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基于信息溢出网络的我国行业关联性研究
引用本文:王丹,黄玮强.基于信息溢出网络的我国行业关联性研究[J].运筹与管理,2019,28(9):173-180.
作者姓名:王丹  黄玮强
作者单位:东北大学 工商管理学院,辽宁 沈阳 110167
基金项目:国家自然科学基金面上项目(71771042,71371044);中央高校基本科研业务费项目(N180614004)
摘    要:行业信息溢出网络是各行业之间风险关联的载体,其信息溢出的方向和强度与行业的风险传染特征密切相关。运用广义方差分解对申银万国行业一级指数同时构建行业收益率溢出网络和行业波动率溢出网络,分别从静态和动态角度分析我国行业信息溢出的总体情况和动态演化。研究发现:我国各行业间信息溢出水平较高,整体信息联动能力强,但各行业信息溢出随时间变化具有波动性和不确定性。长期情形下,收益率溢出网络和波动溢出网络对系统性重要行业的识别排序具有高度一致性,但短期内两者存在较大差异。长期内,银行业和非银行金融业是系统性重要(信息)接受行业,机械设备业是系统性重要(信息)传播行业;短期内,银行、非银行金融、国防军工、食品饮料及家用电器业是系统性重要行业,但它们的具体角色(信息接受或者传播)具有不确定性。研究结论对于政府产业政策制定及产业监管具有重要的现实意义。

关 键 词:行业关联  方差分解  信息溢出网络  系统性重要行业  
收稿时间:2018-05-24

Study on Chinese Industry Connectedness Based on Information Spillover Network
WANG Dan,HUANG Wei-qiang.Study on Chinese Industry Connectedness Based on Information Spillover Network[J].Operations Research and Management Science,2019,28(9):173-180.
Authors:WANG Dan  HUANG Wei-qiang
Institution:School of Business Administration, Northeastern University, Shenyang110167, China
Abstract:Information spillover network is a channel of risk connectedness among different industries. The direction and strength of information spillover are closely related to the industries’ risk contagion characteristics. Using the generalized variance decomposition to establish industry return spillover networks and industry volatility spillover networks for the industry-level index of Shenyin & Wanguo Industries, this paper analyzes the total connectedness and dynamic evolution of China’s industry information spillovers from static and dynamic perspectives. The results show that the information spillover among Chinese industries is higher and stronger connectedness. However, the information spillover fluctuates and shows uncertainty with time. In the long run, it is highly consistent for return spillover networks and volatility spillover networks to identify and rank the systemically important industries. Nevertheless, in the short run there is a difference between them. Specifically, in the long term, bank and non-bank financial industry are the systemically important (information) accepted industries and the machinery and equipment industry is the systemically important (information) transmitted industries. In the short term, banks, non-bank finance, defense industry, food and beverage and household electrical appliances are systemically important industries, but their specific roles (accepted or transmitted information) are uncertain. Our findings have important implications for government industrial policy-makers and industrial regulators.
Keywords:industry connectedness  variance decomposition  information spillover network  systemically important industries  
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