What Do Online Listings Tell Us About the Housing Market?

33 Pages Posted: 14 May 2018 Last revised: 8 Apr 2020

See all articles by Michele Loberto

Michele Loberto

Bank of Italy

Andrea Luciani

Bank of Italy

Marco Pangallo

Scuola Superiore Sant'Anna di Pisa

Date Written: April 6, 2020

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.

Keywords: big data, machine learning, housing market

JEL Classification: C44, C81, R31

Suggested Citation

Loberto, Michele and Luciani, Andrea and Pangallo, Marco, What Do Online Listings Tell Us About the Housing Market? (April 6, 2020). Updated version of Bank of Italy Temi di Discussione (Working Paper) No. 1171, Available at SSRN: https://ssrn.com/abstract=3176962 or http://dx.doi.org/10.2139/ssrn.3176962

Michele Loberto (Contact Author)

Bank of Italy ( email )

Via Nazionale 91
Rome, 00184
Italy

Andrea Luciani

Bank of Italy ( email )

Via Nazionale 91
Rome, 00184
Italy

Marco Pangallo

Scuola Superiore Sant'Anna di Pisa ( email )

Biblioteca Scuola Superiore Sant'Anna
Piazza Martiri della Liberta, n. 33
Pisa, 56127
Italy

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