This study investigates the impact of COVID-19 pandemic on the Chinese stock market in 2020. Using daily data of three industries, this study addresses the identification of abnormal stock returns as a multiple hypothesis testing problem and proposes to apply a grouped comparison procedure for better detection. By comparing the numbers of daily signals and numbers of stocks with abnormal positive and negative returns, the empirical result shows that the three industries perform differently under the pandemic. Compared to the non-grouped testing procedure, the signals found by the grouped procedure are more prominent, which is advantageous for some situations when there tends to be abnormal performance clustering at the occurrence of major event. This paper on stock return anomalies gives a new perspective on the impact of major events to the stock market, like the global outbreak disease.

This paper examines the effectiveness of four major COVID-19 social distancing policies, (i) shelter-in-place orders (SIPO), (ii) non-essential business closures, (iii) mandatory quarantine for travelers, and (iv) bans on large gatherings, on both COVID cases and COVID deaths. Results indicate that states are highly ineffective in producing the fraction of the population that does not have COVID-19 or the fraction of the population that does not die from COVID-19. We find that having any form of social distancing policies increases the fraction of the population not considered a positive COVID-19 case by 23.5 percentage points. Results also show that having any of the four major social distancing policies reduces the fraction of the population who has died of COVID-19 by 1.3 percentage points between March 1, 2020 and September 1, 2020; during the first 100 days, effectiveness would improve by 2.1 percentage points. Evidence suggests that there is no effective uniform national COVID-19 social distancing policy. Furthermore, conditional efficiency regressions after 100 days suggest that behavioral noncompliance and premature expiration of social distancing policies both negatively impact effectiveness. Partial regression plots suggest that bans on large gatherings and the closure of non-essential businesses were the two most impactful COVID-19 social distancing policies.

The world economy, and SMEs in particular, have been hit hard by the COVID-19 epidemic. SME finance issues are becoming a significant focus of policymakers and academics. This research uses private companies as a sample to analyze how COVID-19 affected SME finance. We examine critical factors such as business size, leverage, profitability, liquidity, and the influence of COVID-19. Our research shows that the pandemic has had a significant, detrimental impact on funding for small and medium-sized businesses. Small and medium-sized enterprises (SMEs) have expanded their borrowing amid falling profits and cash flow. More specifically, smaller SMEs have been hit harder than their bigger counterparts. Implications for policymakers and the owners of SMEs are substantial. Governments should help small and medium-sized enterprises by providing incentives like tax credits and loan guarantees. Owners of small and medium-sized enterprises (SMEs) should prioritize sound financial management and stability. This research sheds light on SMEs' funding difficulties in the wake of COVID-19 and highlights the need to aid such businesses as rebuild.

This paper examines the effectiveness of the monetary policies undertaken by the central bank on economic growth during COVID-19 uncertainty in case of India and Indonesia. We use an innovative framework of Growth-at-Risk as oppose to standard macroeconomic models, which can predict the growth in a much robust way particularly when an economy is facing shocks like COVID-19. The empirical results based on Growth-at-Risk model clearly reveal that effect of COVID-19 pandemic on economic growth is much adverse in comparison to actual declines. Further, this study shows the effectiveness of monetary and financial policies undertaken by the central banks of both India and Indonesia, which have actually subsided the adverse impact of COVID-19.

The enactment of COVID-19 policies in Canada falls under provincial jurisdiction. This study exploits time-series variation across four Canadian provinces to evaluate the effects of stricter COVID-19 policies on daily case counts. Employing data from this time-period allows an evaluation of the efficacy of policies independent of vaccine impacts. While both OLS and IV results offer evidence that more stringent Non-Pharmaceutical Interventions (NPIs) can reduce daily case counts within a short time-period, IV estimates are larger in magnitude. Hence, studies that fail to control for simultaneity bias might produce confounded estimates of the efficacy of NPIs. However, IV estimates should be treated as correlations given the possibility of other unobserved determinants of COVID-19 spread and mismeasurement of daily cases. With respect to specific policies, mandatory mask usage in indoor spaces and restrictions on business operations are significantly associated with lower daily cases. We also test the efficacy of different forecasting models. Our results suggest that Gradient Boosted Regression Trees (GBRT) and Seasonal Autoregressive-Integrated Moving Average (SARIMA) models produce more accurate short-run forecasts relative to Vector Auto Regressive (VAR), and Susceptible-Infected-Removed (SIR) epidemiology models. Forecasts from SIR models are also inferior to results from basic OLS regressions. However, predictions from models that are unable to correct for endogeneity bias should be treated with caution.

This paper examines the responses of credit and business cycle to various policy actions of the Government of Indonesia during the COVID-19 crisis. Specifically, the paper addresses two key questions (1) How do the credit and business cycle behave during the COVID-19 crisis in Indonesia? (2) Do the central bank and government policy responses effectively stabilize the credit and business cycle? Using the concordance Index and DCC-GARCH methodology, we found that the COVID-19 crisis increased Indonesia's credit and business cycle co-movements. Similarly, using the mixed data sampling regression technique, our findings suggest fiscal policy measures and government support help the business cycle revival during the COVID-19 pandemic. However, the monetary policy transmission is weak during the pandemic.

We investigate the lending implication of the PMK 70, a low-cost funding for lending scheme introduced by the Indonesian Ministry of Finance in June 2020 as a response to the COVID-19 pandemic. We utilize a quasi-experimental design of difference-in-differences to compare the lending of participating state-owned banks to the non-participating banks before and after the introduction of the policy. Overall, our findings suggest that the policy encourages participating banks to lend more than the non-participating banks during the distress period. We find no evidence that the low-cost funds lead to a moral hazard of liquidity hoarding for the state-owned banks. Our findings also highlight the important role of unconventional policies in alleviating banks' risk aversion during downturns.

This study examines the effect of a means-tested COVID-19 stimulus payment, which was provided by the Seoul Metropolitan Government in South Korea, on consumer spending. The Seoul government issued a one-off payment in the spring of 2020 for residents in the city living below the national median income. We use daily card transaction data aggregated by users' age, income and location of residence, and apply a difference-in-differences approach to assess the effect of the stimulus payment. We compare consumption for the treatment (eligible for the payment) and control (ineligible but with a similar level of income) groups before and after the implementation of the payment. The results show that the payment increased consumer spending for the treatment group by about 12%. Recipients of the means-tested payment have a marginal propensity of consumption at no less than 59%, larger than that found for a universal emergency payment made by the Korean government and similar stimulus checks in other countries.

Environmental, social, and governance (ESG) practices can play a crucial role in promoting green recovery by fostering sustainable and responsible economic growth. Based on a novel dataset of Japanese listed companies from January 2016 to December 2021, this study examines the effect of corporate (ESG) performance on the Japanese stock market during the COVID-19 pandemic. We contribute additional evidence to the literature by exploring the unique role of ESG factors that affect stock markets during economic downturns. The results of the study show a positive association between corporate ESG performance and stock returns during the COVID-19 period. Furthermore, we demonstrate that strong ESG performance contributed to enhanced stock market stability and increased market liquidity in Japan during the COVID-19 pandemic. These results provide a rationale for implementing supportive measures and regulations that encourage companies to adopt and disclose robust ESG practices. By doing so, they can contribute to the stability and liquidity of the stock market and fostering sustainable economic growth.

The world is adjusting to regain control over direct economic impacts of the COVID-19 pandemic. This adjustment is occurring whilst global collective action is also gearing up to tackle climate change, avert biodiversity collapse and redress unsustainable growth practices that featured in pre-Covid era global economic activity for decades. COVID-19 pandemic experience since December 2019 has been a period of pronounced anxiety and inspiration. Despite the angst of widespread calamity, and the loss of over six million lives, a coordinated global effort helped contain the impacts well short of initial predictions. Progress toward eliminating poverty, the central goal in rural economic transformation, has been set back by decades. The strength in organising - through social and business processes - marked the resilience endured. The recovery is patchy and uneven across individual nations, and the medium-term prospects remain contingent on the efficacy of funding essential human services and clear market bottlenecks. Bridging capacity constraints across the rural-urban continuum also remain a need to ease the regulatory burden as the world tackles widespread externalities of the past to create new growth opportunities. In this special issue, emerging and established academics from the Asian region and beyond, draw insights from research and analysis on the challenges facing policy makers, businesses, and households in raising living standards and inspiring the pursuit of individual and social affluence during these uncertain but opportune times.

This paper examines frequency dynamic spillovers in return and volatility and the hedging ability of Green Bonds, gold, silver, oil, the US dollar index, and volatility index against downside US stock prices before and during the COVID-19 pandemic outbreak and for the short and long run. To do so, we use the Diebold and Yilmaz (2014), the TVP-VAR model, and the frequency spillover index by Baruník and Křehlík (2018). We show that the short-term volatility spillovers dominate their long-term counterparts. Green Bond is net transmitters of spillovers in the system at the short term and net receivers at the long term. S&P500 and silver (USDX and oil) are net transmitters (receivers) of short- and long-term spillovers. Gold and VIX are net receivers of short-term spillovers and net transmitters of long-term spillovers. COVID-19 crisis has more effects on the short-term spillover, which reaches its highest level early 2020. COVID-19 and time horizons lead the direction and the magnitude of spillovers. The Quantile-on-Quantile regression analysis shows significant nonlinear relationships between markets under study. More interestingly, we show that green bonds and gold are safe haven assets for US equity investors during COVID-19. On the other hand, a mixed portfolio offers higher diversification benefits. Finally, hedging effectiveness is dependent on COVID-19 and time horizon.

The COVID-19 pandemic has caused turmoil in every aspect of life and may be prevalent for years. Therefore, this study aimed to determine whether the pandemic reflects oil prices in China. We utilized a model to simulate and examine the energy, economic, and environmental effects of COVID-19, which affects a wide range of industries and households. The impact of the pandemic is considered in terms of customer expectations and factor input changes. Based on these changes, we find that factor input changes are the primary cause of the economic recession. We further find a parallel relationship between CO2 emissions and economic downturn. In addition, a reduction in transportation has significantly influenced the Gross Domestic product (GDP), which plunged during the pandemic period by 0.49%. Transportation negatively influences industrial production, railway sector, and air transportation by 10.17%, 1.76%, and 1.53%, respectively. Based on these findings, this study proposes important policy implications.

After the pandemic, China's fiscal and monetary authorities implemented macroeconomic restructuring measures to combat the pandemic. Using a difference-in-difference model based on data collected during the COVID-19 phase, this study attempted to determine the economic recovery in China using the pandemic means for economic growth and energy consumption in other economies. A 0.21 percent increase in the western region's economic growth is comparable to a 0.15 percent increase in the growth of the southern central and northern regions during the pandemic period. Accordingly, we found evidence of actual provincial spillover effects in the clustering of high- and poor-performing regions. The impact of China's economic resurgence beyond the pandemic phase plays an important role in expanding power consumption in different regions. Since headwinds hamper economic development to aggregate output, fiscal policy is the sole option for maintaining pollution levels while simultaneously improving household well-being in terms of demand and employment.

This paper extends the existing empirical literature by investigating whether the COVID-19 crisis has strengthened the dynamic relationships between oil price and exchange rate. We find significant breaks in the relationships wherein a common break is detected around the COVID-19 outbreak period. Of note, the interactions between the two markets intensified since the outbreak of the COVID-19 pandemic. Overall, our findings imply that the investors and policymakers are taking stock of the valuable information from the unanticipated occurrence of the COVID-19 pandemic. Thus, diversification in the form of portfolio switches towards foreign currency-denominated assets may be effective in the case of a depreciation of the domestic currency.

Numerous studies have explored the impact of the Covid-19 pandemic on firms' financial performance, but the link between such performance and employment has rarely been estimated rigorously. Using the ASEAN-5 firms' data from Q1-2018 to Q3-2021, this study shows how the pandemic affects firms' revenue, cost, profitability, and employment heterogeneously across countries. It is argued that while revenue losses are the main challenge, widespread and prolonged restrictions in some countries have created extra complications in idle inventories and labour. In response to the revenue shocks, firms reduce their employment with an elasticity of around 0.10, indicating that a 10 per cent revenue decline is associated with a 1 per cent headcount reduction in the short run. A further examination using event analyses reveals that the path of labour adjustment is diverse across countries and industries, reflecting the degree of pandemic severity and countries' structural issues.

We study the labour market impact of the confinement measures implemented in Spain to halt the spread of the COVID-19 pandemic in the first quarter of 2020. We use data from 8108 municipalities to quantify the impact of the shutdown of non-essential activity on local unemployment. Ordinary least squares regressions show that an increment of 10 percentage points in the share of firms performing non-essential activities increased the unemployment-population ratio by between 0.032 and 0.148 percentage points. We only find this positive effect in municipalities with more than 2395 inhabitants. The lockdown explains between 25% and 40% of the observed increase in the unemployment within these municipalities. We also look at the impact of the lockdown by gender and age, and find that the impact of these closures was felt relatively more by males and workers above 45 years old.

The outbreak and ongoing evolution of the COVID-19 pandemic have dramatically impacted economic development and CO emissions. China is under simultaneous pressure to recover from the outbreak and meet its carbon reduction targets, and the government is endeavouring to stimulate economic recovery through fiscal and monetary policies. This paper uses a computable general equilibrium model to measure the impact on China's economic recovery and carbon emissions by incorporating the pandemic shock and related economic recovery policies of loan prime rate (LPR) and value-added tax (VAT) reduction. The study found that COVID-19 led to a simultaneous shock on China's supply and demand sides in which GDP dropped by 2.62% and carbon emissions fell by 2.53%, compared to the period prior to COVID-19. Although the LPR and VAT reduction effectively mitigated economic loss, the combined LPR and VAT reduction had a more substantial effect on boosting GDP than the single policies. The VAT cut expands production and was used to overcome supply-side shocks, while lowering LPR mitigates the damage of demand-side shocks. Compared to the VAT reduction policy, reduced LPR has smaller carbon emissions per unit of GDP output. Consequently, we recommend that the government concentrate on a combination of policies to navigate pandemic shocks, as the two economic stimulus policies are confirmed to complement one another in terms of strengths and shortcomings.

In this paper we study the structural robustness of the Italian business system, using the Covid-19 pandemic as an exogenous event to test it. To this aim, we use the ROC (Receiver Operating Characteristics) methodology, quite new for economics, to classify Italian firms according to their economic solidity, obtaining a taxonomy based on a wide set of characteristics. Our results show that the number of "Solid" firms is less than one-fifth of all Italian enterprises but they represent the lion's share in terms of employment and value added. "Fragile" and "At Risk" firms, albeit much less relevant for the creation of value added, account for over one-third of total employment, so they may be a worrisome issue for policymakers. Solidity conditions have clearly both a size and sector-related dimension: At Risk and Fragile conditions prevail among firms of smaller economic size (a broad definition of firm size) and among those operating in Construction and Other services. Finally, we find that factors such as firms' performance, and internal and external organization, although significant, play a less relevant role than economic size and digitalization/innovation in determining Italian firms' resilience to exogenous shocks such as the Covid-19 one.

This paper explores the relationship between the stock markets of emerging and developed economies and the fear triggered by the COVID-19 pandemic crisis in a period that spans from mid-January 2020 to mid-February 2022. The potential relations are analyzed in terms of Granger causality and dynamic correlation, both from the view of raw undecomposed returns and different time-frequency decompositions derived from a previous wavelet transform screening approach. Overall, our Granger and dynamic correlation results suggest that changes in panic indexes resulting from the COVID-19 pandemic do not have a significant relation with the raw stock market returns, but the reverse occurs in terms of time-frequency decompositions. Correlation analysis also indicates that all countries have a quite similar pattern of phase transitions, with certain stages preceded by a hump and others by a valley, i.e., they exhibit both positive and negative correlations. Despite a gradual reduction in media coverage, both causal relationships and correlations between financial markets and panic indexes held in 2021 and early 2022.

Following a national lockdown in response to the Covid-19 pandemic, state governments in Germany published lists of "essential" occupations that were considered necessary to maintain basic services such as health care, social care, food production and transport. This paper examines working conditions in these essential occupations and identifies clusters of similar jobs. Differences across clusters are highlighted using detailed data on job characteristics including working conditions, tasks and educational requirements. Two clusters with favourable or average working conditions account for more than three-quarters of jobs in essential occupations. Another two clusters, comprising 20% of jobs in essential occupations, are associated with unfavourable working conditions such as low pay, job insecurity, poor prospects for advancement and low autonomy. These latter clusters exhibit high shares of migrants. An Oaxaca-Blinder decomposition is used to investigate which individual characteristics explain why migrants are more likely to have unfavourable working conditions. The results suggest that lacking proficiency in the host-country language is the main barrier to improving migrants' working conditions.

Investigations into the effects of the pandemic on small businesses remain insufficient, and the role of Fintech during a pandemic has rarely been investigated. Using novel firm-level data on registration and various identifications of fixed-effect and difference-in-difference models, we exploit the interactive effect of lockdown policies and Fintech on the creation of small businesses. First, both lockdown policies and Fintech have negative impacts on new firm creation in the manufacturing sector. Second, lengthier pandemics induce more severe destruction of firm registrations. Third, an alternative indicator shows that Fintech is not intensively related to labor demand in the manufacturing sector. Policy implications call for higher match efficiency between the manufacturing sector and financial resources to reduce financial misallocation to a large extent.