Determinants of house price dynamics. What can we learn from search engine data?
Marco Oestmann, Helmut Schmidt University Hamburg & Lars Bennöhr, Helmut Schmidt University Hamburg, 2015-06-15
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.
year: | 2015 |
volume: | 66, Issue 1 |
pages: | 99-128 |
JEL: | C23, C82, R21, R31 |
keywords: | google_trends house_price_index real_estate |
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