The impact of the COVID-19 pandemic on business expectations

We document and evaluate how businesses are reacting to the COVID-19 crisis through August 2020. First, on net, firms see the shock (thus far) largely as a demand rather than supply shock. A greater share of firms report significant or severe disruptions to sales activity than to supply chains. We compare these measures of disruption to their expected changes in selling prices and find that, even for firms that report supply chain disruptions, they expect to lower near-term selling prices on average. We also show that firms are engaging in wage cuts and expect to trim wages further before the end of 2020. These cuts stem from firms that have been disproportionally negatively impacted by the pandemic. Second, firms (like professional forecasters) have responded to the COVID-19 pandemic by lowering their one-year-ahead inflation expectations. These responses stand in stark contrast to that of household inflation expectations (as measured by the University of Michigan or the New York Fed). Indeed, firms’ one-year-ahead inflation expectations fell precipitously (to a series low) following the onset of the pandemic, while household measures of inflation expectations jumped markedly. Third, despite the dramatic decline in firms’ near-term inflation expectations, their longer-run inflation expectations have remained relatively stable.     

Adaptive market hypothesis: The story of the stock markets and COVID-19 pandemic

Since the level of markets’ information efficiency is key to profiteering by strategic players, Shocks; such as the COVID-19 pandemic, can play a role in the nature of markets’ information efficiency. The martingale difference and conditional heteroscedasticity tests are used to evaluate the Adaptive form of market efficiency for four (4) major stock market indexes in the top four affected economies during the COVID-19 pandemic (USA, Brazil, India, and Russia). Generally, based on the martingale difference spectral test, there is no evidence of a substantial change in the levels of market efficiency for the US and Brazilian stock markets in the short, medium, and long term. However, in the long term, the Indian stock markets became more information inefficient after the coronavirus outbreak while the Russian stock markets become more information efficient. Intuitively, these affect the forecastability and predictability of these markets’ prices and/or returns. Thereby, informing the strategic and trading actions of stock investors (including arbitrageurs) towards profit optimization, portfolio asset selection, portfolio asset adjustment, etc. Similar policy implications are further discussed.     

Dynamic volatility spillovers between industries in the US stock market: Evidence from the COVID-19 pandemic and Black Monday

We examine the volatility spillovers among various industries during the COVID-19 pandemic period. We measure volatility spillovers by defining the volatility of each sector in the S&P 500 index and implement a static and rolling-window analysis following the Diebold and Yilmaz (2012) approach. We find that the pandemic enhanced volatility spillovers, which reveals the financial contagion effects on the US stock market. Second, there were sudden, large changes in the dynamic volatility spillovers on Black Monday (March 9, 2020), much of it due to the energy sector shock. These findings have important implications for portfolio managers and policymakers.     

Animal Behavior in Capital markets: Herding formation dynamics,trading volume,and the role of COVID-19 pandemic

This paper provides new evidence on herding behavior. Using daily frequency data for 336 US listed firms over a five-year period, we investigate three important elements of financial herding behavior. First, trading volume, representing market interest, as a significant variable in capital markets apart from stock prices. Second, herding dynamics since herding formation is a dynamic process. Third, the reaction of possible financial herding to exogenous events-threats, as we use the pandemic event in order to investigate a market under stress. Even though the benchmark herding model used does not provide evidence of herding behavior, our results verify the significance of the above herding elements. We also find that trading volume and positive changes in trading volume result in increased cross-sectional absolute deviation (CSAD). Most importantly, we find that herding behavior is evident during the COVID-19 pandemic confirming that investors tend to herd during major crisis periods.     

Improving resilience of the healthcare supply chain in a pandemic: Evidence from Europe during the COVID-19 crisis

The severe scarcity of critical medical supplies caused by the COVID-19 pandemic led to considerable procurement challenges in the healthcare supply chain (HCSC). As ensuring the availability of such supplies during disruptions is critical, the debate on how to increase supply chain resilience in healthcare has gained new momentum. We present empirical evidence from a multi-tier case study spanning nine European medical supplies manufacturers and hospital groups. Based on the resource dependence theory, we investigated procurement-related strategies to improve medical supplies availability. We conducted semi-structured interviews with 39 procurement and supply chain management experts and derived seven propositions on buffering and bridging approaches for managing evolving resource dependencies and thereby strengthening supply chain resilience in a pandemic. Overall, we confirm the resource dependence theory's applicability for explaining companies' mitigation measures in a pandemic disruption. We find that bridging measures within the healthcare supply base, such as offering procurement support for suppliers or leveraging long-term buyer-supplier relationships, are more effective for securing medical supplies than buffering measures. Complementing bridging with buffering, such as extended upstream procurement or resource sharing among hospitals, can lead to superior risk mitigation as capacities of the present supplier base may not suffice. Furthermore, we extend the resource dependence theory by showing that the severity of disruptions caused by a pandemic triggers new forms of buffering external to the HCSC. Both traditional and new buffering measures establish novel flows of medical supplies in the HCSC that can enable higher supply security in a pandemic.     

Modeling the lockdown relaxation protocols of the Philippine government in response to the COVID-19 pandemic: An intuitionistic fuzzy DEMATEL analysis

The COVID-19 pandemic, which started at Wuhan, has shut down world economies, prompting governments to impose drastic lockdown measures of the economy and the society. As these measures are exhausted, non-COVID-19 related issues such as those associated with the mental and physical well-being of people under lockdowns became an emerging concern. As these issues are evident, not to mention the economic downturn, governments are currently looking at designing lockdown relaxation efforts by simultaneously considering both public health and economic restart. Without documented experiences to rely on, governments are resorting to trial-and-error approach in creating a lockdown exit strategy while preventing succeeding waves of cases that may overwhelm healthcare facilities. Thus, this work pioneers the use of the decision-making trial and evaluation laboratory (DEMATEL) method with intuitionistic fuzzy (IF) sets along with the domain of public health and the emerging COVID-19 pandemic. The DEMATEL handles the intertwined causal relationships among guideline protocols for the relaxation strategy. The intuitionistic fuzzy set theory addresses the vagueness and uncertainty of human judgments in the context of the DEMATEL. A case study of the Philippine government response for the lockdown exit is presented to evaluate the applicability of the proposed method. Findings reveal that compliance of minimum public health standards, limited movement of persons, suspension of physical classes, the prohibition of mass gatherings, non-operation of category IV industries, and non-operation of hotels or similar establishments are the most crucial protocols for such strategy. These findings offer practical insights for the government to allocate resources and impose measures to ensure their implementation, as well as for developing mitigation efforts to cushion their socio-economic impacts. Policy insights and avenues for future works are also discussed.     

新冠肺炎疫情对粤港澳大湾区城市群创新网络的冲击路径及应对策略

创新对疫后经济高质量恢复至关重要,但鲜有文献分析突发事件对跨地区合作创新网络的影响路径。本文将社会网络分析的节点影响力方法应用于创新网络冲击分析,使用联合申请专利数据,研究了新冠肺炎疫情对粤港澳大湾区合作创新网络的影响路径。研究发现:创新网络中的高链接节点、高频节点、高紧密度节点和高外向度节点更容易受到冲击,冲击对于合作创新的两城市影响具有显著的不对称性,冲击通过具有中介中心属性的热点节点城市影响网络边缘城市。据此,本文建议:率先稳定和恢复高热度节点城市创新活动,提高城市之间合作创新活动恢复的协同度,加快城市群创新网络的恢复和重构,针对不同节点城市实施差异化的创新激励政策。     

COVID-19, ESG investing,and the resilience of more sustainable stocks: Evidence from European firms

Following the COVID-19 outbreak, orientation toward sustainability is a critical factor in ensuring firm survival and growth. Using a large sample of 1,204 firms in Europe during the year 2020, this study investigates how more sustainable firms fare during the pandemic compared with other firms in terms of risk–return trade-off and stock market liquidity. We also highlight the drivers of the resilience of more sustainable firms to the pandemic. Particularly, we document that higher levels of cash holdings and liquid assets in the pre-COVID period help these firms to perform and absorb the COVID-19 externalities better than other firms. Our results are robust to a host of econometric models, including GMM estimations and several measures of stock market performance. These findings contribute to the theoretical and empirical debate on the role of the sustainability as a source of corporate resilience to unexpected shocks.     

新冠疫情对湘西州小微餐饮企业的影响及应对策略研究

2020年的疫情对整个餐饮业产生巨大冲击,餐饮企业面临营业额骤降问题,企业发展陷入困境,尤其是单体规模小、资金实力薄弱的小微企业。论文通过调查与分析湘西州小微餐饮企业的发展现状,针对其发展现状提出合理对策。     

A socio-economic optimization model for blood supply chain network design during the COVID-19 pandemic: An interactive possibilistic programming approach for a real case study

In uncertain circumstances like the COVID-19 pandemic, designing an efficient Blood Supply Chain Network (BSCN) is crucial. This study tries to optimally configure a multi-echelon BSCN under uncertainty of demand, capacity, and blood disposal rates. The supply chain comprises blood donors, collection facilities, blood banks, regional hospitals, and consumption points. A novel bi-objective Mixed-Integer Linear Programming (MILP) model is suggested to formulate the problem which aims to minimize network costs and maximize job opportunities while considering the adverse effects of the pandemic. Interactive possibilistic programming is then utilized to optimally treat the problem with respect to the special conditions of the pandemic. In contrast to previous studies, we incorporated socio-economic factors and COVID-19 impact into the BSCN design. To validate the developed methodology, a real case study of a Blood Supply Chain (BSC) is analyzed, along with sensitivity analyses of the main parameters. According to the obtained results, the suggested approach can simultaneously handle the bi-objectiveness and uncertainty of the model while finding the optimal number of facilities to satisfy the uncertain demand, blood flow between supply chain echelons, network cost, and the number of jobs created.     

Evaluating the impacts of the COVID-19 pandemic on unemployment,income distribution and poverty in Turkey

In the recent World Economic Outlook, the IMF indicates that world output shrank by 3.5% in 2020. Despite all pessimistic expectations, the Turkish economy was one of the few countries to have a positive, albeit low, economic growth rate in 2020. This was, however, achieved at the expense of high social and economic costs. The present research examines the distributional costs of this economic growth during the pandemic and suggests economic measures required to control them. The empirical examination is based on generating unavailable income and living conditions for 2020 by using the results available in TurkStat’s 2017 Income and Living Conditions Survey. The actual changes in sectoral output and employment, which are available as of March 2021, are used to generate changes in the income levels of households in TurkStat’s 2017 survey. The research empirically shows that adequate fiscal support with a large scope for households and businesses is necessary to compensate for economic losses caused by the pandemic. The short-run working allowance policy appears to have been very important to improve income distribution, which might have deteriorated due to the pandemic. Direct cash support to households is considered another essential policy measure that is required to mitigate the severity of increased poverty.     

Analysis of the impact of COVID-19 pandemic on G20 stock markets

We examine the impact of the COVID-19 pandemic on G20 stock markets from multiple perspectives. To measure the impact of COVID-19 on cross-market linkages and deeply explore the dynamic evolution of risk transmission relations and paths among G20 stock markets, we statically and dynamically measure total, net, and pairwise volatility connectedness among G20 stock markets based on the DY approach by Diebold and Yilmaz (2012, 2014). The results indicate that the total volatility connectedness among G20 stock markets increases significantly during the COVID-19 crisis, moreover, the volatility connectedness display dynamic evolution characteristics during different periods of the COVID-19 pandemic. Besides, we also find that the developed markets are the main spillover transmitters while the emerging markets are the main spillover receivers. Furthermore, to capture the impact of COVID-19 on the volatility spillovers of G20 stock markets, we individually apply the spatial econometrics methods to analyze both the direct and indirect effects of COVID-19 on the stock markets’ volatility spillovers based on the “volatility spillover network matrix” innovatively constructed in this paper. The empirical results suggest that stock markets react more strongly to the COVID-19 confirmed cases and cured cases than the death cases. In general, our study offers some reference for both the investors and policymakers to understand the impact of COVID-19 on global stock markets.     

新冠疫情对我国中小企业经济状况的影响及对策分析

2020年以来,新冠疫情对我国中小企业的影响巨大。论文从收入、成本、现金流三个方面分析了疫情下我国中小企业的现状及可采取的对策,以期助力中小企业渡过难关。     

新冠疫情背景下山东省小微企业减税降费政策效应研究

新冠疫情的蔓延对国民经济造成了很大的影响,作为市场经济中重要组成部分的小微企业也为此遭遇重创,此时,其需要精确的财政政策进行疫情救援。在税务政策方面,减税降费政策属于积极财政政策的重要组成部分,应继续保持长期的减税降费趋势,同时,发挥税务部门的征管数据优势和纳税服务优势,积极助力小微企业增强生存能力,巩固未来发展的根蒂,使小微企业步入健康发展的快车道。     

Impact of COVID-19 pandemic on stock markets: Conventional vs. Islamic indices using wavelet-based multi-timescales analysis

We empirically explore the effect of the COVID-19 pandemic on Islamic and conventional stock markets from a global perspective. We also explore the co-movement between Islamic and conventional stock markets. Two comparable pairs of conventional and Islamic stock indices – Dow Jones Index and FTSE Index are considered in this study. Employing Wavelet-based multi-timescales techniques on the daily data from 21st January to 27th November 2020, our findings indicate that the pandemic creates identical volatility in both stock markets. Our findings further suggest that both markets are strongly associated and tend to co-move highly during our sample period, rebutting the decoupling hypothesis of the Islamic stock market from the conventional market. However, the Shariah screening process fails to provide immunity to Islamic stock markets against financial crises. Our findings suggest that investors should be aware that Islamic stocks' conservative features do not present a superior investment alternative, especially in economic turmoil.