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Determinants of house price dynamics. What can we learn from search engine data?

Oestmann Marco () and Lars Bennöhr
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Oestmann Marco: Helmut Schmidt University Hamburg, Department of Economics, Holstenhofweg 85, D-22043 Hamburg

Review of Economics, 2015, vol. 66, issue 1, 99-127

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.

Keywords: Google Trends; House Price Index; Real Estate; Google Trends; House Price Index; Real Estate (search for similar items in EconPapers)
Date: 2015
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Citations: View citations in EconPapers (2)

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Working Paper: Determinants of house price dynamics. What can we learn from search engine data? (2014) Downloads
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DOI: 10.1515/roe-2015-0106

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