Determinants of house price dynamics. What can we learn from search engine data?
-
Marco Oestmann
and
Lars Bennöhr
Abstract
There is a broad literature on determinants of house price dynamics, which received increasing attention in the aftermath of the subprime crisis. Additional to macroeconomic standard variables, there might be other hard to measure or even unobservable factors influencing real estate prices. Using quarterly data, we try to increase the informational input of conventional models and capture such effects by including Google search engine query information into a set of standard fundamental variables explaining house prices. We use the house price index (HPI) published by Eurostat to perform fixed-effects regressions for a panel of 14 EU-countries comprising the years 2005-2013. We find that Google data as a single aggregate measure plays a prominent role in explaining house price developments.
© 2015 by Lucius & Lucius, Stuttgart
Articles in the same Issue
- Contents
- What Caused the Great Recession?
- Time Varying Fiscal Multipliers in Germany
- Planned Fiscal Consolidations and Growth Forecast Errors – New Panel Evidence on Fiscal Multipliers
- Nowcasting Regional GDP: The Case of the Free State of Saxony
- Determinants of house price dynamics. What can we learn from search engine data?
Articles in the same Issue
- Contents
- What Caused the Great Recession?
- Time Varying Fiscal Multipliers in Germany
- Planned Fiscal Consolidations and Growth Forecast Errors – New Panel Evidence on Fiscal Multipliers
- Nowcasting Regional GDP: The Case of the Free State of Saxony
- Determinants of house price dynamics. What can we learn from search engine data?
