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Can Google Trends Data Predict Housing Market Trends?

Author

Listed:
  • Mirosaw Beej
  • Agnieszka Szczepaska

Abstract

The main idea of this work is that the dynamics of the housing market is derived from the society's behaviour and the data obtained from Google Trends, allows monitoring the activity of the information society in terms of interest in housing. Obtaining and analysing data on the dynamics of internet searches for specific words related to the housing market can provide a basis for forecasting housing price dynamics. An increase in searches can suggest a future increase in prices and a decrease a stagnation or slump. The study used a vector autoregressive model (VAR) together with causality analysis in the Granger sense. The method developed allows more accurate forecasting of housing prices than traditional methods using only macroeconomic data.

Suggested Citation

  • Mirosaw Beej & Agnieszka Szczepaska, 2024. "Can Google Trends Data Predict Housing Market Trends?," ERES eres2024-044, European Real Estate Society (ERES).
    • Handle: RePEc:arz:wpaper:eres2024-044
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    File URL: https://eres.architexturez.net/doc/oai-eres-id-eres2024-044
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    More about this item

    Keywords

    Forcasting; Google Trends; housing; real estate;
    All these keywords.

    JEL classification:

    • R3 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Real Estate Markets, Spatial Production Analysis, and Firm Location

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