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"Geco" and its potential for real estate research: Evidence from the US housing market

Author

Listed:
  • Ralf Hohenstatt

    (University of Regensburg)

  • Manuel Käsbauer

    (University of Regensburg)

  • Wolfgang Schäfers

    (University of Regensburg)

Abstract

Over the past few years, Google econometrics (Geco) turns out to be a powerful tool for research based on individuals rational. Following the seminal work of Ginsberg et al. (2009), this is the second academic journal contribution to be based on search query data from Google Insights for Search (I4S). Existing information on the Home Buying Process is embedded into existing literature on the price-volume relationship in the housing market. The main findings are: I4S subcategories yield inferences about prices and transactions in the near future. While the “Real Estate Agency†subcategory serves as a very robust indicator of transaction volume, "Home Financing" provides interesting insights into the corresponding financing decisions. Therefore, this study contributes towards improving the infor-mational efficiency of a relatively imperfect market and is addressed to policy makers as well as real estate professionals.

Suggested Citation

  • Ralf Hohenstatt & Manuel Käsbauer & Wolfgang Schäfers, 2011. ""Geco" and its potential for real estate research: Evidence from the US housing market," Journal of Real Estate Research, American Real Estate Society, vol. 33(4), pages 471-506.
    • Handle: RePEc:jre:issued:v:33:n:4:2011:p:471-506
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    Citations

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    Cited by:

    1. Oestmann Marco & Bennöhr Lars, 2015. "Determinants of house price dynamics. What can we learn from search engine data?," Review of Economics, De Gruyter, vol. 66(1), pages 99-127, April.
    2. Prashant Das & Alan Ziobrowski & N. Coulson, 2015. "Online Information Search, Market Fundamentals and Apartment Real Estate," The Journal of Real Estate Finance and Economics, Springer, vol. 51(4), pages 480-502, November.
    3. 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.
    4. 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.

    More about this item

    JEL classification:

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

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