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Research on China’s Risk of Housing Price Contagion Based on Multilayer Networks

The major issue in the evolution of housing prices is risk of housing price contagion. To model this issue, we constructed housing multilayer networks using transfer entropy, generalized variance decomposition, directed minimum spanning trees, and directed planar maximally filtered graph methods, as...

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Detalles Bibliográficos
Autores principales: Qiu, Lu, Su, Rongpei, Wang, Zhouwei
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9498244/
https://www.ncbi.nlm.nih.gov/pubmed/36141192
http://dx.doi.org/10.3390/e24091305
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author Qiu, Lu
Su, Rongpei
Wang, Zhouwei
author_facet Qiu, Lu
Su, Rongpei
Wang, Zhouwei
author_sort Qiu, Lu
collection PubMed
description The major issue in the evolution of housing prices is risk of housing price contagion. To model this issue, we constructed housing multilayer networks using transfer entropy, generalized variance decomposition, directed minimum spanning trees, and directed planar maximally filtered graph methods, as well as China’s comprehensive indices of housing price and urban real housing prices from 2012 to 2021. The results of our housing multilayer networks show that the topological indices (degree, PageRank, eigenvector, etc.) of new first-tier cities (Tianjin, Qingdao, and Shenyang) rank higher than those of conventional first-tier cities (Beijing, Shanghai, Guangzhou, and Shenzheng).
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spelling pubmed-94982442022-09-23 Research on China’s Risk of Housing Price Contagion Based on Multilayer Networks Qiu, Lu Su, Rongpei Wang, Zhouwei Entropy (Basel) Article The major issue in the evolution of housing prices is risk of housing price contagion. To model this issue, we constructed housing multilayer networks using transfer entropy, generalized variance decomposition, directed minimum spanning trees, and directed planar maximally filtered graph methods, as well as China’s comprehensive indices of housing price and urban real housing prices from 2012 to 2021. The results of our housing multilayer networks show that the topological indices (degree, PageRank, eigenvector, etc.) of new first-tier cities (Tianjin, Qingdao, and Shenyang) rank higher than those of conventional first-tier cities (Beijing, Shanghai, Guangzhou, and Shenzheng). MDPI 2022-09-15 /pmc/articles/PMC9498244/ /pubmed/36141192 http://dx.doi.org/10.3390/e24091305 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Qiu, Lu
Su, Rongpei
Wang, Zhouwei
Research on China’s Risk of Housing Price Contagion Based on Multilayer Networks
title Research on China’s Risk of Housing Price Contagion Based on Multilayer Networks
title_full Research on China’s Risk of Housing Price Contagion Based on Multilayer Networks
title_fullStr Research on China’s Risk of Housing Price Contagion Based on Multilayer Networks
title_full_unstemmed Research on China’s Risk of Housing Price Contagion Based on Multilayer Networks
title_short Research on China’s Risk of Housing Price Contagion Based on Multilayer Networks
title_sort research on china’s risk of housing price contagion based on multilayer networks
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9498244/
https://www.ncbi.nlm.nih.gov/pubmed/36141192
http://dx.doi.org/10.3390/e24091305
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