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Can Tightness in the Housing Market Help Predict Subsequent Home Price Appreciation? Evidence from the United States and the Netherlands

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  • Paul E. Carrillo
  • Eric R. Wit
  • William Larson

Abstract

type="main"> This article assesses the predictive power of variables that measure market tightness, such as seller's bargaining power and sale probabilities, on future home prices. Theoretical insights from a stylized search-and-matching model illustrate that such indicators can be associated with subsequent home price appreciation. The empirical analysis employs listings data on residential units offered for sale through a real estate broker in the Netherlands and for certain U.S. regions. Individual records are used to construct quarterly home price indices, an index that measures seller's bargaining power and (quality-adjusted) home sale probabilities. Using conventional time-series models we show that current sale probabilities and bargaining power can significantly reduce home price appreciation forecast errors and help to predict turning points in local area housing markets. The measures and approaches in this article help to demonstrate ways in which researchers and practitioners can leverage listings data to gain knowledge about the current and future state of the housing market.

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  • Paul E. Carrillo & Eric R. Wit & William Larson, 2015. "Can Tightness in the Housing Market Help Predict Subsequent Home Price Appreciation? Evidence from the United States and the Netherlands," Real Estate Economics, American Real Estate and Urban Economics Association, vol. 43(3), pages 609-651, September.
    • Handle: RePEc:bla:reesec:v:43:y:2015:i:3:p:609-651
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    File URL: http://hdl.handle.net/10.1111/1540-6229.12082
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    Cited by:

    1. Edward C. H. Tang, 2021. "Speculate a lot," Pacific Economic Review, Wiley Blackwell, vol. 26(1), pages 91-109, February.
    2. 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.
    3. Peter Chinloy & William D. Larson, 2017. "The Daily Microstructure of the Housing Market," FHFA Staff Working Papers 17-01, Federal Housing Finance Agency.
    4. Michele Loberto & Andrea Luciani & Marco Pangallo, 2022. "What Do Online Listings Tell Us about the Housing Market?," International Journal of Central Banking, International Journal of Central Banking, vol. 18(4), pages 1-52, October.
    5. Dorinth van Dijk, 2019. "Local Constant-Quality Housing Market Liquidity Indices," DNB Working Papers 637, Netherlands Central Bank, Research Department.
    6. Bricongne, Jean-Charles & Meunier, Baptiste & Pouget, Sylvain, 2023. "Web-scraping housing prices in real-time: The Covid-19 crisis in the UK," Journal of Housing Economics, Elsevier, vol. 59(PB).
    7. Steven Caudill & Claudio Detotto & Dominique Prunetti, 2020. "Bargaining power in apartment sales in Corsica: A latent class approach," Urban Studies, Urban Studies Journal Limited, vol. 57(13), pages 2754-2772, October.
    8. Justin Contat & Malcolm Rogers, 2022. "Housing Supply and Liquidity in the COVID-19 Era," FHFA Staff Working Papers 22-02, Federal Housing Finance Agency.
    9. Rangan Gupta & Damien Moodley, 2023. "Housing Search Activity and Quantiles-Based Predictability of Housing Price Movements in the United States," Working Papers 202335, University of Pretoria, Department of Economics.
    10. Dorinth van Dijk & David Geltner & Alex van de Minne, 2018. "Revisiting supply and demand indexes in real estate," ERES eres2018_41, European Real Estate Society (ERES).
    11. Elliot Anenberg & Daniel R. Ringo, 2022. "Volatility in Home Sales and Prices: Supply or Demand?," Finance and Economics Discussion Series 2022-041, Board of Governors of the Federal Reserve System (U.S.).
    12. Dorinth W. Dijk & David M. Geltner & Alex M. Minne, 2022. "The Dynamics of Liquidity in Commercial Property Markets: Revisiting Supply and Demand Indexes in Real Estate," The Journal of Real Estate Finance and Economics, Springer, vol. 64(3), pages 327-360, April.
    13. Dorinth W. van Dijk & Marc K. Francke, 2018. "Internet Search Behavior, Liquidity and Prices in the Housing Market," Real Estate Economics, American Real Estate and Urban Economics Association, vol. 46(2), pages 368-403, June.
    14. Darren K. Hayunga & R. Kelley Pace, 2019. "The Impact of TOM on Prices in the US Housing Market," The Journal of Real Estate Finance and Economics, Springer, vol. 58(3), pages 335-365, April.
    15. Han, Lu & Strange, William C., 2016. "What is the role of the asking price for a house?," Journal of Urban Economics, Elsevier, vol. 93(C), pages 115-130.
    16. Galesi, Alessandro & Mata, Nuria & Rey, David & Schmitz, Sebastian & Schuffels, Johannes, 2020. "Regional Housing Market Conditions in Spain," Research Memorandum 029, Maastricht University, Graduate School of Business and Economics (GSBE).
    17. Michele Loberto & Andrea Luciani & Marco Pangallo, 2018. "The potential of big housing data: an application to the Italian real-estate market," Temi di discussione (Economic working papers) 1171, Bank of Italy, Economic Research and International Relations Area.
    18. Alter, Adrian & Mahoney, Elizabeth M., 2021. "Local house-price vulnerability: Evidence from the U.S. and Canada," Journal of Housing Economics, Elsevier, vol. 54(C).
    19. Dorinth van Dijk & David Geltner & Alex van de Minne, 2018. "Revisiting supply and demand indexes in real estate," DNB Working Papers 583, Netherlands Central Bank, Research Department.

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