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Forecasting euro area variables with German pre-EMU data

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  • Ralf Brüggemann

    (Lehrstuhl für Statistik und Ökonometrie, Universität Konstanz, Konstanz, Germany)

  • Helmut Lütkepohl

    (Department of Economics, European University Institute, Florence, Italy)

  • Massimiliano Marcellino

    (Bocconi University, Milan, Italy)

Abstract

It is investigated whether euro area variables can be forecast better based on synthetic time series for the pre-euro period or by using just data from Germany for the pre-euro period. Our forecast comparison is based on quarterly data for the period 1970Q1-2003Q4 for 10 macroeconomic variables. The years 2000-2003 are used as forecasting period. A range of different univariate forecasting methods is applied. Some of them are based on linear autoregressive models and we also use some nonlinear or time-varying coefficient models. It turns out that most variables which have a similar level for Germany and the euro area such as prices can be better predicted based on German data, while aggregated European data are preferable for forecasting variables which need considerable adjustments in their levels when joining German and European Monetary Union (EMU) data. These results suggest that for variables which have a similar level for Germany and the euro area it may be reasonable to consider the German pre-EMU data for studying economic problems in the euro area. Copyright © 2008 John Wiley & Sons, Ltd.

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File URL: http://hdl.handle.net/10.1002/for.1064
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Bibliographic Info

Article provided by John Wiley & Sons, Ltd. in its journal Journal of Forecasting.

Volume (Year): 27 (2008)
Issue (Month): 6 ()
Pages: 465-481

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Handle: RePEc:jof:jforec:v:27:y:2008:i:6:p:465-481

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Web page: http://www3.interscience.wiley.com/cgi-bin/jhome/2966

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Cited by:
  1. Stelios Bekiros & Alessia Paccagnini, 2013. "On the predictability of time-varying VAR and DSGE models," Empirical Economics, Springer, vol. 45(1), pages 635-664, August.
  2. Heather Anderson & Mardi Dungey & Denise Osborn & Farshid Vahid, 2007. "Constructing Historical Euro Area Data," Money Macro and Finance (MMF) Research Group Conference 2006 99, Money Macro and Finance Research Group.
  3. Bekiros, Stelios D. & Paccagnini, Alessia, 2014. "Bayesian forecasting with small and medium scale factor-augmented vector autoregressive DSGE models," Computational Statistics & Data Analysis, Elsevier, vol. 71(C), pages 298-323.
  4. Amisano, Gianni & Fagan, Gabriel, 2010. "Money growth and inflation: a regime switching approach," Working Paper Series 1207, European Central Bank.
  5. Ralf Brüggemann & Jing Zeng, 2012. "Forecasting Euro-Area Macroeconomic Variables Using a Factor Model Approach for Backdating," Working Paper Series of the Department of Economics, University of Konstanz 2012-15, Department of Economics, University of Konstanz.
  6. Helmut Lütkepohl, 2010. "Forecasting Aggregated Time Series Variables: A Survey," OECD Journal: Journal of Business Cycle Measurement and Analysis, OECD Publishing,CIRET, vol. 2010(2), pages 1-26.
  7. Gianni Amisano & Roberta Colavecchio, 2013. "Money Growth and Inflation: evidence from a Markov Switching Bayesian VAR," Macroeconomics and Finance Series 201304, Hamburg University, Department Wirtschaft und Politik.

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