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What do online listings tell us about the housing market?

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  • Michele Loberto
  • Andrea Luciani
  • Marco Pangallo

Abstract

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.

Suggested Citation

  • Michele Loberto & Andrea Luciani & Marco Pangallo, 2020. "What do online listings tell us about the housing market?," Papers 2004.02706, arXiv.org.
  • Handle: RePEc:arx:papers:2004.02706
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    References listed on IDEAS

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    Cited by:

    1. Michele Loberto, 2021. "Foreclosures and house prices," Temi di discussione (Economic working papers) 1325, Bank of Italy, Economic Research and International Relations Area.

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