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基于面板分位数回归的住宅价格影响因素分析
引用本文:喻胜华,赵 盼. 基于面板分位数回归的住宅价格影响因素分析[J]. 财经理论与实践, 2018, 0(5): 128-133
作者姓名:喻胜华  赵 盼
作者单位:(湖南大学 经济与贸易学院,湖南 长沙 410079)
摘    要:采用面板分位数回归方法,以全国35个大中城市为样本,利用2006—2015年的数据,对影响住宅价格的因素进行研究。结果表明:土地价格、人均储蓄余额、在岗职工平均工资、人口密度、空气质量对住宅价格有正向影响,每亿人医院或卫生院数量对住宅价格有负向影响;并且不同分位数水平下各影响因素的作用大小具有明显差异。研究结论对不同城市依据自身特征采取相应的调控政策具有一定的参考价值。

关 键 词:住宅价格;影响因素;面板数据;分位数回归

Analysis of Influencing Factors of Housing Price Based on Panel Quantile Regression
YU Shenghu,ZHAO Pan. Analysis of Influencing Factors of Housing Price Based on Panel Quantile Regression[J]. The Theory and Practice of Finance and Economics, 2018, 0(5): 128-133
Authors:YU Shenghu  ZHAO Pan
Affiliation:(School of Economics and Trade, Hunan University, Changsha, Hunan 410079, China)
Abstract:In this paper, the panel quantile regression method is used to study the factors that affecting the housing price by using the data from 2006 to 2015 in 35 large and medium-sized cities in China. The results show that the land price, per capita savings balance, the average salary of staff, population density and the air quality have significantly positive influence on housing price. The number of hospitals per one hundred million people has a negative impact on housing prices. And the level of influence is various in different quantiles. The conclusion has certain value for reference for different cities to adopt corresponding control policies according to their own characteristics.
Keywords:housing price   influencing factors   panel data   quantile regression
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