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A New Index of Housing Sentiment

Author

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  • Lasse Bork

    (Aalborg University)

  • Stig V. Møller

    (Aarhus University and CREATES)

  • Thomas Q. Pedersen

    (Aarhus University and CREATES)

Abstract

We propose a new measure for housing sentiment and show that it accurately tracks expectations about future house price growth rates. We construct the housing sentiment index using partial least squares on household survey responses to questions about buying conditions for houses. We ?find that housing sentiment explains a large share of the time-variation in house prices during both boom and bust cycles and it strongly outperforms several macroeconomic variables typically used to forecast house prices.

Suggested Citation

  • Lasse Bork & Stig V. Møller & Thomas Q. Pedersen, 2016. "A New Index of Housing Sentiment," CREATES Research Papers 2016-32, Department of Economics and Business Economics, Aarhus University.
    • Handle: RePEc:aah:create:2016-32
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    Cited by:

    1. Oguzhan Cepni & Rangan Gupta & Christian Pierdzioch, 2024. "Forecasting Growth-at-Risk of the United States: Housing Price versus Housing Sentiment or Attention," Working Papers 202401, University of Pretoria, Department of Economics.
    2. Goller, Daniel & Harrer, Tamara & Lechner, Michael & Wolff, Joachim, 2021. "Active labour market policies for the long-term unemployed: New evidence from causal machine learning," Economics Working Paper Series 2108, University of St. Gallen, School of Economics and Political Science.
    3. Oguzhan Cepni & Rangan Gupta & Yigit Onay, 2022. "The role of investor sentiment in forecasting housing returns in China: A machine learning approach," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(8), pages 1725-1740, December.
    4. Petre Caraiani & Rangan Gupta & Chi Keung Marco Lau & Hardik A. Marfatia, 2022. "Effects of Conventional and Unconventional Monetary Policy Shocks on Housing Prices in the United States: The Role of Sentiment," Journal of Behavioral Finance, Taylor & Francis Journals, vol. 23(3), pages 241-261, July.
    5. Rangan Gupta & Hardik A. Marfatia & Christian Pierdzioch & Afees A. Salisu, 2022. "Machine Learning Predictions of Housing Market Synchronization across US States: The Role of Uncertainty," The Journal of Real Estate Finance and Economics, Springer, vol. 64(4), pages 523-545, May.
    6. André, Christophe & Caraiani, Petre & Călin, Adrian Cantemir & Gupta, Rangan, 2022. "Can monetary policy lean against housing bubbles?," Economic Modelling, Elsevier, vol. 110(C).
    7. Luiz Renato Lima & Lucas Lúcio Godeiro, 2023. "Equity‐premium prediction: Attention is all you need," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 38(1), pages 105-122, January.
    8. Borup, Daniel & Christensen, Bent Jesper & Mühlbach, Nicolaj Søndergaard & Nielsen, Mikkel Slot, 2023. "Targeting predictors in random forest regression," International Journal of Forecasting, Elsevier, vol. 39(2), pages 841-868.
    9. Christophe Andre & David Gabauer & Rangan Gupta, 2020. "Time-Varying Spillovers between Housing Sentiment and Housing Market in the United States," Working Papers 202091, University of Pretoria, Department of Economics.
    10. Xu Gong & Keqin Guan & Qiyang Chen, 2022. "The role of textual analysis in oil futures price forecasting based on machine learning approach," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 42(10), pages 1987-2017, October.
    11. Rangan Gupta & Chi Keung Marco Lau & Wendy Nyakabawo, 2018. "Predicting Aggregate and State-Level US House Price Volatility: The Role of Sentiment," Working Papers 201866, University of Pretoria, Department of Economics.
    12. Bouras, Christos & Christou, Christina & Gupta, Rangan & Lesame, Keagile, 2023. "Forecasting state- and MSA-level housing returns of the US: The role of mortgage default risks," Research in International Business and Finance, Elsevier, vol. 65(C).
    13. 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.
    14. André, Christophe & Gabauer, David & Gupta, Rangan, 2021. "Time-varying spillovers between housing sentiment and housing market in the United States☆," Finance Research Letters, Elsevier, vol. 42(C).
    15. Schmeling, Maik & Schrimpf, Andreas & Steffensen, Sigurd A.M., 2022. "Monetary policy expectation errors," Journal of Financial Economics, Elsevier, vol. 146(3), pages 841-858.
    16. Rangan Gupta & Chi Keung Marco Lau & Vasilios Plakandaras & Wing-Keung Wong, 2019. "The role of housing sentiment in forecasting U.S. home sales growth: evidence from a Bayesian compressed vector autoregressive model," Economic Research-Ekonomska Istraživanja, Taylor & Francis Journals, vol. 32(1), pages 2554-2567, January.
    17. Gupta, Rangan & Ma, Jun & Theodoridis, Konstantinos & Wohar, Mark E, 2020. "Is there a National Housing Market Bubble Brewing in the United States?," Cardiff Economics Working Papers E2020/3, Cardiff University, Cardiff Business School, Economics Section.
    18. Shao, Jin & Hong, Jingke & Wang, Xianzhu & Yan, Xiaochen, 2023. "The relationship between social media sentiment and house prices in China: Evidence from text mining and wavelet analysis," Finance Research Letters, Elsevier, vol. 57(C).
    19. Hardik A. Marfatia & Christophe André & Rangan Gupta, 2022. "Predicting Housing Market Sentiment: The Role of Financial, Macroeconomic and Real Estate Uncertainties," Journal of Behavioral Finance, Taylor & Francis Journals, vol. 23(2), pages 189-209, May.
    20. Gong, Xue & Zhang, Weiguo & Wang, Junbo & Wang, Chao, 2022. "Investor sentiment and stock volatility: New evidence," International Review of Financial Analysis, Elsevier, vol. 80(C).
    21. Bauer, Gregory H., 2017. "International house price cycles, monetary policy and credit," Journal of International Money and Finance, Elsevier, vol. 74(C), pages 88-114.
    22. Christou, Christina & Gupta, Rangan & Nyakabawo, Wendy, 2019. "Time-varying impact of uncertainty shocks on the US housing market," Economics Letters, Elsevier, vol. 180(C), pages 15-20.

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    More about this item

    Keywords

    Housing sentiment; house price forecastability; partial least squares; dynamic model averaging;
    All these keywords.

    JEL classification:

    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • E3 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles
    • G1 - Financial Economics - - General Financial Markets

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