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To comprehensively assess the economic impacts from China's tourism industry caused by COVID-19 in 2020, this article develops a new multiplier calculation and decomposition method based on the social accounting matrix (SAM). This method is suitable for situations in which multiple industries are simultaneously exposed to external shocks, especially comprehensive industries like tourism. By categorizing all industries as being in either the tourism sector or the nontourism sector, we calculate the output, value-added and employment impacts of COVID-19, then decompose them into four levels: direct, indirect, spillover and reverberation effects. There are some subindustries of both the tourism and nontourism sectors that were severely affected. Compared with the calculation results from the traditional SAM method, the method developed in this paper identifies quite different industrial structures, although there is almost no difference in the total impacts. [ABSTRACT FROM AUTHOR]

As China's economy and the U.S. economy have shown a definite interaction, there is considerable interest in studying the correlation between the Chinese stock market and the US financial markets. This paper uses an Asymmetric Dynamic Conditional Correlation (ADCC)-GARCH to investigate the correlation between the Shanghai Composite Index (SHCI) and the U.S. financial markets, including SP500, NASDAQ, and US dollar indexes. The empirical results show that the time-varying daily and the lag-one correlation between China and the US stock markets have different performances during global events and national events. Compared with the complicated effect of negative events on the correlation of the stock market, SHCI and USD are negatively correlated with higher negative correlation during the global negative events. In addition, we found Chinese investors are more contagious to the news than American investors, indicating that the Chinese government's policy are more indicated to Chinese investors. Finally, some policy suggestions are provided, and are beneficial to risk prevention and control, and investment. [ABSTRACT FROM AUTHOR]

Purpose: This study aims at the sudden outbreak of COVID-19, which had an unprecedented negative impact on the Chinese economy, with firms being affected most. Firms differ in terms of their specific internal environment, shaping their ability to respond to the outbreak, so the impact may also vary. Design/methodology/approach: In this paper Chinese listed firms are selected as samples to investigate the mediating effect of prior digital technology on the relationship between R&D (research and development) investment (funds and staff) and firm performance during the epidemic. Firm size and diversification are then introduced as moderating variables to explore the conditional mediating effect of digital technology. Findings: The results indicate that the higher the firm's prior R&D investment, the higher its digital technology level, and thus the stronger its resistance to the epidemic. Moreover, compared with large-scale firms, small-scale firms have the advantage of strategic flexibility to technological changes, which can help them accumulate experience from R&D activities for digital transformation, thus attenuating the negative impact of the COVID-19 on firm performance. Finally, the results also show that digital technology mediates more strongly between R&D investment and firm performance in diversified firms than in centralized firms. Originality/value: The study builds a mediation model to reveal the process mechanism through which R&D investment affects firm performance via digital technology. Firm size and diversification are then innovatively introduced as situational factors to build the moderated mediation model, which opens up a new perspective for understanding the effect of firm internal factors on the relationship between R&D investment, digital transformation and firm performance. [ABSTRACT FROM AUTHOR]

Copper in the international market has been priced by copper futures contracts from the London Metal Exchange (LME) and the New York Commodity Exchange (COMEX). Copper prices initially showed a downward trend until March 2020, but after the outbreak of COVID-19, they continued to rise and reached a record high in May 2021. The rise in copper demand also stimulated the continuous growth of copper production. However, a significant amount of smelting flue gas is produced in the copper smelting process. The main component of the flue gas is SO2 and other acid gases, which pollute the environmental atmosphere. At the same time, due to the Chinese government's effective control of the pandemic, China's economy continued to grow. Therefore, as one of the world's largest copper consumers and producers, China's futures market has attracted attention for its influence on copper pricing and the pollution caused by copper smelting. In this paper, we used the grey entropy method to compare the influence of copper prices on the three futures markets and changes in China's air pollution in recent years. Our results show that before the pandemic, the influence of the LME futures copper price was the same as the COMEX but greater than the Shanghai Futures Exchange (SHFE). After the outbreak of the pandemic, the influence of the SHFE copper futures price significantly improved and slightly exceeded the LME and COMEX. This result echoes our finding that SO2 has caused serious air pollution in recent years. [ABSTRACT FROM AUTHOR]

This paper analyses the interaction between the novel coronavirus pandemic (COVID-19), unemployment rate, stock market, consumer confidence index (CCI), and economic policy uncertainty (EPU) index in China within a time-frequency framework. We compare the changes in economic indicators during the global financial crisis (GFC) and study the different impacts of the two events on China's economy. An unprecedented impact of COVID-19 shocks on the unemployment rate, CCI, EPU index, and stock market volatility over the low frequency bands is uncovered by applying the coherence wavelet method to China monthly data. The COVID-19 effect on the stock market volatility and the EPU index is substantially higher than on the unemployment rate and the CCI. On the contrary, the GFC's impact on the unemployment rate is much greater than that on the EPU index and CCI. Additionally, the impact of the GFC on the economy is more cyclical in the long-term, while the COVID-19 pandemic is a short-term shock with a relatively short oscillation cycle. This study concludes that the economic impact of COVID-19 will not spread into a financial crisis for China and believe that the COVID-19 pandemic is more of a health event than an economic crisis for Chinese economy. [ABSTRACT FROM AUTHOR]

The outbreak of COVID-19 at the beginning of 2020 had a significant impact on China's economy, society, and citizens; it also had a negative impact on the development of the construction industry. In particular, small and medium-sized construction enterprises with low ability to withstand risk have been strongly impacted, aggravating a crisis of survival among these firms. The focus of this study is to analyze the impact of COVID-19 on the growth of small and medium-sized construction companies. Based on the characteristics of small and medium-sized construction enterprises, this paper establishes a growth evaluation index and builds a growth evaluation model based on factor analysis. Twenty-three construction enterprises listed on small and medium-sized enterprises board are selected as samples, and the quarterly data of 2019 and 2020 are used for empirical analysis. The results show that the epidemic has had a high short-term impact on construction enterprises, and the total output value of the construction industry in the first quarter of 2020 was 16% lower than that in the same period of last year. In the long run, the impact of the epidemic on the growth of small and medium-sized construction enterprises has been limited. In the first quarter of 2020, the growth score of enterprises decreased by only 1.95% year-over-year, and it was essentially flat in the second and third quarters. The epidemic has had little influence on solvency, tangible resources or intangible resources but a high short term influence on profitability, capital expansion and market expectations. The long-term impact is small; It is conducive to the improvement of enterprise operation ability. Finally, to both address the influence of the COVID-19 on small and medium-sized construction enterprises and to realize their transformation and upgrading, targeted suggestions are offered at the policy and enterprise levels. The results will help to understand the impact of the epidemic on the growth of construction enterprises, and provide decision support for the healthy and orderly development of the follow-up construction industry. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic lockdowns led to a sharp drop in socio-economic activities in China in 2020, including reductions in fossil fuel use, industry productions, and traffic volumes. China's economy suffered a serious negative effect from COVID-19. However, there is a "positive effect" on CO 2 emissions reduction. Here, for the first time, this paper constructs a new model named "Weighted Multi-regional Hypothetical Extraction Method (WMHEM)" based on a multiregional input-output model. It not only solves the problems of traditional HEM methods such as improper use of assumptions, excessive reliance on industry intermediate input, but also accurately reflects the impact of external shocks on the inter-industry linkages. By using the monthly economic data of each provinces in China during COVID-19 (except Hong Kong，Macao and Taiwan) an the latest Multi-regional input-output tables, the "economic negative effect" and "CO 2 emission positive effect" under COVID-19 in China are measured. Results show that COVID-19 lockdown was estimated to have reduced China's CO 2 emissions substantially between January and March in 2020, with the largest reductions in February. With the spread of coronavirus controlled, China's CO 2 emissions rebounded in April. In addition, key emission reduction sectors and key development encouraged sectors are selected by combining "economic negative effect" and "CO 2 emission positive effect" during COVID-19. Therefore, policies recommendations are put forward based on forward and backward linkages respectively which are from two ends of the supply chain to turn pandemic-related CO 2 emissions declines into firm climate action. • COVID-19 has negative effects on economy, but positive effects on CO 2 emissions. • A new model is used to measure economic and CO 2 emission effects during COVID-19. • Hubei had the biggest economic and CO 2 emission effects on China due to COVID-19. • Economic and CO 2 emission effects of COVID-19 are combined to select key sectors. [ABSTRACT FROM AUTHOR]

Like the other spheres of economic activity, international trade is also a victim of the current Covid-19 pandemic. Therefore, taking this into consideration, this study examines the impact of the novel Covid-19 virus on international trade, by using monthly data from China and USA. For this purpose, we have referred to the novel Fourier causality test. The findings of the test show that there is a direct causal relationship between the Covid-19 related deaths and the exports and imports of China, while the Covid-19 cases do not have a causal relationship with the exports and imports of China in the pandemic. Moreover, the Covid-19 cases and deaths have a causal relationship with the exports and imports of USA. Thus, we found that there were heterogeneous effects experienced in both the countries. Based on these empirical findings, some policy implications have been suggested for the Chinese and USA economies. [ABSTRACT FROM AUTHOR]

COVID-19 has had a serious impact on the lives and health of people and severely affected the population flow in 2020. Baidu migration data offer great opportunities to study spatiotemporal interactions among cities. Revealing population flow patterns has important scientific significance for the precise prevention and control of the COVID-19 epidemic. The aim of this article is to reveal the spatiotemporal patterns of population flow and associated influential factors in 22 cities in the Sichuan-Chongqing region (SCR), which is regarded as the fourth pole of China's economy. Four typical time periods are selected to study the spatiotemporal patterns of population flow. The regional population flow intensities in all cities and between different cities in the SCR are illustrated. Stepwise regression is used to analyse the factors affecting regional population flow intensity in four selected periods. The results show that (1) the COVID-19 epidemic greatly affected population flow in the SCR, (2) more travel occurred between cities on holidays than on weekdays in the SCR when the epidemic was not serious, and (3) the regional population flow intensity was strongly correlated with the population education level and transportation facilities when the epidemic was not serious. [ABSTRACT FROM AUTHOR]