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'GECO's Weather Forecast' for the U.K. Housing Market: To What Extent Can We Rely on Google ECOnometrics?

Author

Listed:
  • Ralf Hohenstatt

    (University of Regensburg)

  • Manuel Kaesbauer

    (University of Regensburg)

Abstract

This study follows the stream of research identifying sentiment trends by using online search query data. The potential of the Google data series for the U.K. housing market on a disaggregated level is analyzed in a panel VAR framework. The findings confirm existing research based on U.S. samples that Google subcategories, especially "Real Estate Agency", serve as a robust indicator of transaction volume. Beside investigating how to deal with Google series in general and with heterogeneous cross sections specifically, the main contribution of this study to existing research is the detection of contrary dynamics within the Google "Home Financing" sub-category, which to date yields empirically mixed evidence (Hohenstatt, Kaesbauer and Schaefers, 2011). As expected from existing literature, sensitivity analysis yields that transaction volume responds twice as sensitively as house prices due to a standard deviation increase of the stress indicator. Most importantly, the derived stress indicator of housing market (un-)soundness works at least as well as in downturns, as opposed to "Real Estate Agency", which is primarily a suitable indicator during upturns.

Suggested Citation

  • Ralf Hohenstatt & Manuel Kaesbauer, 2014. "'GECO's Weather Forecast' for the U.K. Housing Market: To What Extent Can We Rely on Google ECOnometrics?," Journal of Real Estate Research, American Real Estate Society, vol. 36(2), pages 253-282.
    • Handle: RePEc:jre:issued:v:36:n:2:2014:p:253-282
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    Citations

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    Cited by:

    1. Mikhail Stolbov & Maria Shchepeleva, 2023. "Sentiment-based indicators of real estate market stress and systemic risk: international evidence," Annals of Finance, Springer, vol. 19(3), pages 355-382, September.
    2. Ramya Rajajagadeesan Aroul & Sanjiv Sabherwal & Sergiy Saydometov, 2022. "FEAR Index, city characteristics, and housing returns," Real Estate Economics, American Real Estate and Urban Economics Association, vol. 50(1), pages 173-205, March.
    3. Gianluca Marcato & Anupam Nanda, 2022. "Asymmetric Patterns of Demand-Supply Mismatch in Real Estate," The Journal of Real Estate Finance and Economics, Springer, vol. 64(3), pages 440-472, April.

    More about this item

    JEL classification:

    • L85 - Industrial Organization - - Industry Studies: Services - - - Real Estate Services

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