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2.
Sci Rep ; 11(1): 21783, 2021 11 08.
Article in English | MEDLINE | ID: covidwho-1758307

ABSTRACT

To reduce the spread and the effect of the COVID-19 global pandemic, non-pharmaceutical interventions have been adopted on multiple occasions by governments. In particular lockdown policies, i.e., generalized mobility restrictions, have been employed to fight the first wave of the pandemic. We analyze data reflecting mobility levels over time in Italy before, during and after the national lockdown, in order to assess some direct and indirect effects. By applying methodologies based on percolation and network science approaches, we find that the typical network characteristics, while very revealing, do not tell the whole story. In particular, the Italian mobility network during lockdown has been damaged much more than node- and edge-level metrics indicate. Additionally, many of the main Provinces of Italy are affected by the lockdown in a surprisingly similar fashion, despite their geographical and economic dissimilarity. Based on our findings we offer an approach to estimate unavailable high-resolution economic dimensions, such as real time Province-level GDP, based on easily measurable mobility information.


Subject(s)
COVID-19/epidemiology , Communicable Disease Control/legislation & jurisprudence , Physical Distancing , Algorithms , COVID-19/therapy , Geography , Humans , Italy/epidemiology , Models, Economic , Public Health Informatics , Travel
3.
PLoS One ; 17(2): e0264016, 2022.
Article in English | MEDLINE | ID: covidwho-1704081

ABSTRACT

A key factor for business management is the assessment of the financial situation of companies. Nowadays, it is essential to monitor the liquidity crisis, which is closely linked to corporate crises. The aim of the paper is to analyse a selected sector of the economy from the perspective of the corporate crisis and to identify the factors of crisis. More than 2000 engineering companies in Slovakia were analysed during the period from 2015 to 2019 with the aim of analysing financial results, especially in the area of financial forecast for the future. In the analysis, statistical testing of the significance of relationships using the Spearman correlation coefficient, the significance of differences by the power of t-test, regression and clustering were used. A significant part of the paper is the analysis of selected indicators of the company's crisis-Altman's Z score and the IN05 index. The results indicate that engineering companies in Slovakia are achieving good results and their financial situation is improving within the years between 2015-2019. The results can also be used as a starting point for research concerning the impact of COVID-19 in this area. In the context of corporate crisis management, engineering companies behave in the same way but it is necessary to monitor individual factors that can detect a corporate crisis. Possible measures would thus lead to the stabilization of financial results and long-term sustainable positive prospects for companies in the future.


Subject(s)
Engineering/organization & administration , Industry/organization & administration , Models, Economic , COVID-19/economics , COVID-19/epidemiology , Engineering/economics , Industry/economics , Pandemics/economics , Slovakia
4.
PLoS One ; 17(2): e0259869, 2022.
Article in English | MEDLINE | ID: covidwho-1690763

ABSTRACT

The purpose of our study is to figure out the transitions of the cryptocurrency market due to the outbreak of COVID-19 through network analysis, and we studied the complexity of the market from different perspectives. To construct a cryptocurrency network, we first apply a mutual information method to the daily log return values of 102 digital currencies from January 1, 2019, to December 31, 2020, and also apply a correlation coefficient method for comparison. Based on these two methods, we construct networks by applying the minimum spanning tree and the planar maximally filtered graph. Furthermore, we study the statistical and topological properties of these networks. Numerical results demonstrate that the degree distribution follows the power-law and the graphs after the COVID-19 outbreak have noticeable differences in network measurements compared to before. Moreover, the results of graphs constructed by each method are different in topological and statistical properties and the network's behavior. In particular, during the post-COVID-19 period, it can be seen that Ethereum and Qtum are the most influential cryptocurrencies in both methods. Our results provide insight and expectations for investors in terms of sharing information about cryptocurrencies amid the uncertainty posed by the COVID-19 pandemic.


Subject(s)
COVID-19/epidemiology , Investments/trends , Models, Economic , COVID-19/economics , Humans , Information Dissemination , Investments/statistics & numerical data , Pandemics/economics , Uncertainty
6.
Sci Rep ; 12(1): 1052, 2022 01 20.
Article in English | MEDLINE | ID: covidwho-1642020

ABSTRACT

The COVID-19 pandemic provides a major opportunity to study fishing effort dynamics and to assess the response of the industry to standard and remedial actions. Knowing a fishing fleet's capacity to compensate for effort reduction (i.e., its resilience) allows differentiating governmental regulations by fleet, i.e., imposing stronger restrictions on the more resilient and weaker restrictions on the less resilient. In the present research, the response of the main fishing fleets of the Adriatic Sea to fishing hour reduction from 2015 to 2020 was measured. Fleet activity per gear type was inferred from monthly Automatic Identification System data. Pattern recognition techniques were applied to study the fishing effort trends and barycentres by gear. The beneficial effects of the lockdowns on Adriatic endangered, threatened and protected (ETP) species were also estimated. Finally, fleet effort series were examined through a stock assessment model to demonstrate that every Adriatic fishing fleet generally behaves like a stock subject to significant stress, which was particularly highlighted by the pandemic. Our findings lend support to the notion that the Adriatic fleets can be compared to predators with medium-high resilience and a generally strong impact on ETP species.


Subject(s)
COVID-19 , Fisheries/economics , Models, Economic , Pandemics/economics , Quarantine/economics , SARS-CoV-2 , COVID-19/economics , COVID-19/epidemiology , COVID-19/prevention & control , Humans
7.
PLoS One ; 16(12): e0261118, 2021.
Article in English | MEDLINE | ID: covidwho-1597647

ABSTRACT

Rice market efficiency is important for food security in countries where rice is a staple. We assess the impact of rice quality on rice prices, food security, and environmental sustainability in Bangladesh. We find that while price varies as expected for most quality attributes, it is unaffected by a broken percentage below 24.9 percent. This reveals a potential inefficiency, considering the average 5 percent broken rate observed in the market. An increase in the broken rate of milled rice within the limits supported by our findings can, ceteris paribus, increase rice rations by 4.66 million a year, or conversely, yield the current number of rice rations using 170.79 thousand fewer hectares and cutting emissions by 1.48 million metric tons of CO2 equivalent. Thus, producing rice based on quality assessment can improve food security and its sustainability.


Subject(s)
Food Security , Oryza/physiology , Sustainable Development , Bangladesh , Commerce , Food Security/economics , Models, Economic , Statistics as Topic
8.
PLoS One ; 16(12): e0261615, 2021.
Article in English | MEDLINE | ID: covidwho-1592216

ABSTRACT

One of the most pressing challenges facing food systems in Africa is ensuring availability of a healthy and sustainable diet to 2.4 billion people by 2050. The continent has struggled with development challenges, particularly chronic food insecurity and pervasive poverty. In Africa's food systems, fish and other aquatic foods play a multifaceted role in generating income, and providing a critical source of essential micronutrients. To date, there are no estimates of investment and potential returns for domestic fish production in Africa. To contribute to policy debates about the future of fish in Africa, we applied the International Model for Policy Analysis of Agriculture Commodities and Trade (IMPACT) to explore two Pan-African scenarios for fish sector growth: a business-as-usual (BAU) scenario and a high-growth scenario for capture fisheries and aquaculture with accompanying strong gross domestic product growth (HIGH). Post-model analysis was used to estimate employment and aquaculture investment requirements for the sector in Africa. Africa's fish sector is estimated to support 20.7 million jobs in 2030, and 21.6 million by 2050 under the BAU. Approximately 2.6 people will be employed indirectly along fisheries and aquaculture value chains for every person directly employed in the fish production stage. Under the HIGH scenario, total employment in Africa's fish food system will reach 58.0 million jobs, representing 2.4% of total projected population in Africa by 2050. Aquaculture production value is estimated to achieve US$ 3.3 billion and US$ 20.4 billion per year under the BAU and HIGH scenarios by 2050, respectively. Farm-gate investment costs for the three key inputs (fish feeds, farm labor, and fish seed) to achieve the aquaculture volumes projected by 2050 are estimated at US$ 1.8 billion per year under the BAU and US$ 11.6 billion per year under the HIGH scenario. Sustained investments are critical to sustain capture fisheries and support aquaculture growth for food system transformation towards healthier diets.


Subject(s)
Fisheries/economics , Africa , Commerce/economics , Commerce/legislation & jurisprudence , Employment , Fisheries/legislation & jurisprudence , Humans , Investments , Models, Economic
10.
PLoS One ; 16(11): e0259362, 2021.
Article in English | MEDLINE | ID: covidwho-1504217

ABSTRACT

We analyze whether and to what extent strategies employed by governments to fight the COVID-19 pandemic made a difference for GDP growth developments in 2020. Based on the strength and speed with which governments imposed non-pharmaceutical interventions (NPIs) when confronted with waves of infections we distinguish between countries pursuing an elimination strategy and countries following a suppression / mitigation strategy. For a sample of 44 countries fixed effect panel regression results show that NPI changes conducted by elimination strategy countries had a less severe effect on GDP growth than NPI changes in suppression / mitigation strategy countries: strategy matters. However, this result is sensitive to the countries identified as "elimination countries" and to the sample composition. Moreover, we find that exogenous country characteristics drive the choice of strategy. At the same time our results show that countries successfully applying the elimination strategy achieved better health outcomes than their peers without having to accept lower growth.


Subject(s)
COVID-19/epidemiology , COVID-19/prevention & control , Federal Government , Government , Humans , Internationality , Models, Economic , Pandemics , Physical Distancing , Public Policy , Quarantine , Regression Analysis , Risk , SARS-CoV-2
11.
PLoS One ; 16(11): e0259451, 2021.
Article in English | MEDLINE | ID: covidwho-1504036

ABSTRACT

INTRODUCTION: Our aim was to examine attitudes of the general population towards reasonableness of these costs, as well as the degree to which these costs are shared across society (solidarity financing) and to determine the factors associated with them. METHOD: Repeated cross-sectional data from a nationally representative online-survey. More precisely, data from wave 8 (21-22 April 2020) and wave 16 (7-8 July 2020) were used (in wave 8: analytical sample with n = 976, average age was 47.0 years (SD: 15.3 years), ranging from 18 to 74 years, 51.8% female; in wave 16: analytical sample with n = 978, average age was 46.1 years (SD: 15.9 years), ranging from 18 to 74 years, 50.9% female). After a short introduction emphasizing considerable economic costs associated with the measures against the spread of the coronavirus, individuals were asked to rate the following statements (outcome measures), in each case from 1 = strongly disagree to 7 = strongly agree: "These economic costs are currently reasonable in relation to the objective pursued" (reasonableness of costs), "These economic costs should be borne jointly by all citizens and depending on income" (solidarity financing). RESULTS: In wave 8 (wave 16 in parentheses), the average rating for the attitude towards reasonableness of costs was 4.3, SD: 1.8 (wave 16, average: 4.2, SD: 1.8) and the average rating for the attitude towards solidarity financing was 3.7, SD: 1.9 (wave 16, average: 3.3, SD: 2.0). In wave 8, more positive attitudes towards the reasonableness of costs and solidarity financing were associated with being male, higher education, not being in a partnership/being unmarried, higher affect regarding COVID-19 and higher presumed severity with respect to COVID-19. Furthermore, more positive attitudes towards the reasonableness of costs were associated with having a migration background. More positive attitudes towards solidarity financing was associated with higher age groups. Mainly similar findings were observed in wave 16. DISCUSSION: Agreement with reasonableness of costs of preventative measures as well as solidarity financing was moderately high. Knowledge of these attitudes is important to ensure social cohesion during the fight against COVID-19.


Subject(s)
COVID-19/epidemiology , COVID-19/therapy , Adolescent , Adult , Aged , Attitude to Health , COVID-19/economics , Cross-Sectional Studies , Female , Germany/epidemiology , Health Knowledge, Attitudes, Practice , Humans , Male , Middle Aged , Models, Economic , Perception , Regression Analysis , SARS-CoV-2 , Surveys and Questionnaires , Young Adult
12.
PLoS One ; 16(10): e0258309, 2021.
Article in English | MEDLINE | ID: covidwho-1477533

ABSTRACT

Examining the spread of macroeconomic phenomena between countries has become increasingly popular after the 2008 economic crisis, but the recent COVID-19 pandemic rendered this issue much more relevant as it shed more light on the risks arising from strongly interconnected economies. This paper intends to extend previous studies in this line by examining the relationship between trade openness and business cycle synchronization. It extends the scope of previous analyses in three areas. First, we use a Granger-causality approach to identify synchronization. Second, trade is broken down to the sector level and third, we distinguish between upstream and downstream connections. These developments allow for a directed approach in the analysis. We use conditional logit regressions to estimate the effect of trade openness on the probability of shock-transmission. The results presented in this study contribute to the literature in two ways. First, in addition to revealing a positive effect of aggregate two-way trade on shock-contagion, it also points out that this overall effect hides diverse behavior in specific trading sectors as well as upstream and downstream channels. Second, while some sectors are not significant channels of shock-transmission in either directions, upstream channels seem to be important in agriculture while downstream channels dominate machinery and other manufactures. Also, there are sectors (chemicals and related products) trade in which affects shock-transmission negatively.


Subject(s)
COVID-19/economics , COVID-19/epidemiology , Economic Development , Models, Economic , Pandemics/economics , SARS-CoV-2 , Humans
13.
Sci Rep ; 11(1): 20451, 2021 10 14.
Article in English | MEDLINE | ID: covidwho-1469991

ABSTRACT

This research measures the epidemiological and economic impact of COVID-19 spread in the US under different mitigation scenarios, comprising of non-pharmaceutical interventions. A detailed disease model of COVID-19 is combined with a model of the US economy to estimate the direct impact of labor supply shock to each sector arising from morbidity, mortality, and lockdown, as well as the indirect impact caused by the interdependencies between sectors. During a lockdown, estimates of jobs that are workable from home in each sector are used to modify the shock to labor supply. Results show trade-offs between economic losses, and lives saved and infections averted are non-linear in compliance to social distancing and the duration of the lockdown. Sectors that are worst hit are not the labor-intensive sectors such as the Agriculture sector and the Construction sector, but the ones with high valued jobs such as the Professional Services, even after the teleworkability of jobs is accounted for. Additionally, the findings show that a low compliance to interventions can be overcome by a longer shutdown period and vice versa to arrive at similar epidemiological impact but their net effect on economic loss depends on the interplay between the marginal gains from averting infections and deaths, versus the marginal loss from having healthy workers stay at home during the shutdown.


Subject(s)
COVID-19/epidemiology , Agriculture/economics , COVID-19/economics , COVID-19/prevention & control , Communicable Disease Control , Construction Industry/economics , Employment , Humans , Industry/economics , Models, Economic , SARS-CoV-2/isolation & purification , Teleworking , United States/epidemiology
14.
Sci Rep ; 11(1): 19960, 2021 10 07.
Article in English | MEDLINE | ID: covidwho-1462021

ABSTRACT

Coping with the outbreak of Coronavirus disease 2019 (COVID-19), many countries have implemented public-health measures and movement restrictions to prevent the spread of the virus. However, the strict mobility control also brought about production stagnation and market disruption, resulting in a severe worldwide economic crisis. Quantifying the economic stagnation and predicting post-pandemic recovery are imperative issues. Besides, it is significant to examine how the impact of COVID-19 on economic activities varied with industries. As a reflection of enterprises' production output, high-frequency electricity-consumption data is an intuitive and effective tool for evaluating the economic impact of COVID-19 on different industries. In this paper, we quantify and compare economic impacts on the electricity consumption of different industries in eastern China. In order to address this problem, we conduct causal analysis using a difference-in-difference (DID) estimation model to analyze the effects of multi-phase public-health measures. Our model employs the electricity-consumption data ranging from 2019 to 2020 of 96 counties in the Eastern China region, which covers three main economic sectors and their 53 sub-sectors. The results indicate that electricity demand of all industries (other than information transfer industry) rebounded after the initial shock, and is back to pre-pandemic trends after easing the control measures at the end of May 2020. Emergency response, the combination of all countermeasures to COVID-19 in a certain period, affected all industries, and the higher level of emergency response with stricter movement control resulted in a greater decrease in electricity consumption and production. The pandemic outbreak has a negative-lag effect on industries, and there is greater resilience in industries that are less dependent on human mobility for economic production and activities.


Subject(s)
COVID-19 , Industry , COVID-19/epidemiology , China/epidemiology , Electricity , Humans , Models, Economic , Pandemics , Power Plants , Public Health
15.
PLoS Med ; 18(10): e1003815, 2021 10.
Article in English | MEDLINE | ID: covidwho-1450724

ABSTRACT

BACKGROUND: Multiple Coronavirus Disease 2019 (COVID-19) vaccines appear to be safe and efficacious, but only high-income countries have the resources to procure sufficient vaccine doses for most of their eligible populations. The World Health Organization has published guidelines for vaccine prioritisation, but most vaccine impact projections have focused on high-income countries, and few incorporate economic considerations. To address this evidence gap, we projected the health and economic impact of different vaccination scenarios in Sindh Province, Pakistan (population: 48 million). METHODS AND FINDINGS: We fitted a compartmental transmission model to COVID-19 cases and deaths in Sindh from 30 April to 15 September 2020. We then projected cases, deaths, and hospitalisation outcomes over 10 years under different vaccine scenarios. Finally, we combined these projections with a detailed economic model to estimate incremental costs (from healthcare and partial societal perspectives), disability-adjusted life years (DALYs), and incremental cost-effectiveness ratio (ICER) for each scenario. We project that 1 year of vaccine distribution, at delivery rates consistent with COVAX projections, using an infection-blocking vaccine at $3/dose with 70% efficacy and 2.5-year duration of protection is likely to avert around 0.9 (95% credible interval (CrI): 0.9, 1.0) million cases, 10.1 (95% CrI: 10.1, 10.3) thousand deaths, and 70.1 (95% CrI: 69.9, 70.6) thousand DALYs, with an ICER of $27.9 per DALY averted from the health system perspective. Under a broad range of alternative scenarios, we find that initially prioritising the older (65+) population generally prevents more deaths. However, unprioritised distribution has almost the same cost-effectiveness when considering all outcomes, and both prioritised and unprioritised programmes can be cost-effective for low per-dose costs. High vaccine prices ($10/dose), however, may not be cost-effective, depending on the specifics of vaccine performance, distribution programme, and future pandemic trends. The principal drivers of the health outcomes are the fitted values for the overall transmission scaling parameter and disease natural history parameters from other studies, particularly age-specific probabilities of infection and symptomatic disease, as well as social contact rates. Other parameters are investigated in sensitivity analyses. This study is limited by model approximations, available data, and future uncertainty. Because the model is a single-population compartmental model, detailed impacts of nonpharmaceutical interventions (NPIs) such as household isolation cannot be practically represented or evaluated in combination with vaccine programmes. Similarly, the model cannot consider prioritising groups like healthcare or other essential workers. The model is only fitted to the reported case and death data, which are incomplete and not disaggregated by, e.g., age. Finally, because the future impact and implementation cost of NPIs are uncertain, how these would interact with vaccination remains an open question. CONCLUSIONS: COVID-19 vaccination can have a considerable health impact and is likely to be cost-effective if more optimistic vaccine scenarios apply. Preventing severe disease is an important contributor to this impact. However, the advantage of prioritising older, high-risk populations is smaller in generally younger populations. This reduction is especially true in populations with more past transmission, and if the vaccine is likely to further impede transmission rather than just disease. Those conditions are typical of many low- and middle-income countries.


Subject(s)
COVID-19 Vaccines/economics , COVID-19/economics , Cost-Benefit Analysis/methods , Health Impact Assessment/economics , Models, Economic , Vaccination/economics , COVID-19/epidemiology , COVID-19/prevention & control , COVID-19 Vaccines/administration & dosage , Cost-Benefit Analysis/trends , Health Impact Assessment/methods , Health Impact Assessment/trends , Humans , Pakistan/epidemiology , Quality-Adjusted Life Years , Vaccination/trends
17.
PLoS One ; 16(9): e0257572, 2021.
Article in English | MEDLINE | ID: covidwho-1435616

ABSTRACT

The purpose of this paper is to analyse the global Sales and Operations Planning (S&OP) process and investigate the steps to support consolidated business planning in worldwide operations and large-scale supply chains. The paper conducts a case study at a multinational manufacturing company applying an abductive approach. It combines the deductive logic from theory and the inductive logic from field observation in an attempt to elaborate further on theory on global S&OP. The analysis is structured and guided by a novel framework for global S&OP, which is developed based on the theoretical background and the case study findings. The research findings characterise the S&OP process for global operations and identify challenges related to the need to synchronise the subsidiaries' S&OP efforts worldwide to deal with different contingencies of these subsidiaries, and to manage and analyse a large amount of information gathered. The research reveals how the subsidiaries' performance is analysed by top executives along the global S&OP process, feeding strategic initiatives in the organisation and identifying business opportunities like benchmarking among subsidiaries, synergies with other management practices, and global gains. This paper offers a novel investigation of the global steps on S&OP in a real-life setting, offering a well-documented characterisation of the process that goes beyond the traditional local approach. Moreover, it is the first study to reveal challenges and expected outcomes of such a global perspective for S&OP. The theoretical advancements of S&OP research offered herein aid scholars, opening avenues for middle-range theorising, highlighting the cross-disciplinary nature of the domain, and discussing the use of concepts from related disciplines like Economics, Psychology, and Information Systems. The research findings can also assist executives, especially from multinational manufacturers, in their efforts to consolidate global planning.


Subject(s)
Commerce/organization & administration , Internationality , Models, Economic
18.
J Infect Dis ; 224(6): 938-948, 2021 09 17.
Article in English | MEDLINE | ID: covidwho-1429242

ABSTRACT

BACKGROUND: With multiple coronavirus disease 2019 (COVID-19) vaccines available, understanding the epidemiologic, clinical, and economic value of increasing coverage levels and expediting vaccination is important. METHODS: We developed a computational model (transmission and age-stratified clinical and economics outcome model) representing the United States population, COVID-19 coronavirus spread (February 2020-December 2022), and vaccination to determine the impact of increasing coverage and expediting time to achieve coverage. RESULTS: When achieving a given vaccination coverage in 270 days (70% vaccine efficacy), every 1% increase in coverage can avert an average of 876 800 (217 000-2 398 000) cases, varying with the number of people already vaccinated. For example, each 1% increase between 40% and 50% coverage can prevent 1.5 million cases, 56 240 hospitalizations, and 6660 deaths; gain 77 590 quality-adjusted life-years (QALYs); and save $602.8 million in direct medical costs and $1.3 billion in productivity losses. Expediting to 180 days could save an additional 5.8 million cases, 215 790 hospitalizations, 26 370 deaths, 206 520 QALYs, $3.5 billion in direct medical costs, and $4.3 billion in productivity losses. CONCLUSIONS: Our study quantifies the potential value of decreasing vaccine hesitancy and increasing vaccination coverage and how this value may decrease with the time it takes to achieve coverage, emphasizing the need to reach high coverage levels as soon as possible, especially before the fall/winter.


Subject(s)
COVID-19 Vaccines/economics , Cost-Benefit Analysis , Vaccination/economics , COVID-19/prevention & control , COVID-19 Vaccines/administration & dosage , Humans , Models, Economic , SARS-CoV-2 , United States , Vaccination/statistics & numerical data
19.
Int J Environ Res Public Health ; 18(18)2021 Sep 10.
Article in English | MEDLINE | ID: covidwho-1409556

ABSTRACT

Lessons learnt from the initial stages of the COVID-19 outbreak indicate the need for a more coordinated economic and public health response. While social distancing has been shown to be effective as a non-pharmaceutical intervention (NPI) measure to mitigate the spread of COVID-19, the economic costs have been substantial. Insights combining epidemiological and economic data provide new theoretical predictions that can be used to better understand the health economy tradeoffs. This literature review aims to elucidate perspectives to assist policy implementation related to the management of the ongoing and impending outbreaks regarding the Health Economic Dilemma (HED). This review unveiled the need for information-based decision-support systems which will combine pandemic spread modelling and control, with economic models. It is expected that the current review will not only support policy makers but will also provide researchers on the development of related decision-support-systems with comprehensive information on the various aspects of the HED.


Subject(s)
COVID-19 , Humans , Models, Economic , Pandemics , Public Health , SARS-CoV-2
20.
PLoS One ; 16(9): e0256879, 2021.
Article in English | MEDLINE | ID: covidwho-1403303

ABSTRACT

This paper uses event study based on the Generalized Autoregressive Conditional Heteroscedasticity (GARCH) model to study the impact of the COVID-19 outbreak on China's financial market. It finds that the pandemic had an overall significant and negative impact on the stock prices of firms listed on SSE, SZSE and ChiNext. However, such impact appeared to be heterogeneous across industries, affecting listed firms in industries such as pharmaceutical and telecommunications positively, but those in services industries such as accommodation, catering, and commercial services negatively. Apparently, a crisis for some had been an opportunity for others. In addition, this paper seeks to understand the micro mechanism behind the heterogeneity of pandemic shock from the perspective of firms' financial position. It finds that listed firms with higher debt level were hit harder, whereas those with more net cash flow had displayed higher resilience against the blow of the pandemic. However, the opposite pattern is found among those listed on ChiNext and in industries severely devastated by the pandemic. These findings have policy implications in terms of preventing systemic financial risks and facilitating recovery during pandemic-induced economic downturns. It also helps investor adjust investment strategies, hedge against risks, and secure gains when the market conditions in general are unfavorable.


Subject(s)
COVID-19/economics , COVID-19/epidemiology , Models, Economic , China/epidemiology , Financial Management , Industry , Investments
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