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Determinants of Airbnb prices in European cities: A spatial econometrics approach

机译:欧洲城市Airbnb价格的决定因素:空间计量方法方法

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摘要

We examine the determinants of Airbnb prices in 10 major EU cities, focusing on the role of location. The results confirm that attributes related to size, quality, and location are all significant drivers of Airbnb rates. Novel indices based on TripAdvisor data are used to measure the attractiveness of neighbourhoods, and the results show a more robust impact on price than standard location variables based on selected points of interest. The analysis confirms that Airbnb prices are spatially dependent, requiring the implementation of spatial regression models. Following recent studies on spatial econometrics, we examine various spatial models, including specifications with multiple sources of spatial dependence. The results show significant differences between the coefficients estimated with OLS and the various spatial models, especially in the case of location-specific variables. As well as having managerial and policy implications, our study contributes to the hedonic price literature by providing a methodological guide on spatial regression models.
机译:我们研究了10个主要城市的Airbnb价格的决定因素,重点是位置的作用。结果证实,与大小,质量和位置相关的属性是Airbnb率的所有重要驱动因素。基于TripAdvisor数据的新型指数用于衡量邻域的吸引力,结果对基于所选择的兴趣点的标准位置变量表示更强大的影响。分析证实,Airbnb价格在空间上依赖,需要实施空间回归模型。在最近关于空间计量经济学的研究之后,我们检查各种空间模型,包括具有多种空间依赖来源的规格。结果显示了与OLS和各种空间模型估计的系数之间的显着差异,特别是在特定位置的变量的情况下。除了有管理和政策影响,我们的研究通过提供空间回归模型的方法导指导,我们的研究通过提供了一种方法导向。

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