基于TVP-SV模型的商品住房价格波动机理研究——以深圳市为例
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摘要
近年来,商品住房价格受多变量因素动态作用呈现出较大的波动现象,而各因素对商品住房价格的作用机理表明其具有不同的相关性和显著性。研究采用深圳市为样本数据,基于时间序列回归模型并引入时变和随机因子,构建了随机波动时变参数(TVP-SV)模型,通过分析影响商品住房价格的供给和需求因素指标,运用Gibbs抽样方法估计模型参数,针对2000-2015年影响深圳市商品住房价格变动的因素进行动态分析,实证研究表明,小学学生数量、商品住房供应量和土地价格对深圳市商品住房价格波动的影响最为显著。
In recent years commodity housing price is influenced by dynamic actions of multiple variable factors and present a large fluctuation, while action mechanisms of various factors on commodity housing price show that they have different correlations and significances. This study is based on time series regression model and employs time varying factor and random factor, takes Shenzhen city as the sample data, and has built a TVP-SV model. Through analyzing the supply factor and demand factor that influence commodity housing price, and employs Gibbs sampling method to estimate this model's parameters, and conducts a dynamic analysis on factors that influence Shenzhen commodity housing's price fluctuation in 2000-2015. The study results show that the population of primary school students,supply amount of commodity housing and land price have the most significant influences on Shenzhen commodity housing price fluctuation.
In recent years commodity housing price is influenced by dynamic actions of multiple variable factors and present a large fluctuation, while action mechanisms of various factors on commodity housing price show that they have different correlations and significances. This study is based on time series regression model and employs time varying factor and random factor, takes Shenzhen city as the sample data, and has built a TVP-SV model. Through analyzing the supply factor and demand factor that influence commodity housing price, and employs Gibbs sampling method to estimate this model's parameters, and conducts a dynamic analysis on factors that influence Shenzhen commodity housing's price fluctuation in 2000-2015. The study results show that the population of primary school students,supply amount of commodity housing and land price have the most significant influences on Shenzhen commodity housing price fluctuation.
引文
[1]Nellis J,Longbottom J.An empirical analysis of the date prices in the United Kingdom[J].Urban Studies,1981,(17):9-21.
[2]Abraham J M,Hendershott P H.Bubbles in metropolitan housing[J].Journal of Housing Research,1996:191-208.
[3]Joshua Gallin.The long-run relationship between house price and income:Evidence from local housing market[J].Real Estate Economics,2006,34(3):417-438.
[4]张红,翁少群.基于均衡价格形成机制的住宅价格变化特征研究[J].土木工程学报,2007,40(8):100-105.
[5]薛建谱,王卫华.基于均衡模型的我国商品房价格影响因素分析[J].统计与决策,2013,(22):118-121.
[6]Lawrence Katz,Kenneth T Rosen.The inter jurisdictional effects of growth controls on housing prices[J].Journal of Law&Economics,1987,30(1):149-160.
[7]张所地,范新英.基于面板分位数回归模型的收入、利率对房价的影响关系研究[J].数理统计与管理,2015,34(6):1057-1065.
[8]柴强.影响房价的几个理论问题[J].城市开发,2005,5:8-9.㈦
[9]兰峰,张媛.商品住宅价格上涨的空间自回归模型及其实证[J].统计与决策,2012,(13):94-97.
[10]姜喜龙,赵伟.经济结构变化对商品房价格的影响:来自1999-2011年省际面板数据的实证分析[J].数理统计与管理,2016,35(2):276-284.
[11]Stuart A Gabriel,Joe P Mattey,William L Wascher.Housing price differentials and dynamics:Evidence from the Los Angeles and San Francisco metropolitan areas[J].Economic Review,1999,2(1):3-22.
[12]Sirmans G S,Macpherson D A,Zietz E N.The composition of hedonic pricing models[J].Journal of real estate literature,2005,13(1):3-43.
[13]温海珍,贾生华.住宅的特征与特征的价格一基于特征价格模型的分析[J].浙江大学学报(工学版),2004,38(10):1338-1342.
[14]徐丽,简迎辉.基于特征价格模型的南京市住宅价格实证分析[J].土木工程与管理学报,2015,32(4):85-89.
[15]Black F.Studies of stock market volatility changes[A].Proceedings of the American Statistical Association,Business and Economic Statistics Section[C].Springer,1976:177-181.
[16]Taylor S T.Modeling Financial Time Series[M].New York:Wiley,1986.
[17]Yasuhiro Omori,Siddhartha Chib,Neil Shephard,Jouchi Nakajima.Stochastic volatility with leverage:Fast likelihood inference[J].Journal of Econometrics,2007,10:425-449.
[18]赵昕东,王小叶.什么决定中国食品价格变动:供给抑或需求一基于随机波动时变参数模型[J].财经研究,2014,11:61-68.
[19]朱慧明,周帅伟,李素芳,曾昭法.基于Gibbs抽样算法的贝叶斯动态面板数据模型分析[J].经济数学,2011,28(1):52-60.
[20]袁博,刘园.中国房地产价格波动的宏观经济要素研究一基于可变参数状态空间模型的动态研究[J].中央财经大学学报,2014,4:97-103.
[21]原鹏飞,邓嫦琼.住房价格上涨与其影响因素之间的关系研究一基于VEC模型的实证分析[J].统计与信息论坛,2008,11:83-86.
[2]Abraham J M,Hendershott P H.Bubbles in metropolitan housing[J].Journal of Housing Research,1996:191-208.
[3]Joshua Gallin.The long-run relationship between house price and income:Evidence from local housing market[J].Real Estate Economics,2006,34(3):417-438.
[4]张红,翁少群.基于均衡价格形成机制的住宅价格变化特征研究[J].土木工程学报,2007,40(8):100-105.
[5]薛建谱,王卫华.基于均衡模型的我国商品房价格影响因素分析[J].统计与决策,2013,(22):118-121.
[6]Lawrence Katz,Kenneth T Rosen.The inter jurisdictional effects of growth controls on housing prices[J].Journal of Law&Economics,1987,30(1):149-160.
[7]张所地,范新英.基于面板分位数回归模型的收入、利率对房价的影响关系研究[J].数理统计与管理,2015,34(6):1057-1065.
[8]柴强.影响房价的几个理论问题[J].城市开发,2005,5:8-9.㈦
[9]兰峰,张媛.商品住宅价格上涨的空间自回归模型及其实证[J].统计与决策,2012,(13):94-97.
[10]姜喜龙,赵伟.经济结构变化对商品房价格的影响:来自1999-2011年省际面板数据的实证分析[J].数理统计与管理,2016,35(2):276-284.
[11]Stuart A Gabriel,Joe P Mattey,William L Wascher.Housing price differentials and dynamics:Evidence from the Los Angeles and San Francisco metropolitan areas[J].Economic Review,1999,2(1):3-22.
[12]Sirmans G S,Macpherson D A,Zietz E N.The composition of hedonic pricing models[J].Journal of real estate literature,2005,13(1):3-43.
[13]温海珍,贾生华.住宅的特征与特征的价格一基于特征价格模型的分析[J].浙江大学学报(工学版),2004,38(10):1338-1342.
[14]徐丽,简迎辉.基于特征价格模型的南京市住宅价格实证分析[J].土木工程与管理学报,2015,32(4):85-89.
[15]Black F.Studies of stock market volatility changes[A].Proceedings of the American Statistical Association,Business and Economic Statistics Section[C].Springer,1976:177-181.
[16]Taylor S T.Modeling Financial Time Series[M].New York:Wiley,1986.
[17]Yasuhiro Omori,Siddhartha Chib,Neil Shephard,Jouchi Nakajima.Stochastic volatility with leverage:Fast likelihood inference[J].Journal of Econometrics,2007,10:425-449.
[18]赵昕东,王小叶.什么决定中国食品价格变动:供给抑或需求一基于随机波动时变参数模型[J].财经研究,2014,11:61-68.
[19]朱慧明,周帅伟,李素芳,曾昭法.基于Gibbs抽样算法的贝叶斯动态面板数据模型分析[J].经济数学,2011,28(1):52-60.
[20]袁博,刘园.中国房地产价格波动的宏观经济要素研究一基于可变参数状态空间模型的动态研究[J].中央财经大学学报,2014,4:97-103.
[21]原鹏飞,邓嫦琼.住房价格上涨与其影响因素之间的关系研究一基于VEC模型的实证分析[J].统计与信息论坛,2008,11:83-86.