transfer, welfare payments, subsidies, and reducing short-term unemployment. As a result of the COVID-19 pandemic, China's government has adopted a number of measures to minimize the damage to the economy. This article also focuses on China's numerous budgetary actions with COVID-19.

Studying corporate liquidity and regulatory responses for economic recovery in COVID-19 crises.

Many enterprises across the European Union (EU) have been hampered by the massive spread of COVID-19. It has severely impacted revenues and financial flows, potentially leading to an increase in corporate insolvency. This study investigates the influence of this new coronavirus on the solvency status of businesses in EU Member States. Several stress scenarios were constructed for non-financial listed enterprises. The results reveal a gradual surge in the possibility of default, a rise in loan repayment, and coverage being refused. According to our findings, the solvency profiles of all firms are deteriorating. Industries, such as mining, mass production, and retail, are the most susceptible to a drop in sales income and market capitalization. Before COVID-19, previous research had looked at policy options for maintaining solvency. Our data imply that a tax delay is adequate if there is a slight deterioration in the economic outlook. There should be hybrid assistance through loans and equity for even a slight deterioration in the state of an economy. This research will benefit policymakers, corporate executives, and creditors.

Dynamical analysis of coronavirus disease with crowding effect, and vaccination: a study of third strain.

Countries affected by the coronavirus epidemic have reported many infected cases and deaths based on world health statistics. The crowding factor, which we named "crowding effects," plays a significant role in spreading the diseases. However, the introduction of vaccines marks a turning point in the rate of spread of coronavirus infections. Modeling both effects is vastly essential as it directly impacts the overall population of the studied region. To determine the peak of the infection curve by considering the third strain, we develop a mathematical model (susceptible-infected-vaccinated-recovered) with reported cases from August 01, 2021, till August 29, 2021. The nonlinear incidence rate with the inclusion of both effects is the best approach to analyze the dynamics. The model's positivity, boundedness, existence, uniqueness, and stability (local and global) are addressed with the help of a reproduction number. In addition, the strength number and second derivative Lyapunov analysis are examined, and the model was found to be asymptotically stable. The suggested parameters efficiently control the active cases of the third strain in Pakistan. It was shown that a systematic vaccination program regulates the infection rate. However, the crowding effect reduces the impact of vaccination. The present results show that the model can be applied to other countries' data to predict the infection rate.

A blessing in disguise: new insights on the effect of COVID-19 on the carbon emission, climate change, and sustainable environment.

COVID-19, declared by the World Health Organization (WHO) to be a pandemic, has affected greenhouse gas emissions and contributed to the uncertainty of environmental activities. This study demonstrates the effect of lockdowns, the number of new confirmed cases, and the number of newly confirmed deaths due to COVID-19 on CO2 emissions. The data series used are for the UK from 23 March 2020 to 31 December 2020 and for Spain from 14 March 2020 to 31 December 2020. This research adopted the Augmented Dickey-Fuller (ADF) test for a stationarity check of the data series, the Johansen cointegration test for determining cointegration among variables, and the vector error correction model (VEC) Granger causality test for directional cause and effect between exogenous and endogenous variables. The VEC model shows a bidirectional relationship between CO2 emissions and lockdown and a unidirectional relationship with newly confirmed cases and deaths for the UK. The results of Spain confirmed the unidirectional relationship of CO2 emissions, lockdown, new confirmed cases, and deaths. The Granger causality test reconfirms the relationship of variables except for newly confirmed deaths for the UK and newly confirmed cases for Spain. Conclusively, the pandemic breakout reduced the emission of CO2. The directional relation of variables supported the short-run relationship of CO2 emissions with newly confirmed cases and deaths, while a long- and short-run relationship was shown with lockdown. The directional and relational behavior of lockdown potentially linked the CO2 emissions with daily life activities.

Modeling the relationship between carbon emissions and environmental sustainability during COVID-19: a new evidence from asymmetric ARDL cointegration approach.

The study aims to examine the CO2 emissions by considering the implication of COVID-19 under strict lockdown in India. The nonlinear (asymmetric) relationship is investigated between CO2 emission and COVID-19 with its specific determinants. The positive and negative asymmetries of COVID-19 determinants are also captured by using econometric techniques. The daily data series of CO2 emission, new confirmed cases, confirmed deaths, and lockdown as dummy variables from January 30, 2020, to December 1, 2020, for India is analyzed by employing the nonlinear autoregressive distributed lag model. This research revealed a significant nonlinear relationship between CO2 emission and COVID-19. The bound test and asymmetric coefficients are confirmed by the variables' long- and short-run relationships. The dynamic multiplier graphs present that India's strict lockdown due to the rapid increase in COVID-19 patients significantly reduces toxic gas emissions, especially CO2 emissions. This asymmetric relationship has been proficiently declared that unhealthy public routine, extra traffic, and unhygienic gases released in the air become the reason for environmental destruction. The lockdown is practically imposed for specific periods and reasons, contributing to reducing toxic emissions, but it is not a permanent solution for environmental sustainability. The government of India, policymakers, and environmentalists should make people aware of unhealthy and environmentally envying activities and policies and long-term applicable strategies should be designed to upgrade the environment's quality.

The Investor Psychology and Stock Market Behavior During the Initial Era of COVID-19: A Study of China, Japan, and the United States.

A highly transmittable and pathogenic viral infection, COVID-19, has dramatically changed the world with a tragically large number of human lives being lost. The epidemic has created psychological resilience and unbearable psychological pressure among patients and health professionals. The objective of this study is to analyze investor psychology and stock market behavior during COVID-19. The psychological behavior of investors, whether positive or negative, toward the stock market can change the picture of the economy. This research explores Shanghai, Nikkei 225, and Dow Jones stock markets from January 20, 2020, to April 27, 2020, by employing principal component analysis. The results showed that investor psychology was negatively related to three selected stock markets under psychological resilience and pandemic pressure. The negative emotions and pessimism urge investors to cease financial investment in the stock market, and consequently, the stock market returns decreased. In a deadly pandemic, the masses were more concerned about their lives and livelihood and less about wealth and leisure. This research contributes to the literature gap of investors' psychological behavior during a pandemic outbreak. The study suggests that policy-makers should design a plan to fight against COVID-19. The government should manage the health sector's budget to overcome future crises.