Search and Predictability of Prices in the Housing Market

Stig Vinther Møller (), Thomas Pedersen (), Erik Christian Schütte and Allan Timmermann ()
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Stig Vinther Møller: Department of Economics and Business Economics, Aarhus University, 8210 Aarhus, Denmark; Danish Finance Institute, 2000 Frederiksberg, Denmark
Thomas Pedersen: Department of Economics and Business Economics, Aarhus University, 8210 Aarhus, Denmark; Danish Finance Institute, 2000 Frederiksberg, Denmark
Allan Timmermann: University of California, San Diego, La Jolla, California 92093; Center for Economic and Policy Research, London EC1V 0DX, United Kingdom

Management Science, 2024, vol. 70, issue 1, 415-438

Abstract: We develop a new housing search index ( HSI ) extracted from online search activity on a limited set of keywords related to the house-buying process. We show that HSI has strong predictive power over subsequent changes in house prices, both in-sample and out-of-sample and after controlling for the effect of commonly used predictors, and relate our findings to models of search-induced frictions. Our results imply that search data can be used as an early indicator of where the market is going.

Keywords: internet search; housing markets; housing demand; forecasting; frictions; inelastic housing supply (search for similar items in EconPapers)
Date: 2024
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http://dx.doi.org/10.1287/mnsc.2023.4672 (application/pdf)

Related works:
Working Paper: Search and Predictability of Prices in the Housing Market (2021)
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Persistent link: https://EconPapers.repec.org/RePEc:inm:ormnsc:v:70:y:2024:i:1:p:415-438

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