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Search and Predictability of Prices in the Housing Market

Author

Listed:
  • 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)

  • Erik Christian Montes Schütte

    (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)

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.

Suggested Citation

  • Stig Vinther Møller & Thomas Pedersen & Erik Christian Montes Schütte & Allan Timmermann, 2024. "Search and Predictability of Prices in the Housing Market," Management Science, INFORMS, vol. 70(1), pages 415-438, January.
    • Handle: RePEc:inm:ormnsc:v:70:y:2024:i:1:p:415-438
    DOI: 10.1287/mnsc.2023.4672
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    Cited by:

    1. Zhou, Mingtao & Ma, Yong, 2025. "Climate risk and predictability of global stock market volatility," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 101(C).
    2. Frederico Mira Godinho & Katja Neugebauer, 2025. "House Hunting High and Low: Constructing a Housing Search Index for Portugal," Working Papers w202507, Banco de Portugal, Economics and Research Department.
    3. Hu, Maggie Rong & Kuang, Weida & Li, Xiaoyang & Shi, Yang, 2025. "Is the more the merrier? Buyers’ onsite viewing activities and housing search outcomes," Journal of Banking & Finance, Elsevier, vol. 180(C).
    4. Biktimirov, Ernest N. & Sokolyk, Tatyana & Ayanso, Anteneh, 2024. "Unpacking the relation between media sentiment and house prices: A topic modeling approach," Journal of Housing Economics, Elsevier, vol. 66(C).
    5. Elisa Guglielminetti & Michele Loberto & Giordano Zevi & Roberta Zizza, 2021. "Living on my own: the impact of the Covid-19 pandemic on housing preferences," Questioni di Economia e Finanza (Occasional Papers) 627, Bank of Italy, Economic Research and International Relations Area.

    More about this item

    Keywords

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    JEL classification:

    • C10 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - General
    • E17 - Macroeconomics and Monetary Economics - - General Aggregative Models - - - Forecasting and Simulation: Models and Applications
    • G10 - Financial Economics - - General Financial Markets - - - General (includes Measurement and Data)
    • R3 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Real Estate Markets, Spatial Production Analysis, and Firm Location

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