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

Author

Listed:
  • Bełej Mirosław

    (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
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    References listed on IDEAS

    as
    1. Zambrano-Monserrate, Manuel A. & Ruano, María Alejandra, 2019. "Does environmental noise affect housing rental prices in developing countries? Evidence from Ecuador," Land Use Policy, Elsevier, vol. 87(C).
    2. 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.
    3. 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)

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    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

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