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Housing price forecastability: A factor analysis

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Author Info

  • Lasse Bork

    ()
    (Aalborg University)

  • Stig V. Møller

    ()
    (Aarhus University and CREATES)

Abstract

We examine US housing price forecastability using a common factor approach based on a large panel of 122 economic time series. We find that a simple three-factor model generates an explanatory power of about 50% in one-quarter ahead in-sample forecasting regressions. The predictive power of the model stays high at longer horizons. The estimated factors are strongly statistically signi?cant according to a bootstrap resampling method which takes into account that the factors are estimated regressors. The simple three-factor model also contains substantial out-of-sample predictive power and performs remarkably well compared to both autoregressive benchmarks and computational intensive forecast combination models.

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File URL: ftp://ftp.econ.au.dk/creates/rp/12/rp12_27.pdf
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Bibliographic Info

Paper provided by School of Economics and Management, University of Aarhus in its series CREATES Research Papers with number 2012-27.

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Length: 44
Date of creation: 25 May 2012
Date of revision:
Handle: RePEc:aah:create:2012-27

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Web page: http://www.econ.au.dk/afn/

Related research

Keywords: House prices; Forecasting; Factor model; Principal components; Macroeconomic factors; Factor forecast combination; Bootstrap;

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Cited by:
  1. Paul E. Carrillo & Erik Robert De Wit & William D. Larson, 2012. "Can Tightness in the Housing Market Help Predict Subsequent Home Price Appreciation? Evidence from the U.S. and the Netherlands," Working Papers 2012-11, The George Washington University, Institute for International Economic Policy.

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