论文标题
在线清单告诉我们有关房屋市场的信息？
What do online listings tell us about the housing market?
论文作者
论文摘要
用于分析住房市场的传统数据源显示出几个局限性，最近使用来自住房销售广告（ADS）网站的数据开始克服这些局限性。在本文中，使用意大利的大量AD数据集，我们将对这些数据的问题和潜力进行首次综合分析。主要问题是多个广告（“重复”）可以与同一住房单元相对应。我们表明，这个问题主要是由于卖方试图提高清单的可见性而引起的。复制品导致对住房供应的数量和组成的陈述，但是可以通过使用机器学习工具来识别重复项来纠正这种偏见。然后，我们专注于这些数据的潜力。我们表明，这些数据的及时性，粒度和在线性质允许监视住房需求，供应和流动性，并且网站上发布的（问）价格比交易价格更有用。
Traditional data sources for the analysis of housing markets show several limitations, that recently started to be overcome using data coming from housing sales advertisements (ads) websites. In this paper, using a large dataset of ads in Italy, we provide the first comprehensive analysis of the problems and potential of these data. The main problem is that multiple ads ("duplicates") can correspond to the same housing unit. We show that this issue is mainly caused by sellers' attempt to increase visibility of their listings. Duplicates lead to misrepresentation of the volume and composition of housing supply, but this bias can be corrected by identifying duplicates with machine learning tools. We then focus on the potential of these data. We show that the timeliness, granularity, and online nature of these data allow monitoring of housing demand, supply and liquidity, and that the (asking) prices posted on the website can be more informative than transaction prices.
