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Forecasting EMU macroeconomic variables

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Massimiliano Marcellino

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Abstract

After the creation of the European Monetary Union (EMU), both the European Commission (EC) and the European Central Bank (ECB) are focusing more and more on the evolution of the EMU as a whole, rather than on single member countries. A particularly relevant issue from a policy point of view is the availability of reliable forecasts for the key macroeconomic variables. Hence, both the fiscal and the monetary authorities have developed aggregate forecasting models, along the lines previously adopted for the analysis of single countries. A similar approach will be likely followed in empirical analyses on, e.g., the existence of an aggregate Taylor rule or the evaluation of the aggregate impact of monetary policy shocks, where linear specifications are usually adopted. Yet, it is uncertain whether standard linear models provide the proper statistical framework to address these issues. The process of aggregation across countries can produce smoother series, better suited for the analysis with linear models, by averaging out country specific shocks. But the method of construction of the aggregate series, which often involves time-varying weights, and the presence of common shocks across the countries, such as the deflation in the early 1980s and the convergence process in the early 1990s, can introduce substantial non-linearity into the generating process of the aggregate series. To evaluate whether this is the case, we fit a variety of non-linear and time-varying models to aggregate EMU macroeconomic variables, and compare them with linear specifications. Since non-linear models often over-fit in sample, we assess their performance in a real time forecasting framework. It turns out that for several variables linear models are beaten by non-linear specifications, a result that questions the use of standard linear methods for forecasting and modeling EMU variables.

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Paper provided by IGIER (Innocenzo Gasparini Institute for Economic Research), Bocconi University in its series Working Papers with number 216.

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  3. Rudiger Dornbusch & Carlo A. Favero & Francesco Giavazzi, 1998. "The Immediate Challenges for the European Central Bank," NBER Working Papers 6369, National Bureau of Economic Research, Inc. [Downloadable!] (restricted)
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  6. Norman R. Swanson & Halbert White, 1997. "A Model Selection Approach To Real-Time Macroeconomic Forecasting Using Linear Models And Artificial Neural Networks," The Review of Economics and Statistics, MIT Press, vol. 79(4), pages 540-550, November. [Downloadable!] (restricted)
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  9. Fagan, Gabriel & Henry, Jerome & Mestre, Ricardo, 2005. "An area-wide model for the euro area," Economic Modelling, Elsevier, vol. 22(1), pages 39-59, January. [Downloadable!] (restricted)
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  11. Marcellino, Massimiliano, 2002. "Forecast Pooling for Short Time Series of Macroeconomic Variables," CEPR Discussion Papers 3313, C.E.P.R. Discussion Papers. [Downloadable!] (restricted)
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  12. Elliott, Graham & Rothenberg, Thomas J & Stock, James H, 1996. "Efficient Tests for an Autoregressive Unit Root," Econometrica, Econometric Society, vol. 64(4), pages 813-36, July. [Downloadable!] (restricted)
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  16. 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. [Downloadable!] (restricted)
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  21. Stock, James H & Watson, Mark W, 1996. "Evidence on Structural Instability in Macroeconomic Time Series Relations," Journal of Business & Economic Statistics, American Statistical Association, vol. 14(1), pages 11-30, January.
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  22. Gerlach, Stefan & Schnabel, Gert, 2000. "The Taylor rule and interest rates in the EMU area," Economics Letters, Elsevier, vol. 67(2), pages 165-171, May. [Downloadable!] (restricted)
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  23. Stock, James H, 1996. "VAR, Error Correction and Pretest Forecasts at Long Horizons," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 58(4), pages 685-701, November.
  24. Rudi Dornbusch & Carlo Favero & Francesco Giavazzi, 1998. "Immediate challenges for the European Central Bank," Economic Policy, CEPR, CES, MSH, vol. 13(26), pages 15-64, 04. [Downloadable!] (restricted)
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Cited by:
(explanations, 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.)

  1. Anindya Banerjee & Massimiliano Marcellino & Igor Masten, . "Leading Indicators for Euro-area Inflation and GDP Growth," Working Papers 235, IGIER (Innocenzo Gasparini Institute for Economic Research), Bocconi University. [Downloadable!]
    Other versions:
  2. Favero, Carlo A & Marcellino, Massimiliano, 2005. "Modelling and Forecasting Fiscal Variables for the euro Area," CEPR Discussion Papers 5294, C.E.P.R. Discussion Papers. [Downloadable!] (restricted)
    Other versions:
  3. B. Siliverstovs & D.J. Van Dijk, 2003. "Forecasting industrial production with linear, nonlinear and structural change models," Econometric Institute Report 321, Erasmus University Rotterdam, Econometric Institute. [Downloadable!]
  4. Ralf Brüggemann & Helmut Lütkepohl & Massimiliano Marcellino, 2006. "Forecasting Euro-Area Variables with German Pre-EMU Data," SFB 649 Discussion Papers SFB649DP2006-065, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany. [Downloadable!]
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  5. Teräsvirta, Timo, 2005. "Forecasting economic variables with nonlinear models," Working Paper Series in Economics and Finance 598, Stockholm School of Economics, revised 29 Dec 2005. [Downloadable!]
    Other versions:
  6. A.H.J. den Reijer & P.J.G. Vlaar, 2003. "Forecasting Inflation in the Netherlands and the Euro Area," WO Research Memoranda (discontinued) 723, Netherlands Central Bank, Research Department. [Downloadable!]
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