Determinants of house price dynamics. What can we learn from search engine data?
Lars Bennöhr and
Marco Oestmann ()
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Marco Oestmann: Helmut Schmidt University, Hamburg, Postal: Helmut-Schmidt-Universität / Universität der Bundeswehr HH, Holstenhofweg 85, 22043 Hamburg, Germany
No 153/2014, Working Paper from Helmut Schmidt University, Hamburg
There is a broad literature about fundamental determinants of house prices, which received increasing attention in the aftermath of the subprime crisis. However, there might be several other partly unobservable socio-demographic, psychological or individual factors influencing real estate price dynamics. Using quarterly data, we try to capture such effects by including relevant Google search engine query information into a set of standard fundamental variables. We perform fixed-effects regressions for a panel of 14 EU-countries comprising the years 2005-2013. As dependent variable the house price index (HPI) from Eurostat is employed. We find that Google data as a single aggregate measure of unobserved variables plays a substantial role in explaining house price developments.
Keywords: Google Trends; House Price Index; Real Estate; Google Econometrics (search for similar items in EconPapers)
JEL-codes: C23 C82 R21 R31 (search for similar items in EconPapers)
Pages: 34 pages
New Economics Papers: this item is included in nep-ure
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Journal Article: Determinants of house price dynamics. What can we learn from search engine data? (2015)
Working Paper: Determinants of house price dynamics. What can we learn from search engine data? (2015)
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Persistent link: https://EconPapers.repec.org/RePEc:ris:vhsuwp:2014_153
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