Forecasting Residential Real Estate Price Changes from Online Search Activity
Eli Beracha () and
M. Babajide Wintoki ()
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Eli Beracha: University of Wyoming
M. Babajide Wintoki: University of Kansas
Journal of Real Estate Research, 2013, vol. 35, issue 3, 283-312
The intention of buying a home is revealed by many potential home buyers when they turn to the Internet to search for their future residence. This paper examines the extent to which future cross-sectional differences in home price changes are predicted by online search intensity in prior periods. Our findings are economically meaningful and suggest that abnormal search intensity for real estate in a particular city can help predict the cityâ€™s future abnormal housing price change. On average, cities associated with abnormally high real estate search intensity consistently outperform cities with abnormally low real estate search volume by as much as 8.5% over a two-year period.
JEL-codes: L85 (search for similar items in EconPapers)
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