运用分位回归特征价格模型构建住房价格指数

发布时间：2018-04-19 21:49

本文选题：分位价格指数 + 特征价格模型　；参考：《统计与决策》2015年04期

【摘要】：文章采用上海市新建住房及二手住房交易数据,在特征价格模型的基础上,运用分位回归编制住房价格指数,并通过与OLS回归结果对比,验证其必要性及可行性。结果发现,不同层次的住房价格波动存在显著差异,房价上涨率从低端住房向高端住房递减,低分位点的房价指数波动更大。
[Abstract]:Based on the transaction data of newly built and second-hand housing in Shanghai, this paper uses quantile regression to compile the housing price index based on the characteristic price model, and verifies its necessity and feasibility by comparing with the results of OLS regression. The results show that there are significant differences between different levels of housing price fluctuation, the rise rate of house price decreases from low-end housing to high-end housing, and the price index of low-grade housing is more volatile.
【作者单位】：上海金融学院国际金融学院;上海财经大学公共经济与管理学院;
【基金】：国家自然科学基金资助项目(71103121) 上海市政府决策咨询课题(2011-GR-26)
【分类号】：F299.27

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