<abstract xmlns="http://www.w3.org/1999/xhtml">

<p>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 <italic>dwelling</italic> 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.</p>
</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.

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

Departament of Spatial Analysis and Real Estate Market

University of Warmia and Mazury in Olsztyn

Real Estate Management and Valuation

This work is licensed under the Creative Commons Attribution 4.0 International License.

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...

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

Online veröffentlicht: 09. Dez. 2023

Seitenbereich: 73 - 87

Eingereicht: 26. Juli 2023

Akzeptiert: 12. Sept. 2023

DOI: https://doi.org/10.2478/remav-2023-0032

Schlüsselwörter
calendar effects, behavioral finance, real estate market

© 2023 Mirosław Bełej, published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

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

Online veröffentlicht: 09. Dez. 2023

Seitenbereich: 73 - 87

Eingereicht: 26. Juli 2023

Akzeptiert: 12. Sept. 2023

DOI: https://doi.org/10.2478/remav-2023-0032

Schlüsselwörtercalendar effects, behavioral finance, real estate market

© 2023 Mirosław Bełej, published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Schlüsselwörter
calendar effects, behavioral finance, real estate market