混合效应模型在新建住宅房价指数中的应用
发布时间:2018-10-13 19:15
【摘要】:我国目前新建住宅房价指数编制方法仍采用第一代或第二代方法,与真实房价情况严重脱节。现今房价指数编制第三代方法逐渐成为国际上的主要方法,但这一方法并非完全适合国内情况。文章采取第三代方法"同质可比"的思想,考虑我国实际房产交易情况,研究虚拟重复交易虚拟数据产生方法,并建立单一新建住房交易和虚拟重复住房交易两种交易数据的模型,找到一种新的、具有更高计算精确度和有效性的房价指数编制模型——自回归混合效应模型。
[Abstract]:At present, the compilation method of housing price index is still the first generation or the second generation method, which is out of step with the real housing price. Nowadays, the third generation method of house price index compilation has gradually become the main method in the world, but this method is not completely suitable for the domestic situation. This paper adopts the idea of "homogeneity comparison" of the third generation method, considering the real estate transaction situation in our country, studies the virtual data generation method of virtual duplicate transaction. The model of single new house transaction and virtual duplicate housing transaction is established, and a new model of house price index compilation with higher calculation accuracy and validity is found, which is called autoregressive mixed effect model.
【作者单位】: 西南财经大学经济与管理研究院;武汉理工大学理学院;
【基金】:湖北省统计科研计划项目(HB132-10)
【分类号】:F224.7;F299.23
[Abstract]:At present, the compilation method of housing price index is still the first generation or the second generation method, which is out of step with the real housing price. Nowadays, the third generation method of house price index compilation has gradually become the main method in the world, but this method is not completely suitable for the domestic situation. This paper adopts the idea of "homogeneity comparison" of the third generation method, considering the real estate transaction situation in our country, studies the virtual data generation method of virtual duplicate transaction. The model of single new house transaction and virtual duplicate housing transaction is established, and a new model of house price index compilation with higher calculation accuracy and validity is found, which is called autoregressive mixed effect model.
【作者单位】: 西南财经大学经济与管理研究院;武汉理工大学理学院;
【基金】:湖北省统计科研计划项目(HB132-10)
【分类号】:F224.7;F299.23
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