Housing price forecastability: A factor analysis
Lasse Bork and
Stig V. Møller ()
Additional contact information
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
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)
New Economics Papers: this item is included in nep-for and nep-ure
References: Add references at CitEc
Citations: View citations in EconPapers (11) Track citations by RSS feed
Downloads: (external link)
Journal Article: Housing Price Forecastability: A Factor Analysis (2018)
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
Persistent link: https://EconPapers.repec.org/RePEc:aah:create:2012-27
Access Statistics for this paper
More papers in CREATES Research Papers from Department of Economics and Business Economics, Aarhus University
Bibliographic data for series maintained by ().