The accession of ten countries into the European Union makes the forecasting of their key macroeconomic indicators such as GDP growth, inflation and interest rates an exercise of some importance. Because of the transition period, only short spans of reliable time series are available which suggests the adoption of simple time series models as forecasting tools, because of their parsimonious specification and good performance. Nevertheless, despite this constraint on the span of data, a large number of macroeconomic variables (for a given time span) are available which are of potential use in forecasting, making the class of dynamic factor models a reasonable alternative forecasting tool. We compare the relative performance of the two forecasting approaches, first by means of simulation experiments and then by using data for five Acceding countries. We also evaluate the role of Euro-area information for forecasting, and the usefulness of robustifying techniques such as intercept corrections and second differencing. We find that factor models work well in general, even though there are marked differences across countries. Robustifying techniques are useful in a few cases, while Euro-area information is virtually irrelevant.
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Paper provided by IGIER (Innocenzo Gasparini Institute for Economic Research), Bocconi University in its series Working Papers with number
260.
Length: Date of creation: 2004 Date of revision: Handle: RePEc:igi:igierp:260
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References listed on IDEAS Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
James H. Stock & Mark W. Watson, 1998.
"Diffusion Indexes,"
NBER Working Papers
6702, National Bureau of Economic Research, Inc.
[Downloadable!] (restricted)
James H. Stock & Mark W. Watson, 1999.
"Forecasting Inflation,"
NBER Working Papers
7023, National Bureau of Economic Research, Inc.
[Downloadable!] (restricted)
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