文献类型：期刊文献

英文题名：Quantifying interconnectedness and centrality ranking among financial institutions with TVP-VAR framework

作者：Xu, Hai-Chuan[1,2];Jawadi, Fredj[3];Zhou, Jie[1];Zhou, Wei-Xing[1,2]

机构：[1]East China Univ Sci & Technol, Sch Business, 130 Meilong Rd, Shanghai 200237, Peoples R China;[2]East China Univ Sci & Technol, Res Ctr Econophys, 130 Meilong Rd, Shanghai 200237, Peoples R China;[3]IAE Lille Univ, Sch Management, 104 Ave, F-59043 Lille, France

年份：2022

外文期刊名：EMPIRICAL ECONOMICS

收录：;WOS:【SSCI(收录号:WOS:001061286000001)】；

基金：We are grateful to the editor Bertrand Candelon and an anonymous referee for their constructive comments and helpful suggestions. We thank participants at the 5th International Workshop on "Financial Market and Nonlinear Dynamics" organized in Paris in June 2021. We acknowledge financial support from the National Natural Science Foundation of China (U1811462 and 71971081) and the Fundamental Research Funds for the Central Universities.

语种：英文

外文关键词：TVP-VAR; Spillover effect; Systemic risk; Systemically important financial institutions; Ranking stability

摘要：Financial risk is spread and amplified through the interconnectedness among financial institutions. We apply a time-varying parameter vector autoregression model to analyze the dynamic spillover effects in the Chinese financial system. We find that the 2017 house price control policies have significantly increased the risk of China's financial system. Before 2017, with the prosperity of the real estate market, the interconnectedness of the Chinese financial system continued to decline, while after 2017, with the slowdown of house price growth and the downturn of the real estate market, the interconnectedness turned to increase. For different sectors, the trends and the magnitudes of the spillover effects are diverse, and any sector can contribute to systemic risk in a dynamic way. Finally, we rank 20 systemically important financial institutions according to two centrality measures. The stable institution ranking provides less noisy information for regulators to formulate a policy and intervene in the market effectively.