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Forecasting House Prices in the 50 States Using Dynamic Model Averaging and Dynamic Model Selection

44 Pages Posted: 29 Jul 2014  

Lasse Bork

Aalborg University - Department of Business and Management

Stig Vinther Møller

University of Aarhus - CREATES

Date Written: February 01, 2014

Abstract

We examine house price forecastability across the 50 states using Dynamic Model Averaging and Dynamic Model Selection, which allow for model change and parameter shifts. By allowing the entire forecasting model to change over time and across locations, the forecasting accuracy improves substantially. The states in which housing markets have been the most volatile are the states where model change and parameter shifts have been the most needed.

Keywords: Forecasting housing markets, 50 states, Kalman filtering methods, Model change, Parameter shifts, Boom-bust cycle, Model averaging, Model selection

JEL Classification: C51, C52, G1, E3

Suggested Citation

Bork, Lasse and Møller, Stig Vinther, Forecasting House Prices in the 50 States Using Dynamic Model Averaging and Dynamic Model Selection (February 01, 2014). International Journal of Forecasting, Forthcoming. Available at SSRN: https://ssrn.com/abstract=2473468 or http://dx.doi.org/10.2139/ssrn.2473468

Lasse Bork

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 (Contact Author)

University of Aarhus - CREATES ( email )

Nordre Ringgade 1
Aarhus, DK-8000
Denmark

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