 When was the U.S. housing downturn predictable? A comparison of univariate forecasting methodsJoachim Zietz and Anca Traian The Quarterly Review of Economics and Finance, 2014, vol. 54, issue 2, 271-281 Abstract: This paper uses three classes of univariate time series techniques (ARIMA type models, switching regression models, and state-space/structural time series models) to forecast, on an ex post basis, the downturn in U.S. housing prices starting around 2006. The performance of the techniques is compared within each class and across classes by out-of-sample forecasts for a number of different forecast points prior to and during the downturn. Most forecasting models are able to predict a downturn in future home prices by mid 2006. Some state-space models can predict an impending downturn as early as June 2005. State-space/structural time series models tend to produce the most accurate forecasts, although they are not necessarily the models with the best in-sample fit. Keywords: Case-Shiller housing price index; Forecasting; ARIMA; Switching models; State space/structural time series models (search for similar items in EconPapers) Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:eee:quaeco:v:54:y:2014:i:2:p:271-281 DOI: 10.1016/j.qref.2013.12.004 Access Statistics for this article The Quarterly Review of Economics and Finance is currently edited by R. J. Arnould and J. E. Finnerty More articles in The Quarterly Review of Economics and Finance from Elsevier |
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