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A New Index of Housing Sentiment

Author

Listed:
  • 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. Christophe André & Petre Caraiani & Adrian Cantemir Čalin & Rangan Gupta, 2018. "Can Monetary Policy Lean against Housing Bubbles?," Working Papers 201877, University of Pretoria, Department of Economics.
    2. Hardik A. Marfatia & Christophe Andre & Rangan Gupta, 2020. "Predicting Housing Market Sentiment: The Role of Financial, Macroeconomic and Real Estate Uncertainties," Working Papers 202061, University of Pretoria, Department of Economics.
    3. 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.
    4. 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.
    5. Rangan Gupta & Hardik A. Marfatia & Christian Pierdzioch & Afees A. Salisu, 2020. "Machine Learning Predictions of Housing Market Synchronization across US States: The Role of Uncertainty," Working Papers 202077, University of Pretoria, Department of Economics.
    6. 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.
    7. Daniel Borup & Bent Jesper Christensen & Nicolaj N. Mühlbach & Mikkel S. Nielsen, 2020. "Targeting predictors in random forest regression," CREATES Research Papers 2020-03, Department of Economics and Business Economics, Aarhus University.
    8. Oguzhan Cepni & Rangan Gupta & Yigit Onay, 2020. "The Role of Investor Sentiment in Forecasting Housing Returns in China: A Machine Learning Approach," Working Papers 202055, University of Pretoria, Department of Economics.
    9. 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.
    10. 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.
    11. Rangan Gupta & Chi Keung Marco Lau & Vasilios Plakandaras & Wing-Keung Wong, 2018. "The Role of Housing Sentiment in Forecasting US Home Sales Growth: Evidence from a Bayesian Compressed Vector Autoregressive Model," Working Papers 201842, University of Pretoria, Department of Economics.
    12. Petre Caraiani & Rangan Gupta & Chi Keung Marco Lau & Hardik A. Marfatia, 2019. "Effects of Conventional and Unconventional Monetary Policy Shocks on Housing Prices in the United States: The Role of Sentiment," Working Papers 201953, University of Pretoria, Department of Economics.

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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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