商品房价格影响因素的综合分析——基于VAR模型
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摘要
针对商品房价格的影响因素,以合肥市房价为研究对象,根据价格理论,构造了商品房均衡价格模型,并从供需两侧选取了INV、CPI、LC、以及CA四个变量进行实证分析。首先,运用1997年-2016年合肥市各变量年度数据,通过Spearman相关系数检验,得出所选取的变量与商品房平均销售价格之间均具有较强的相关关系。其次,利用合肥市2013年4月-2017年11月部分变量的月度数据,建立向量自回归模型,利用脉冲响应分析和方差分解来进一步分析合肥市CPI、INV、CA以及LC几个变量对合肥市商品房平均销售价格的影响,最终得出除了房价自身以外,INV与CPI对房价的波动都做出了贡献,而LC与CA的贡献度很小。最后,根据实证分析的结果提出相关政策建议。
According to the factors affecting the price of commodity house, the house price of Hefei City is taken as the research object.According to the price theory, the equilibrium price model of commodity house is constructed. The four variables of INV, CPI, LC and CA are selected from both sides of supply and demand for empirical analysis. Firstly, using the annual data of various variables in Hefei from 1997 to2016, through the Spearman correlation coefficient test, it is concluded that there is a strong correlation between the selected variables and the average selling price of commodity house. Secondly, using the monthly data of partial variables from April 2013 to November 2017 in Hefei City, a vector autoregressive model was established, and the pulse response analysis and variance decomposition were used to further analyze the CPI, INV, CA and LC variables of Hefei City. The impact of the average selling price of commercial housing in the city finally concluded that INV and CPI contributed to the fluctuation of housing prices in addition to the housing price itself, while the contribution of LC and CA was small. Finally, based on the results of the empirical analysis, the relevant policy recommendations are proposed.
According to the factors affecting the price of commodity house, the house price of Hefei City is taken as the research object.According to the price theory, the equilibrium price model of commodity house is constructed. The four variables of INV, CPI, LC and CA are selected from both sides of supply and demand for empirical analysis. Firstly, using the annual data of various variables in Hefei from 1997 to2016, through the Spearman correlation coefficient test, it is concluded that there is a strong correlation between the selected variables and the average selling price of commodity house. Secondly, using the monthly data of partial variables from April 2013 to November 2017 in Hefei City, a vector autoregressive model was established, and the pulse response analysis and variance decomposition were used to further analyze the CPI, INV, CA and LC variables of Hefei City. The impact of the average selling price of commercial housing in the city finally concluded that INV and CPI contributed to the fluctuation of housing prices in addition to the housing price itself, while the contribution of LC and CA was small. Finally, based on the results of the empirical analysis, the relevant policy recommendations are proposed.
引文
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[9]赵志龙.基于VAR脉冲响应的商品房价格影响因素探究与分析[J].中国战略新兴产业,2017(28):70.
[10]徐锦,叶子青.基于VAR模型的商品房价格影响因素分析[J].统计与决策,2017(11):93-97.
[11]高鸿业.西方经济学[M].北京:中国人民大学出版社,2000.
[12]李子奈.计量经济学[M].北京:高等教育出版社,2005.
[2]Ambrogio Cesa-Bianchi. Housing cycles and macroeconomicfluctuations:A global perspective[J]. Journal of International Moneyand Finance,2013,37(2):215-238.
[3]Tom Engsted,Thomas Q. Pedersen. Housing market volatilityin the OECD area:Evidence from VAR based return decompositions[J]. Journal of Macroeconomics,2014,42(1):91-103.
[4]Nadia Benbouzid,Sushanta Mallick,Keith Pilbeam. Thehousing market and the credit default swap premium in the UKbanking sector:A VAR approach[J]. Research in InternationalBusiness and Finance,2018,44(1):1-15.
[5]吴学品,林明恒.海南房地产价格影响因素的实证研究———基于VAR模型的分析[J].海南金融,2011(12):21-24.
[6]罗孝玲,洪波,马世昌.基于VAR模型的房地产价格影响因素研究[J].中南大学学报(社会科学版),2012,18(04):1-7.
[7]陈德强,何智丽.基于VAR模型的三线城市商品房价格动态计量分析———以唐山市为例[J].工程管理学报,2012,26(03):84-88.
[8]牛雪贾,沐年国.基于VAR模型对商品房价格影响因素的实证分析———以上海市房价为例[J].科技和产业,2016,16(06):107-111.
[9]赵志龙.基于VAR脉冲响应的商品房价格影响因素探究与分析[J].中国战略新兴产业,2017(28):70.
[10]徐锦,叶子青.基于VAR模型的商品房价格影响因素分析[J].统计与决策,2017(11):93-97.
[11]高鸿业.西方经济学[M].北京:中国人民大学出版社,2000.
[12]李子奈.计量经济学[M].北京:高等教育出版社,2005.