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Forecasting Macroeconomic Variables for the Acceding Countries

Author

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  • Anindya Banerjee
  • Massimiliano Marcellino
  • Igor Masten

Abstract

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.

Suggested Citation

  • Anindya Banerjee & Massimiliano Marcellino & Igor Masten, 2004. "Forecasting Macroeconomic Variables for the Acceding Countries," Working Papers 260, IGIER (Innocenzo Gasparini Institute for Economic Research), Bocconi University.
  • Handle: RePEc:igi:igierp:260
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    References listed on IDEAS

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    Cited by:

    1. Anindya Banerjee & Massimiliano Marcellino & Igor Masten, 2008. "Forecasting Macroeconomic Variables Using Diffusion Indexes in Short Samples with Structural Change," Working Papers 334, IGIER (Innocenzo Gasparini Institute for Economic Research), Bocconi University.
    2. Anindya Banerjee & Victor Bystrov & Paul Mizen, 2010. "Interest rate pass-through in the major European economies - the role of expectations," Discussion Papers 10-07, Department of Economics, University of Birmingham.
    3. Angelini, Elena & Henry, Jerome & Marcellino, Massimiliano, 2006. "Interpolation and backdating with a large information set," Journal of Economic Dynamics and Control, Elsevier, vol. 30(12), pages 2693-2724, December.
    4. O. De Bandt & E. Michaux & C. Bruneau & A. Flageollet, 2007. "Forecasting inflation using economic indicators: the case of France," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 26(1), pages 1-22.
    5. Christian Schulz, 2008. "Forecasting economic activity for Estonia : The application of dynamic principal component analyses," Bank of Estonia Working Papers 2008-02, Bank of Estonia, revised 30 Oct 2008.
    6. Victor Bystrov, 2006. "Forecasting Emerging Market Indicators: Brazil and Russia," Economics Working Papers ECO2006/12, European University Institute.
    7. Harm Bandholz, 2005. "New Composite Leading Indicators for Hungary and Poland," ifo Working Paper Series 3, ifo Institute - Leibniz Institute for Economic Research at the University of Munich.

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