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Online Information Search, Market Fundamentals and Apartment Real Estate

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  • Prashant Das
  • Alan Ziobrowski
  • N. Coulson

Abstract

We examine the association between online apartment rental searches and fundamental real estate market variables namely, vacancy rates, rental rates and real estate asset price returns. We find that consumer real estate searches are significantly associated with the market fundamentals after controlling for known determinants of these variables. In particular, we show that apartment rental-related online searches are endogenously and contemporaneously associated with reduced vacancy rate. However, the association between the searches and rental rates is not significant. The searches are also contemporaneously associated with positive returns on the appraised values of multifamily assets. There is some evidence that the searches are fundamentally associated with REIT returns in the short run and that REIT investors watch the online search trends to inform their stock pricing decisions. Copyright Springer Science+Business Media New York 2015

Suggested Citation

  • 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.
    • Handle: RePEc:kap:jrefec:v:51:y:2015:i:4:p:480-502
    DOI: 10.1007/s11146-015-9496-1
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    2. Paul M. Anglin & Yanmin Gao, 2023. "Value of Communication and Social Media: An Equilibrium Theory of Messaging," The Journal of Real Estate Finance and Economics, Springer, vol. 66(4), pages 861-903, May.
    3. Yunus, Nafeesa, 2023. "Long-run and short-run impact of the U.S. economy on stock, bond and housing markets: An evaluation of U.S. and six major economies," The Quarterly Review of Economics and Finance, Elsevier, vol. 90(C), pages 211-232.
    4. Coble, David & Pincheira, Pablo, 2017. "Nowcasting Building Permits with Google Trends," MPRA Paper 76514, University Library of Munich, Germany.
    5. David Coble & Pablo Pincheira, 2021. "Forecasting building permits with Google Trends," Empirical Economics, Springer, vol. 61(6), pages 3315-3345, December.
    6. Wei, Yu & Cao, Yang, 2017. "Forecasting house prices using dynamic model averaging approach: Evidence from China," Economic Modelling, Elsevier, vol. 61(C), pages 147-155.
    7. 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.
    8. Nuri Hacıevliyagil & Krzysztof Drachal & Ibrahim Halil Eksi, 2022. "Predicting House Prices Using DMA Method: Evidence from Turkey," Economies, MDPI, vol. 10(3), pages 1-27, March.
    9. Nafeesa Yunus, 2023. "Co‐movement among oil, stock, bond, and housing markets: An analysis of U.S., Asian, and European economies," International Review of Finance, International Review of Finance Ltd., vol. 23(2), pages 393-436, June.
    10. Yunus, Nafeesa, 2020. "Time-varying linkages among gold, stocks, bonds and real estate," The Quarterly Review of Economics and Finance, Elsevier, vol. 77(C), pages 165-185.

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