摘要
采用网络分析法,从担保网络节点间关联性网络结构出发,利用2003—2017年沪深A股上市公司数据,探究我国上市公司担保网络风险传染机制。研究发现:负面冲击或关联性的增加都会加剧担保网络风险传染,但是负面冲击只能通过担保链引发风险传染,说明担保网络风险传染路径具有关系传递性且依赖担保链实现。担保网络形成过程中,法律环境缺失导致担保契约非有效和信息不对称,金融市场化程度较低导致的企业担保刚性约束或国有企业政府隐性担保,都会促进企业加入担保链,最终会形成担保网络风险传染;进一步地,负面冲击对居中度较高企业产生较大影响,关联性过高企业间会出现“共荣共损”现象。因此,制度建设和关联性网络结构可视化监管十分必要。
From the network structure of relations in guarantee network, we apply network analysis and the data of listed companies from 2003 to 2017 on the Shanghai and Shenzhen stock exchanges to analyze guarantee network risk contagion mechanism. The results show that negative shock or the increase of relations significantly exacerbates risk contagion. But negative shock can only lead to risk contagion through guarantee chain, which demonstrates that the path of guarantee network risk contagion has relationship transitivity, which depends on the relation of guarantee chain. In the process of guarantee network formation, the ineffective guarantee contract and asymmetric information caused by lack of legal environment and the rigid restriction of guarantee contracts or implicit guarantee of state-owned enterprises caused by low financial marketization are drivers underlying enterprises’ motivation to join the guarantee chain and this will finally lead to risk contagion in guarantee network. Furthermore, the negative shock has a great influence on these enterprises with a high betweenness and those highly related enterprisess tend to gain prosperity or sufer loss jointly. Therefore, the government should improve institutional environment and visual supervision of network structure of guarantee behavior among listed companies.
作者
吕静
王营
郭沛
Lv Jing;Wang Ying;Guo Pei(College of Economics&Management,China Agricultural University,Beijing 100083;School of Finance,Shandong University of Finance and Economics,Jinan 250014)
出处
《管理评论》
CSSCI
北大核心
2022年第3期66-78,共13页
Management Review
基金
国家自然科学基金青年项目(71802116)
教育部人文社会科学规划青年项目(17YJC630166)
山东省自然科学基金博士项目(ZR2018BG006)
山东省社会科学规划研究专项课题(19CJRJ15)。
关键词
担保网络
风险传染
关联性
网络结构
guarantee network
risk contagion
relations
network structure