基于集合经验模态分解技术的中国房地产周期识别研究

发布时间：2018-03-31 22:02

本文选题：经验模态分解(EMD)　切入点：EEMD　出处：《经济评论》2014年04期

【摘要】：本文运用1991年1月-2011年12月房地产销售价格指数的月度数据,结合最新发展的集合经验模态分解(EEMD)技术,从多尺度识别了我国房地产市场内在的准周期成分。准周期的识别过程就是房价形成因素的寻找过程。以房地产改革元年1998年为数据分断点做比较研究和稳定性检验,对应的准周期得到再次识别,增强了结论的可信度。研究表明:从1991年1月-2011年12月的样本期间来看,房地产市场供给弹性不足;货币因素在房价形成中的贡献最大;长期经济增长因素贡献很小,不是驱动房价的主要力量。房改后,上述结论依然成立,然而,货币供给对房价增长主导性作用进一步增强;长期因素的相对方差贡献变大了,房价与经济发展水平关系更紧密。根据结论,本研究建议房地产调控应重在控制货币增速和加大土地供给两方面。
[Abstract]:In this paper, the monthly data of real estate sales price index from January 1991 to December 2011 are used, combined with the latest development of empirical mode decomposition (EMD) technique. This paper identifies the inherent quasi-periodic components of the real estate market in China from multiple scales. The identification process of the quasi-cycle is the process of searching for the forming factors of housing prices. Taking the first year of the real estate reform in 1998 as the data breakpoint, the comparative study and the stability test are done. From the sample period from January 1991 to December 2011, the supply elasticity of the real estate market is insufficient, and the monetary factor contributes the most to the formation of house prices. The contribution of long-term economic growth factors is very small, not the main force driving house prices. After the housing reform, the above conclusions still hold true. However, the dominant role of money supply in housing price growth is further enhanced; the relative variance of long-term factors has increased. According to the conclusion, this study suggests that the regulation of real estate should focus on controlling the monetary growth rate and increasing the supply of land.
【作者单位】：中山大学管理学院;中山大学创业学院;中山大学金融工程与风险管理研究中心;中山大学岭南学院;中山大学数学与计算科学学院;
【基金】：国家自然科学基金重点项目“房地产及其金融资产的定价与风险管理”(项目批准号:71231008) 广东省珠江学者计划(2010) 广东省高等学校高层次人才项目(2011)资助
【分类号】：F293.3;F224

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