Forecasting with vector autoregressive models of data vintages : US output growth and inflation
Clements, Michael P. and Galvão, Ana Beatriz. (2013) Forecasting with vector autoregressive models of data vintages : US output growth and inflation. International Journal of Forecasting, 29 (4). pp. 698-714. ISSN 0169-2070 (In Press)Full text not available from this repository.
Official URL: http://dx.doi.org/10.1016/j.ijforecast.2011.09.003
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:||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|
|Page Range:||pp. 698-714|
|Publication Status:||In Press|
|Access rights to Published version:||Restricted or Subscription Access|
In press, corrected proof
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