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Modelling Housing Rents Using Spatial Autoregressive Geographically Weighted Regression: A Case Study in Cracow, Poland
ISPRS International Journal of Geo-Information ( IF 2.8 ) Pub Date : 2020-05-26 , DOI: 10.3390/ijgi9060346
Mateusz Tomal

The proportion of tenants will undoubtedly rise in Poland, where at present, the ownership housing model is very dominant. As a result, the rental housing market in Poland is currently under‑researched in comparison with owner-occupancy. In order to narrow this research gap, this study attempts to identify the determinants affecting rental prices in Cracow. The latter were obtained from the internet platform otodom.pl using the web scraping technique. To identify rent determinants, ordinary least squares (OLS) regression and spatial econometric methods were used. In particular, traditional spatial autoregressive model (SAR) and spatial autoregressive geographically weighted regression (GWR‑SAR) were employed, which made it possible to take into account the spatial heterogeneity of the parameters of determinants and the spatially changing spatial autocorrelation of housing rents. In-depth analysis of rent determinants using the GWR-SAR model exposed the complexity of the rental market in Cracow. Estimates of the above model revealed that many local markets can be identified in Cracow, with different factors shaping housing rents. However, one can identify some determinants that are ubiquitous for almost the entire city. This concerns mainly the variables describing the area of the flat and the age of the building. Moreover, the Monte Carlo test indicated that the spatial autoregressive parameter also changes significantly over space.

中文翻译:

使用空间自回归地理加权回归建模房屋租金:以波兰克拉科夫为例

毫无疑问,波兰的房客比例将会上升,而波兰目前的所有权住房模式非常占主导地位。结果,与所有者入住相比,目前波兰的租赁住房市场研究不足。为了缩小研究差距,本研究试图确定影响克拉科夫租金价格的决定因素。后者是使用Web抓取技术从Internet平台otodom.pl获得的。为了确定租金决定因素,使用了普通最小二乘(OLS)回归和空间计量经济学方法。特别是采用了传统的空间自回归模型(SAR)和空间自回归地理加权回归(GWR-SAR),这使得考虑决定因素参数的空间异质性和住房租金的空间变化的空间自相关成为可能。使用GWR-SAR模型对租金决定因素进行深入分析,揭示了克拉科夫租赁市场的复杂性。对上述模型的估计表明,克拉科夫可以确定许多当地市场,而不同的因素决定了房屋租金。但是,可以确定几乎整个城市都普遍存在的一些决定因素。这主要涉及描述公寓面积和建筑物使用年限的变量。此外,蒙特卡洛检验表明,空间自回归参数在空间上也有显着变化。使用GWR-SAR模型对租金决定因素进行深入分析,揭示了克拉科夫租赁市场的复杂性。对上述模型的估计表明,克拉科夫可以确定许多当地市场,而不同的因素决定了房屋租金。但是,可以确定几乎整个城市都普遍存在的一些决定因素。这主要涉及描述公寓面积和建筑物使用年限的变量。此外,蒙特卡洛检验表明,空间自回归参数在空间上也有显着变化。使用GWR-SAR模型对租金决定因素进行深入分析,揭示了克拉科夫租赁市场的复杂性。对上述模型的估计表明,克拉科夫可以确定许多当地市场,而不同的因素决定了房屋租金。但是,可以确定几乎整个城市都普遍存在的一些决定因素。这主要涉及描述公寓面积和建筑物使用年限的变量。此外,蒙特卡洛检验表明,空间自回归参数在空间上也有显着变化。这主要涉及描述公寓面积和建筑物使用年限的变量。此外,蒙特卡洛检验表明,空间自回归参数在空间上也有显着变化。这主要涉及描述公寓面积和建筑物使用年限的变量。此外,蒙特卡洛检验表明,空间自回归参数在空间上也有显着变化。
更新日期:2020-05-26
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