Can Google Trends Data Predict Housing Market Trends?

Mirosaw Beej and Agnieszka Szczepaska

ERES from European Real Estate Society (ERES)

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.

Keywords: Forcasting; Google Trends; housing; real estate (search for similar items in EconPapers)
JEL-codes: R3 (search for similar items in EconPapers)
Date: 2024-01-01
New Economics Papers: this item is included in nep-ure
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Persistent link: https://EconPapers.repec.org/RePEc:arz:wpaper:eres2024-044

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