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首页> 外文期刊>Journal of property research >Spatial econometrics and the hedonic pricing model: what about the temporal dimension?
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Spatial econometrics and the hedonic pricing model: what about the temporal dimension?

机译：空间计量经济学和享乐主义定价模型：时间维度如何？

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摘要

Recent ready access to free software and toolbox applications is directly impacting spatial econometric modelling when working with geolocated data. Spatial econometric models are valuable tools for taking into account the possible latent structure of the price determination process and ensuring that the coefficients estimated are unbiased and efficient. However, mechanical applications can potentially bias estimated coefficients if spatial data is pooled over time because the applications consider the spatial dimension alone. Spatial models neglect the fact that data (e.g. real estate) may consist of a collection of spatial data pooled over time, and that time relations generate a unidirectional effect as opposed to the multidirectional effect associated with spatial relations. Through an empirical case study, this paper addresses the possible bias in spatial autoregressive estimated parameters when data consist of spatial layers pooled over time. An empirical study is made using apartment sales in Paris between 1990 and 2001. Estimation results and out-of-sample predictions confirm, at least for this case, the hypothesis that ignoring the time dimension and applying spatial econometric tools generate divergence among the estimated autoregressive coefficients, which can potentially engender other serious problems.
机译：使用地理定位数据时，最近对自由软件和工具箱应用程序的便捷访问将直接影响空间计量经济学建模。空间计量经济学模型是有价值的工具，可用于考虑价格确定过程的潜在结构并确保估计的系数无偏且有效。但是，如果随着时间的推移合并空间数据，则机械应用程序可能会偏向估计系数，因为应用程序仅考虑空间维度。空间模型忽略了这样一个事实，即数据（例如房地产）可能包含一段时间内合并的空间数据的集合，并且时间关系生成的是单向效果，而不是与空间关系相关的多方向效果。通过一个经验案例研究，本文解决了当数据由随时间推移合并的空间层组成时，空间自回归估计参数可能存在的偏差。使用1990年至2001年在巴黎的公寓销售进行了实证研究。至少在这种情况下，估计结果和样本外预测证实了以下假设：忽略时间维度并应用空间计量经济学工具会在估计的自回归中产生差异。系数，可能会引发其他严重问题。

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