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引用次数: 4
摘要
摘要准确分析住房市场需要使用合适的房价指数。我们比较了两个常见的重复销售房价指数[BBailey,Muth and Nourse(BMN)和Case nd Shiller(CS)]与高和王的不平衡面板(UP)方法的性质。利用新西兰三个不同住房市场的数据,这三个指数对房价走势产生了类似的衡量标准。当使用单独的训练和测试数据的子样本进行评估时,这三种测量方法中没有一种明显优于其他方法。当我们使用模拟数据和其他数据生成过程来测试房产时,会出现一个明确的结果:当相对房价跟随实际或近乎随机的波动时,CS方法显然更优越;否则UP方法(稍微)优越。因此,研究人员在选择房价指数构建方法时,应考虑其数据的时间序列特性。
Repeat sales house price indices: comparative properties under alternative data generation processes
ABSTRACT Accurate analysis of housing markets requires the use of an appropriate house price index. We compare the properties of two common repeat sales house price indices [Bailey, Muth and Nourse (BMN) and Case-nd Shiller (CS)] with those of Gao and Wang’s unbalanced panel (UP) approach. Using data across three differing housing markets within New Zealand, the three indices produce similar measures of house price movements. When evaluated using separate training and testing sub-samples of the data, none of the three measures is unambiguously superior to the others. When we test properties using simulated data with alternative data generation processes, a clear result emerges: The CS method is clearly superior when relative house prices follow an actual or near random walk; otherwise the UP method is (slightly) superior. Thus researchers should consider the time series properties of their data when choosing a method of house price index construction.