Housing Price Forecastability: A Factor Analysis

30 Pages Posted: 20 Aug 2018

See all articles by Lasse Bork

Lasse Bork

Aalborg University - Department of Business and Management

Stig Vinther Møller

Aarhus University - CREATES

Multiple version iconThere are 2 versions of this paper

Date Written: Autumn 2018

Abstract

We examine U.S. housing price forecastability using principal component analysis (PCA), partial least squares (PLS) and sparse PLS (SPLS). We incorporate information from a large panel of 128 economic time series and show that macroeconomic fundamentals have strong predictive power for future movements in housing prices. We find that (S)PLS models systematically dominate PCA models. (S)PLS models also generate significant out‐of‐sample predictive power over and above the predictive power contained by the price–rent ratio, autoregressive benchmarks and regression models based on small datasets.

Suggested Citation

Bork, Lasse and Møller, Stig Vinther, Housing Price Forecastability: A Factor Analysis (Autumn 2018). Real Estate Economics, Vol. 46, Issue 3, pp. 582-611, 2018. Available at SSRN: https://ssrn.com/abstract=3233273 or http://dx.doi.org/10.1111/1540-6229.12185

Lasse Bork (Contact Author)

Aalborg University - Department of Business and Management ( email )

Aalborg, DK-9220
Denmark
+45 9940 2707 (Phone)

HOME PAGE: http://personprofil.aau.dk/profil/123645?lang=en

Stig Vinther Møller

Aarhus University - CREATES ( email )

Nordre Ringgade 1
Aarhus, DK-8000
Denmark

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