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The potential of big housing data: an application to the Italian real-estate market

Author

Listed:
  • Michele Loberto

    (Bank of Italy)

  • Andrea Luciani

    (Bank of Italy)

  • Marco Pangallo

    (University of Oxford)

Abstract

We present a new dataset of housing sales advertisements (ads) taken from Immobiliare.it, a popular online portal for real estate services in Italy. This dataset fills a big gap in Italian housing market statistics, namely the absence of detailed physical characteristics for houses sold. The granularity of online data also makes possible timely analyses at a very detailed geographical level. We first address the main problem of the dataset, i.e. the mismatch between ads and actual housing units - agencies have incentives for posting multiple ads for the same unit. We correct this distortion by using machine learning tools and provide evidence about its quantitative relevance. We then show that the information from this dataset is consistent with existing official statistical sources. Finally, we present some unique applications for these data. For example, we provide first evidence at the Italian level that online interest in a particular area is a leading indicator of prices. Our work is a concrete example of the potential of large user-generated online databases for institutional applications.

Suggested Citation

  • Michele Loberto & Andrea Luciani & Marco Pangallo, 2018. "The potential of big housing data: an application to the Italian real-estate market," Temi di discussione (Economic working papers) 1171, Bank of Italy, Economic Research and International Relations Area.
    • Handle: RePEc:bdi:wptemi:td_1171_18
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    References listed on IDEAS

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    2. Piazzesi, M. & Schneider, M., 2016. "Housing and Macroeconomics," Handbook of Macroeconomics, in: J. B. Taylor & Harald Uhlig (ed.), Handbook of Macroeconomics, edition 1, volume 2, chapter 0, pages 1547-1640, Elsevier.
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    4. Michele Loberto & Francesco Zollino, 2016. "Housing and credit markets in Italy in times of crisis," Temi di discussione (Economic working papers) 1087, Bank of Italy, Economic Research and International Relations Area.
    5. Paul E. Carrillo & Eric R. Wit & William Larson, 2015. "Can Tightness in the Housing Market Help Predict Subsequent Home Price Appreciation? Evidence from the United States and the Netherlands," Real Estate Economics, American Real Estate and Urban Economics Association, vol. 43(3), pages 609-651, September.
    6. Donald Haurin, 1988. "The Duration of Marketing Time of Residential Housing," Real Estate Economics, American Real Estate and Urban Economics Association, vol. 16(4), pages 396-410, December.
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    8. Atif Mian & Kamalesh Rao & Amir Sufi, 2013. "Household Balance Sheets, Consumption, and the Economic Slump," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 128(4), pages 1687-1726.
    9. Federica Ciocchetta & Wanda Cornacchia & Roberto Felici & Michele Loberto, 2016. "Assessing financial stability risks from the real estate market in Italy," Questioni di Economia e Finanza (Occasional Papers) 323, Bank of Italy, Economic Research and International Relations Area.
    10. Dorinth W. van Dijk & Marc K. Francke, 2018. "Internet Search Behavior, Liquidity and Prices in the Housing Market," Real Estate Economics, American Real Estate and Urban Economics Association, vol. 46(2), pages 368-403, June.
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    Cited by:

    1. Bricongne, Jean-Charles & Meunier, Baptiste & Pouget, Sylvain, 2023. "Web-scraping housing prices in real-time: The Covid-19 crisis in the UK," Journal of Housing Economics, Elsevier, vol. 59(PB).
    2. Pierluigi Bologna & Arianna Miglietta & Anatoli Segura, 2020. "Contagion in the CoCos Market? A Case Study of Two Stress Events," International Journal of Central Banking, International Journal of Central Banking, vol. 16(6), pages 137-184, December.
    3. Boeri, Filippo & Di Cataldo, Marco & Pietrostefani, Elisabetta, 2022. "Localised effects of re-allocated real estate mafia assets," LSE Research Online Documents on Economics 116682, London School of Economics and Political Science, LSE Library.
    4. Davide Fantino, 2018. "Potential output and microeconomic heterogeneity," Temi di discussione (Economic working papers) 1194, Bank of Italy, Economic Research and International Relations Area.
    5. Corinna Ghirelli & Juan Peñalosa & Javier J. Pérez & Alberto Urtasun, 2019. "Some implications of new data sources for economic analysis and official statistics," Economic Bulletin, Banco de España, issue JUN.
    6. Trojanek, Radoslaw & Gluszak, Michal, 2022. "Short-run impact of the Ukrainian refugee crisis on the housing market in Poland," Finance Research Letters, Elsevier, vol. 50(C).
    7. Michele Loberto & Andrea Luciani & Marco Pangallo, 2022. "What Do Online Listings Tell Us about the Housing Market?," International Journal of Central Banking, International Journal of Central Banking, vol. 18(4), pages 1-52, October.
    8. Valeriia Budiakivska & Luca Casolaro, 2018. "Please in my back yard: the private and public benefits of a new tram line in Florence," Temi di discussione (Economic working papers) 1161, Bank of Italy, Economic Research and International Relations Area.
    9. Elisa Guglielminetti & Michele Loberto & Giordano Zevi & Roberta Zizza, 2021. "Living on my own: the impact of the Covid-19 pandemic on housing preferences," Questioni di Economia e Finanza (Occasional Papers) 627, Bank of Italy, Economic Research and International Relations Area.
    10. Valentina Aprigliano & Guerino Ardizzi & Alessia Cassetta & Alessandro Cavallero & Simone Emiliozzi & Alessandro Gambini & Nazzareno Renzi & Roberta Zizza, 2021. "Exploiting payments to track Italian economic activity: the experience at Banca d’Italia," Questioni di Economia e Finanza (Occasional Papers) 609, Bank of Italy, Economic Research and International Relations Area.
    11. Pangallo, Marco & Nadal, Jean-Pierre & Vignes, Annick, 2019. "Residential income segregation: A behavioral model of the housing market," Journal of Economic Behavior & Organization, Elsevier, vol. 159(C), pages 15-35.
    12. Alessio Anzuini & Luca Rossi, 2018. "Fiscal policy in the US: a new measure of uncertainty and its recent development," Temi di discussione (Economic working papers) 1197, Bank of Italy, Economic Research and International Relations Area.
    13. Michele Cascarano & Filippo Natoli, 2023. "Temperatures and search: evidence from the housing market," Temi di discussione (Economic working papers) 1419, Bank of Italy, Economic Research and International Relations Area.

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    More about this item

    Keywords

    big data; machine learning; housing market;
    All these keywords.

    JEL classification:

    • C44 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Operations Research; Statistical Decision Theory
    • C81 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Methodology for Collecting, Estimating, and Organizing Microeconomic Data; Data Access
    • R31 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Real Estate Markets, Spatial Production Analysis, and Firm Location - - - Housing Supply and Markets

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