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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]

This paper aims to examine the co-movement between the two economic powers, namely the USA and China. The authors are mainly interested in examining the dynamics of co-movements during, and in the pre-covid periods. Additionally, they have aimed to examine the volatility spillover between USA and China, during and in the pre-covid periods. In order to achieve the research-based objectives, advanced econometrics models have been applied to the data from July1, 2010, to April 30, 2021. The results show that the sample market is integrated in the long run. The results also indicate that the behaviour of the Chinese market is same as the US market, and offers negligible opportunities for investors for diversification during this time. The findings indicate that the Ganger Causality between the stock markets during crisis is significantly higher than the pre-crisis period. The results of EGARCH model confirm the presence of asymmetric volatility spillover effects between the US and Chinese markets, during the considered time periods. This study also examines the co-movement in China, grounded upon the robust approach that facilitates examining the dependence structure between the sample variables. The findings offer valuable understanding for investors who are looking for investment diversification opportunities worldwide. [ABSTRACT FROM AUTHOR]

Recent research has shown that the COVID-19 pandemic has holistically affected the financial and industrial sectors of China, in a considerably adverse manner. This paper aims to examine the impact of the COVID-19 virus on the transportation and logistics sector in China. In this regard, the study opted for a quantitative method of research design, along with primary data collection. The explanatory variable here is the COVID-19 virus, whereas, the dependent variables are air freight, ocean freight, and land freight. The data analysis technique used is the Structural Equation Modelling (SEM) analysis, comprising of the Confirmatory Factor Analysis (CFA) and the path assessment method. A structured survey questionnaire was also used, and the survey questionnaire scale was set from strongly agree to disagree strongly. The findings revealed that the effect of COVID-19 on air freight is statistically negative and significant. Moreover, the impact of COVID-19 on land freight is statistically negative and significant, whereas the effect of COVID-19 is statistically insignificant in the context of ocean freight, particularly during the period of the COVID-19 pandemic. Therefore, keeping these results in consideration, policymakers can enhance their support, so as to increase the performance of the logistics and transportation sector in China. [ABSTRACT FROM AUTHOR]

The paper focuses on the trade performance of Romania, a representative country for the Central and Eastern European region, strongly connected with its European partners in global value chains and thus affected by any change in these countries' relationships with the rest of the world in general and China in particular. Using panel data gravity models for the 2008-2019 period, we find that Romania's exports are significantly influenced by the demand of its major trade partners in the EU, and imports from China and the rest of the world. In addition, exports are vulnerable to the effectiveness of the government in relation to the other countries, corruption control and cultural values such as collectivism. We also assess the capacity of Romanian exports to regain their ascending trend displayed before the COVID-19 pandemic by using simulation forecasting scenarios based on the shape of the economic recovery and the type of shock transmission across economies. We observe a sharp decrease in 2020 followed by an important recovery in 2021 in a V-shape scenario and uniform transmission of the pandemic shock in the internal demand and in the foreign trade, or followed by a very slow recovery in 2021 (in a U-shape scenario and non-uniform transmission type in the two previously mentioned elements), especially when the global relation with rest of the world is included. [ABSTRACT FROM AUTHOR]

This paper visualizes variations in the recovery patterns of intercity mobility during the Covid-19 outbreak in China using cartogram mapping. We found large regional disparities in intercity mobility recovery, with lower recovery ratios and speeds primarily concentrated in megacities and provincial capitals. Conversely, the recovery of intercity mobility was relatively high in other cities, especially in some labour-exporting cities of central and south-western China. In addition, cities in southern China showed a relatively higher recovery ratio and speed in intercity mobility than those in northern China. [ABSTRACT FROM AUTHOR]