Evaluating CPB’s published GDP growth forecasts

Adam Elbourne (), Henk Kranendonk (), Rob Luginbuhl (), Bert Smid () and Martin Vromans ()

CPB Documents from CPB Netherlands Bureau for Economic Policy Analysis

Abstract: We compare the accuracy of our published GDP growth forecasts from our large macro model, SAFFIER, to those produced by VAR based models using both classical and Bayesian estimation techniques. We employ a data driven methodology for selecting variables to include in our VAR models and we find that a randomly selected classical VAR model performs worse in most cases than the Bayesian equivalent, which performs worse than our published forecasts in most cases. However, when we pool forecasts across many VARs we can produce more accurate forecasts than we published. A review of the literature suggests that forecast accuracy is likely irrelevant for the non-forecasting activities the model is used for at CPB because they are fundamentally different activities.

Keywords: SEMs; VAR models; Forecast combination; Bayesian methods; Real time (search for similar items in EconPapers)
JEL-codes: C52 C53 E37 (search for similar items in EconPapers)
New Economics Papers: this item is included in nep-cba, nep-for and nep-mac
Date: 2008-10
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Persistent link: http://EconPapers.repec.org/RePEc:cpb:docmnt:172

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