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Forecasting Euro-Area Macroeconomic Variables Using a Factor Model Approach for Backdating

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Author Info

  • Ralf Brüggemann

    (University of Konstanz, Department Economics, Germany)

  • Jing Zeng

    () (University of Konstanz, Department Economics, Germany)

Abstract

We suggest to use a factor model based backdating procedure to construct historical Euro-area macroeconomic time series data for the pre-Euro period. We argue that this is a useful alternative to standard contemporaneous aggregation methods. The paper investigates for a number of Euro-area variables whether forecasts based on the factor-backdated data are more precise than those obtained with standard area-wide data. A recursive pseudo-out-of-sample forecasting experiment using quarterly data is conducted. Our results suggest that some key variables (e.g. real GDP, inflation and long-term interest rate) can indeed be forecasted more precisely with the factor-backdated data.

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Bibliographic Info

Paper provided by Department of Economics, University of Konstanz in its series Working Paper Series of the Department of Economics, University of Konstanz with number 2012-15.

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Length: 31 pages
Date of creation: 02 Aug 2012
Date of revision:
Handle: RePEc:knz:dpteco:1215

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Related research

Keywords: forecasting; factor model; backdating; European monetary union; constructing EMU data;

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References

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  1. Beyer, A. & Doornik, J.A. & Hendry, D.F., 2000. "Constructing Historical Euro-Zone Data," Economics Working Papers eco2000/10, European University Institute.
  2. Elena Angelini & Jerome Henry & Massimiliano Marcellino, 2003. "Interpolation and backdating with a large information set," Working Paper Series 252, European Central Bank.
  3. Jushan Bai & Serena Ng, 2000. "Determining the Number of Factors in Approximate Factor Models," Boston College Working Papers in Economics 440, Boston College Department of Economics.
  4. Clements, Michael P & Hendry, David F, 1996. "Multi-step Estimation for Forecasting," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 58(4), pages 657-84, November.
  5. Marcellino, Massimliano, 2004. "Forecasting EMU macroeconomic variables," International Journal of Forecasting, Elsevier, vol. 20(2), pages 359-372.
  6. 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.
  7. Jean Boivin & Serena Ng, 2003. "Are More Data Always Better for Factor Analysis?," NBER Working Papers 9829, National Bureau of Economic Research, Inc.
  8. Helmut Lütkepohl & Ralf Brüggemann, 2006. "A small monetary system for the euro area based on German data," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 21(6), pages 683-702.
  9. Bosker, E.M., 2006. "On the aggregation of eurozone data," Economics Letters, Elsevier, vol. 90(2), pages 260-265, February.
  10. Andreas Beyer & Katarina Juselius, 2008. "Does it Matter How to Measure Aggregates? The Case of Monetary Transmission Mechanisms in the Euro Area," Discussion Papers 08-07, University of Copenhagen. Department of Economics.
  11. Elena Angelini & Massimiliano Marcellino, 2007. "Econometric analyses with backdated data - unified Germany and the euro area," Working Paper Series 752, European Central Bank.
  12. Granger, Clive W. J. & Terasvirta, Timo, 1993. "Modelling Non-Linear Economic Relationships," OUP Catalogue, Oxford University Press, number 9780198773207, September.
  13. 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.
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