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Housing price forecastability: A factor analysis

Lasse Bork and Stig V. Møller ()
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Stig V. Møller: Aarhus University and CREATES, Postal: Department of Economics and Business, Fuglesangs Allé 4, 8210 Aarhus V, Denmark

CREATES Research Papers from Department of Economics and Business Economics, Aarhus University

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.

Keywords: House prices; Forecasting; Factor model; Principal components; Macroeconomic factors; Factor forecast combination; Bootstrap (search for similar items in EconPapers)
JEL-codes: C53 E3 G1 (search for similar items in EconPapers)
Pages: 44
Date: 2012-05-25
New Economics Papers: this item is included in nep-for and nep-ure
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ftp://ftp.econ.au.dk/creates/rp/12/rp12_27.pdf (application/pdf)

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Journal Article: Housing Price Forecastability: A Factor Analysis (2018) Downloads
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