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

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

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Year of publication:	2014
Authors:	Bork, Lasse
Other Persons:	Møller, Stig Vinther (contributor)
Publisher:	[2014]: [S.l.] : SSRN
Subject:	Immobilienpreis \| Real estate price \| Dynamische Wirtschaftstheorie \| Economic dynamics \| Prognoseverfahren \| Forecasting model \| Zeitreihenanalyse \| Time series analysis \| Modellierung \| Scientific modelling \| Großbritannien \| United Kingdom

Extent:	1 Online-Ressource (44 p)
Type of publication:	Book / Working Paper
Language:	English
Notes:	In: International Journal of Forecasting, Forthcoming Nach Informationen von SSRN wurde die ursprüngliche Fassung des Dokuments February 01, 2014 erstellt
Other identifiers:	10.2139/ssrn.2473468 [DOI]
Classification:	C51 - Model Construction and Estimation ; C52 - Model Evaluation and Testing ; G1 - General Financial Markets ; E3 - Prices, Business Fluctuations, and Cycles
Source:	ECONIS - Online Catalogue of the ZBW

Persistent link: https://www.econbiz.de/10013050052