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Quantifying interconnectedness and centrality ranking among financial institutions with TVP-VAR framework
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 signific...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer Berlin Heidelberg
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9734361/ https://www.ncbi.nlm.nih.gov/pubmed/36532712 http://dx.doi.org/10.1007/s00181-022-02338-x |
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author | Xu, Hai-Chuan Jawadi, Fredj Zhou, Jie Zhou, Wei-Xing |
author_facet | Xu, Hai-Chuan Jawadi, Fredj Zhou, Jie Zhou, Wei-Xing |
author_sort | Xu, Hai-Chuan |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-9734361 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Springer Berlin Heidelberg |
record_format | MEDLINE/PubMed |
spelling | pubmed-97343612022-12-12 Quantifying interconnectedness and centrality ranking among financial institutions with TVP-VAR framework Xu, Hai-Chuan Jawadi, Fredj Zhou, Jie Zhou, Wei-Xing Empir Econ Article 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. Springer Berlin Heidelberg 2022-12-06 /pmc/articles/PMC9734361/ /pubmed/36532712 http://dx.doi.org/10.1007/s00181-022-02338-x Text en © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2022, Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic. |
spellingShingle | Article Xu, Hai-Chuan Jawadi, Fredj Zhou, Jie Zhou, Wei-Xing Quantifying interconnectedness and centrality ranking among financial institutions with TVP-VAR framework |
title | Quantifying interconnectedness and centrality ranking among financial institutions with TVP-VAR framework |
title_full | Quantifying interconnectedness and centrality ranking among financial institutions with TVP-VAR framework |
title_fullStr | Quantifying interconnectedness and centrality ranking among financial institutions with TVP-VAR framework |
title_full_unstemmed | Quantifying interconnectedness and centrality ranking among financial institutions with TVP-VAR framework |
title_short | Quantifying interconnectedness and centrality ranking among financial institutions with TVP-VAR framework |
title_sort | quantifying interconnectedness and centrality ranking among financial institutions with tvp-var framework |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9734361/ https://www.ncbi.nlm.nih.gov/pubmed/36532712 http://dx.doi.org/10.1007/s00181-022-02338-x |
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