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By employing data from Shanghai and Shenzhen A-share markets for the period of 2019–2020, this paper examines the relationship between the degree of the COVID-19 pandemic’s impact on firms’ cash-holdings levels in China. We find that firms that are severely affected by the COVID-19 pandemic have higher current cash holdings levels, suggesting that the more positive (negative) the management tone in responding to the COVID-19 pandemic impact, the lower (higher) the firm’s current cash holdings. However, future corporate cash holdings decrease considerably irrespective of the corporate sentiment towards COVID-19. The positive sentiment of each firm’s management team towards the supply chain and the government policies results in a relative reduction of current cash holdings, whereas the severe impact on operating performance, especially the impact of the outbreak on the supply chain, demand, production and operations, and government policies, reduces the firm’ s future cash holdings. In addition, the impact of the pandemic has increased the current cash holdings of state-owned enterprises and reduced the future cash holdings of non-state-owned enterprises. Meanwhile, companies located in a city with a higher density of population or companies that experience relatively higher competition in the industry tend to undergo a severer impact on their current and future cash holdings due to the COVID-19 pandemic. Overall, this study sheds the light on stimulating the vitality of enterprise investment and promoting the domestic economic cycle. [ABSTRACT FROM AUTHOR]

Affected by the fluctuation of the market and economic environment during the epidemic period, the capital pressure of companies has increased sharply, which increases the possibility of risk transmission in the same industry and poses new challenges to the operation and financing of companies. From the perspective of preventive motivation of corporate cash holding, we creatively use the industry working capital shortfall as the explanatory variable to construct an Extended Cash Holding Model and a Cash Holding Value Regression Model. Taking the panel data of A-share listed companies in Shanghai and Shenzhen as samples, this paper uses the Classical Linear Regression Model and Fixed Effects Regression Model to study the relationship between industry working capital shortfall and cash holdings in the same industry, as well as the relationship between industry working capital shortfall and cash holding value. The empirical results show that industry working capital shortfall has an important impact on the cash holding level within the same industry, and the cash holding level is significantly and positively correlated with industry working capital shortfall. Moreover, this study also reveals that the industry working capital shortfall has a dual impact on cash holdings. Specifically, the higher the risk of industry working capital shortfall, the lower the value of company cash holdings. The conclusions of this paper not only extend the research on cash holding but also provide support and reference for companies to optimize the cash holding value. [ABSTRACT FROM AUTHOR]

Guo, D.; Xu, M., and Li, Y., 2020. An empirical study on the CPI interaction in the Yangtze River Delta economic zone. In: Gong, D.; Zhang, M., and Liu, R. (eds.), Advances in Coastal Research: Engineering, Industry, Economy, and Sustainable Development. Journal of Coastal Research, Special Issue No. 106, pp. 281–284. Coconut Creek (Florida), ISSN 0749-0208. Accurate identification of the source and transmission mechanism of price fluctuation in an economic zone is not only conducive to maintaining price stability and promoting the healthy development of the regional economy, but also its interaction can reflect the degree of integration of economic development among the main bodies in the region. However, few studies have explored the comprehensive price interaction in the integrated economic zone. Therefore, this paper chose the consumer price index (CPI) data of each province in the Yangtze River Delta economic zone to empirically analyze the CPI interaction cross the economic zone. The results showed that CPI fluctuation in Shanghai has a greater influence on CPI fluctuation in Jiangsu and Zhejiang. Shanghai and Jiangsu are each other's Granger causality, and Jiangsu and Zhejiang are each other's Granger causality. The results indicated that Shanghai and Jiangsu have highly integrated industrial and market structures, whereas Zhejiang has a relatively independent industrial and market structure. [ABSTRACT FROM AUTHOR]

The Chinese economy has entered the phase of high-quality development. Urbanization is an important driving factor in promoting the domestic economic cycle, while tourism is an emerging force in the development of urbanization. The convergence of these two factors will contribute to the high-quality development of regional economies. By constructing an evaluation index system of tourism development and urbanization level, 26 cities in the Yangtze River Delta Urban Agglomeration have been identified as the study area. The study has adopted the entropy method and the coupling coordination model to analyze the comprehensive development level of tourism and urbanization and the coupling coordination relationship between them from 2008 to 2018. The results show that the Yangtze River Delta presents a spatial pattern of orderly changes in the development of tourism, forming a spatial structure of "one pole and many centers", with Shanghai as the core. In terms of spatial distribution, it generally presents the spatial trend characteristics of "high in the east and low in the west" in the east–west direction, and "protruding in the middle and lower at both ends" in the south–north direction. Coordination and interaction are steadily developing to a high level, with significant spatial dependence and spillover effects. Based on the research results, the study applies a new development vision to explore the coupling coordination high-quality development mechanism of tourism and urbanization in the Yangtze River Delta region; the corresponding policy recommendations are discussed. [ABSTRACT FROM AUTHOR]

The fluctuations of economic and financial time series are influenced by various kinds of factors and usually demonstrate strong nonstationary and high complexity. Therefore, accurately forecasting economic and financial time series is always a challenging research topic. In this study, a novel multidecomposition and self-optimizing hybrid approach integrating multiple improved complete ensemble empirical mode decompositions with adaptive noise (ICEEMDANs), whale optimization algorithm (WOA), and random vector functional link (RVFL) neural networks, namely, MICEEMDAN-WOA-RVFL, is developed to predict economic and financial time series. First, we employ ICEEMDAN with random parameters to separate the original time series into a group of comparatively simple subseries multiple times. Second, we construct RVFL networks to individually forecast each subseries. Considering the complex parameter settings of RVFL networks, we utilize WOA to search the optimal parameters for RVFL networks simultaneously. Then, we aggregate the prediction results of individual decomposed subseries as the prediction results of each decomposition, respectively, and finally integrate these prediction results of all the decompositions as the final ensemble prediction results. The proposed MICEEMDAN-WOA-RVFL remarkably outperforms the compared single and ensemble benchmark models in terms of forecasting accuracy and stability, as demonstrated by the experiments conducted using various economic and financial time series, including West Texas Intermediate (WTI) crude oil prices, US dollar/Euro foreign exchange rate (USD/EUR), US industrial production (IP), and Shanghai stock exchange composite index (SSEC). [ABSTRACT FROM AUTHOR]