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Forecasting with vector autoregressive models of data vintages : US output growth and inflation

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Clements, Michael P. and Galvão, Ana Beatriz (2012) Forecasting with vector autoregressive models of data vintages : US output growth and inflation. International Journal of Forecasting . ISSN 0169-2070 (In Press)

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Official URL: http://dx.doi.org/10.1016/j.ijforecast.2011.09.003

Abstract

Vintage-based vectorautoregressivemodels of a single macroeconomic variable are shown to be a useful vehicle for obtaining forecasts of different maturities of future and past observations, including estimates of post-revision values. The forecasting performance of models which include information on annual revisions is superior to that of models which only include the first two data releases. However, the empirical results indicate that a model which reflects the seasonal nature of data releases more closely does not offer much improvement over an unrestricted vintage-based model which includes three rounds of annual revisions.

Item Type: Submitted Journal Article
Subjects: H Social Sciences > HB Economic Theory
H Social Sciences > HC Economic History and Conditions
Divisions: Faculty of Social Sciences > Economics
Journal or Publication Title: International Journal of Forecasting
Publisher: Elsevier
ISSN: 0169-2070
Date: 2012
Identification Number: 10.1016/j.ijforecast.2011.09.003
Status: Peer Reviewed
Publication Status: In Press
Access rights to Published version: Restricted or Subscription Access
Description: Forthcoming - In press, corrected proof
URI: http://wrap.warwick.ac.uk/id/eprint/44603

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