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Towards robust house price index estimation: An empirical investigation of San Diego, California.

机译:迈向稳健的房价指数估算:对加利福尼亚圣地亚哥的实证研究。

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摘要

I develop a two step method for modeling the spatial and temporal variation in house prices across the regional landscape. In the first step, I utilize the Goetzmann and Spiegel (1997) Distance Weighted Repeat Sales (DWRS) model to construct "neighborhood" level indices. The DWRS model is a hybrid model: it provides "hedonic controls" via the distance function within the repeat sales framework. In the second step, I model the abnormal appreciation in the neighborhood (defined as the appreciation of the neighborhood's house price index over and above the regional average in the period) within an Autoregressive-Generalized Autoregressive Conditional Heteroskedasticity in Mean (or AR-GARCH-M) framework to characterize its temporal variation. I construct a buffer of "neighbors" variable for each neighborhood and use this to capture the spatial pattern of abnormal house price appreciation.; The benefits from adopting this two-step procedure are at least three-fold, Firstly, adopting the DWRS model enables the construction of accurate neighborhood-level house price indices that would otherwise not be available for small geographic areas. Secondly, this procedure models neighborhood effects and adjacency effects within a repeat sales context (unlike previous modeling within a hedonic specification). Thirdly, the AR-GARCH-M framework models the impact of neighbors and lagged values explicitly. A picture of "neighbors" in "time and space" thus emerges.; I also provide an explicit derivation of the variance-covariance matrix with spatial components for the DWRS model and explore the various conceptual and measurement issues that arise in implementing the estimation procedure.; Finally, I implement the two step procedure for a data set of repeat sales of single family homes in San Diego County, CA between 1995 and 1998 geocoded to Census tracts (a smaller geographic area than is usually employed). This yields 408 quarterly tract-level house price indices that show a wide range of appreciation over the period. I find that the use of a single area-wide house price index (such as the standard Weighted Repeat Sales index) as a proxy for house price appreciation within a specific area or neighborhood is not justified. This work should be of particular interest to the mortgage and mortgage-backed-securities market participants.
机译:我开发了一种分两步的方法来模拟整个区域景观中房价的时空变化。第一步,我利用Goetzmann和Spiegel(1997)的距离加权重复销售(DWRS)模型来构建“邻里”等级指数。 DWRS模型是一种混合模型:它通过重复销售框架中的距离函数提供“享乐控制”。在第二步中,我对均值的自回归-广义自回归条件异方差(或AR-GARCH-)中的邻域异常升值(定义为该时期内区域平均水平之上和之上的邻域房价指数的升值)进行建模。 M)表征其时间变化的框架。我为每个邻域构造一个“邻居”变量的缓冲区,并使用它来捕捉异常房价上涨的空间格局。采用此两步过程的好处至少有三方面:首先,采用DWRS模型可以构建准确的邻里级房价指数,而在其他较小的地理区域则无法获得。其次,此过程对重复销售环境中的邻里效应和邻接效应进行建模(与享乐规范中先前的建模不同)。第三,AR-GARCH-M框架显式地模拟邻居和滞后值的影响。于是出现了“时间和空间”中“邻居”的图片。我还提供了DWRS模型具有空间分量的方差-协方差矩阵的显式推导,并探讨了在实施估算程序时出现的各种概念和测量问题。最后,我对1995年至1998年之间在加利福尼亚州圣地亚哥县单户住宅的重复销售数据集实施了两步过程,该数据集已地理编码为人口普查区域(比通常使用的地理区域小)。这产生了408个季度性住房价格季度指数,显示该时期内的广泛升值。我发现,使用单一区域的房价指数(例如标准的加权重复销售指数)作为特定区域或邻域内的房价升值的代理是不合理的。抵押和抵押支持证券市场参与者应该特别关注这项工作。

著录项

  • 作者

    Raman, Padmasini S.;

  • 作者单位

    Rutgers The State University of New Jersey - New Brunswick.;

  • 授予单位 Rutgers The State University of New Jersey - New Brunswick.;
  • 学科 Economics General.
  • 学位 Ph.D.
  • 年度 2001
  • 页码 103 p.
  • 总页数 103
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类 经济学;
  • 关键词

  • 入库时间 2022-08-17 11:47:20

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