IDEAS home Printed from https://ideas.repec.org/a/vrs/remava/v31y2023i4p73-87n8.html
   My bibliography  Save this article

Predicting Housing Price Trends in Poland: Online Social Engagement - Google Trends

Author

Listed:
  • Bełej Mirosław

    (1 Departament of Spatial Analysis and Real Estate Market, University of Warmia and Mazury in Olsztyn, ul. Oczapowskiego 2, 10-719, Olsztyn, Poland)

Abstract

Various research methods can be used to collect housing market data and predict housing prices. The online search activity of Internet users is a novel and highly interesting measure of social behavior. In the present study, dwelling prices in Poland were analyzed based on aggregate data from seven Polish cities relative to the number of online searches for the keyword dwelling tracked by Google Trends, as well as several classical macroeconomic indicators. The analysis involved a vector autoregressive (VAR) model and the Granger causality test. The results of the study suggest that the volume of online searches returned by Google Trends is an effective predictor of housing price dynamics, and that unemployment and economic growth are important additional variables.

Suggested Citation

  • Bełej Mirosław, 2023. "Predicting Housing Price Trends in Poland: Online Social Engagement - Google Trends," Real Estate Management and Valuation, Sciendo, vol. 31(4), pages 73-87, December.
  • Handle: RePEc:vrs:remava:v:31:y:2023:i:4:p:73-87:n:8
    DOI: 10.2478/remav-2023-0032
    as

    Download full text from publisher

    File URL: https://doi.org/10.2478/remav-2023-0032
    Download Restriction: no

    File URL: https://libkey.io/10.2478/remav-2023-0032?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. López-Salido, J David & Arce, Oscar, 2006. "House Prices, Rents and Interest Rates Under Collateral Constraints," CEPR Discussion Papers 5689, C.E.P.R. Discussion Papers.
    2. Nan-Kuang Chen & Han-Liang Cheng & Ching-Sheng Mao, 2014. "Identifying and forecasting house prices: a macroeconomic perspective," Quantitative Finance, Taylor & Francis Journals, vol. 14(12), pages 2105-2120, December.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Nobili, Andrea & Zollino, Francesco, 2017. "A structural model for the housing and credit market in Italy," Journal of Housing Economics, Elsevier, vol. 36(C), pages 73-87.
    2. Prüser, Jan & Schmidt, Torsten, 2021. "Regional composition of national house price cycles in the US," Regional Science and Urban Economics, Elsevier, vol. 87(C).
    3. Óscar Arce & David López-Salido, 2011. "Housing Bubbles," American Economic Journal: Macroeconomics, American Economic Association, vol. 3(1), pages 212-241, January.
    4. Byron J. Idrovo-Aguirre & Francisco J. Lozano & Javier E. Contreras-Reyes, 2021. "Prosperity or Real Estate Bubble? Exuberance Probability Index of Real Housing Prices in Chile," IJFS, MDPI, vol. 9(3), pages 1-24, September.
    5. Prüser, Jan & Schmidt, Torsten, 2020. "Regional composition of national house price cycles in the US," Ruhr Economic Papers 853, RWI - Leibniz-Institut für Wirtschaftsforschung, Ruhr-University Bochum, TU Dortmund University, University of Duisburg-Essen.
    6. Kuang-Liang Chang & Nan-Kuang Chen & Charles Ka Yui Leung, 2016. "Losing Track of the Asset Markets: the Case of Housing and Stock," International Real Estate Review, Global Social Science Institute, vol. 19(4), pages 435-492.
    7. Luca Agnello & Vitor Castro & Ricardo M. Sousa, 2020. "The Housing Cycle: What Role for Mortgage Market Development and Housing Finance?," The Journal of Real Estate Finance and Economics, Springer, vol. 61(4), pages 607-670, November.
    8. Sugra Ingilab Humbatova & Natig Gadim-Ogli Hajiyev, 2021. "The Relationship between Oil Prices and Real Estate Loans and Mortgage Loans in Azerbaijan," International Journal of Energy Economics and Policy, Econjournals, vol. 11(1), pages 341-354.

    More about this item

    Keywords

    calendar effects; behavioral finance; real estate market;
    All these keywords.

    JEL classification:

    • R20 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Household Analysis - - - General
    • R30 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Real Estate Markets, Spatial Production Analysis, and Firm Location - - - General
    • R31 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Real Estate Markets, Spatial Production Analysis, and Firm Location - - - Housing Supply and Markets

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:vrs:remava:v:31:y:2023:i:4:p:73-87:n:8. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Peter Golla (email available below). General contact details of provider: https://www.sciendo.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.