房价泡沫测度及其相依结构分析——以49个大中城市为例  

House Price Bubble Measurement and Its Dependent Structure Analysis——A Case Study of 49 Large and Medium-sized Cities

作　　者：王凡 王诗琪 傅佳莎 WANG Fan;WANG Shi-qi;FU Jia-sha(Research Institute of Economics and Management,Southwestern University of Finance and Economics,Chengdu,Sichuan,611130,China;Department of Economics,Faculty of Social Sciences,The Chinese University of Hong Kong,Hong Kong,999077,China)

机构地区：[1]西南财经大学经济与管理研究院,四川成都611130 [2]香港中文大学社会科学院经济学系,中国香港999077

出　　处：《西华大学学报（哲学社会科学版）》2024年第3期41-61,共21页Journal of Xihua University(Philosophy & Social Sciences)

基　　金：国家自然科学基金面上项目“新型城镇化背景下行政区划调整的理论模型构建与政策效应评估”(项目编号:72373121)。

摘　　要：房地产行业是我国经济的重要组成部分,监测房价泡沫是防范房地产市场风险、进而防范化解金融风险的关键措施。文章采用GSADF检验和BSADF检验对我国49个大中城市的房地产价格泡沫进行识别,基于Moran's I指数和R-Vine Copula模型分析城市间房价泡沫的空间自相关性和相依结构。研究发现,我国房地产市场存在房价泡沫,具有高度的空间自相关性以及地理区位和城市层面的聚集特征;一线城市和新一线城市房价泡沫峰值高、持续期长,部分三线城市存在房价泡沫;城市之间房价泡沫具有显著的相依性,存在房价同涨同跌的趋势。文章结论有助于地方政府及时监测房价泡沫及其空间溢出效应,对防范房地产市场风险具有重要意义。The real estate industry is an important part of China's economic,and monitoring housing price bubbles is a key meas-ure for preventing real estate market risks and thus preventing and resolving financial risks.This paper adopts the GSADF test and the BSADF test to identify real estate price bubbles in 49 large and medium-sized cities in China,and analyzes the spatial autocorrelation and dependent structure of housing price bubbles among cities based on Moran's I index and the R-Vine Copula model.It is found that there are multiple periods of bubbles in China's real estate market,with high spatial autocorrelation and clustering characteristics at both the geographical and urban levels;the peak and duration of housing price bubbles are higher and longer in first-tier and new first-tier rise and fall together.The results of this study help local governments to timely monitor housing price bubbles and their spillover ef-fects,which are of great significance for preventing risks in the real estate market.

关 键 词：房价泡沫 空间溢出 Vine Copula模型 

分 类 号：F293.3[经济管理—国民经济]