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Forecasting Macroeconomic Variables for the Acceding Countries

  • Anindya Banerjee
  • Massimiliano Marcellino
  • Igor Masten

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.

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Date of creation: 2004
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Handle: RePEc:igi:igierp:260
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  1. Angelini, Elena & Henry, Jérôme & Marcellino, Massimiliano, 2004. "Interpolation and Backdating with A Large Information Set," CEPR Discussion Papers 4533, C.E.P.R. Discussion Papers.
  2. Artis, Michael J & Marcellino, Massimiliano & Proietti, Tommaso, 2004. "Characterizing the Business Cycle for Accession Countries," CEPR Discussion Papers 4457, C.E.P.R. Discussion Papers.
  3. Marcellino, Massimiliano, 2000. " Forecast Bias and MSFE Encompassing," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 62(4), pages 533-42, September.
  4. Fagan, Gabriel & Henry, Jérôme & Mestre, Ricardo, 2001. "An area-wide model (AWM) for the euro area," Working Paper Series 0042, European Central Bank.
  5. James H. Stock & Mark W. Watson, 1999. "Forecasting Inflation," NBER Working Papers 7023, National Bureau of Economic Research, Inc.
  6. Michael Artis & Massimiliano Marcellino, 2001. "Fiscal forecasting: The track record of the IMF, OECD and EC," Econometrics Journal, Royal Economic Society, vol. 4(1), pages S20-S36.
  7. Ben S. Bernanke & Jean Boivin, 2001. "Monetary Policy in a Data-Rich Environment," NBER Working Papers 8379, National Bureau of Economic Research, Inc.
  8. Stock J.H. & Watson M.W., 2002. "Forecasting Using Principal Components From a Large Number of Predictors," Journal of the American Statistical Association, American Statistical Association, vol. 97, pages 1167-1179, December.
  9. James H. Stock & Mark W. Watson, 1998. "Diffusion Indexes," NBER Working Papers 6702, National Bureau of Economic Research, Inc.
  10. Marcellino, Massimiliano & Stock, James H. & Watson, Mark W., 2003. "Macroeconomic forecasting in the Euro area: Country specific versus area-wide information," European Economic Review, Elsevier, vol. 47(1), pages 1-18, February.
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  12. James H. Stock & Mark W. Watson, 1988. "A Probability Model of The Coincident Economic Indicators," NBER Working Papers 2772, National Bureau of Economic Research, Inc.
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