Risk of declined company performance during COVID-19-Spatial quantile autoregression based on network analysis

被引:4
|
作者
Ye, Wuyi [1 ]
Li, Mingge [1 ]
机构
[1] Univ Sci & Technol China, Dept Stat & Finance, Hefei, Anhui, Peoples R China
关键词
Spatial quantile autoregressive model; Network analysis; Systemic risk; Company performance; Supply chain; SUPPLY CHAIN; BUSINESS PARTNERSHIP; REGRESSION; DETERMINANTS; INFERENCE; MODELS;
D O I
10.1016/j.cie.2022.108670
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
There is a great deal of literature regarding the performance of listed companies during periods of financial distress and/or financial crisis. However, very few of them considered the interaction of companies and its impact on performance. This paper introduces network structure and a spatial quantile autoregressive model to study the heterogeneous effect of exogenous variables on the different quantiles of company performance during COVID-19 pandemic. We find that the interconnectedness between listed companies in China changed significantly after the outbreak of COVID-19. The pandemic outbreak, as well as company size, robustness of the supply chain, and other exogenous variables, significantly affect company performance. In addition, we identify four major drivers of company performance from the perspective of spatial analysis. We also find that the impact of explanatory variables shows distributional heterogeneity.
引用
收藏
页数:13
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