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Modelling and Forecasting Fiscal Variables for the euro Area

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  • Favero, Carlo A
  • Marcellino, Massimiliano

Abstract

In this paper we assess the possibility of producing unbiased forecasts for fiscal variables in the euro area by comparing a set of procedures that rely on different information sets and econometric techniques. In particular, we consider ARMA models, VARs, small scale semi-structural models at the national and euro area level, institutional forecasts (OECD), and pooling. Our small scale models are characterized by the joint modelling of fiscal and monetary policy using simple rules, combined with equations for the evolution of all the relevant fundamentals for the Maastricht Treaty and the Stability and Growth Pact. We rank models on the basis of their forecasting performance using the mean square and mean absolute error criteria at different horizons. Overall, simple time series methods and pooling work well and are able to deliver unbiased forecasts, or slightly upward biased forecast for the debt-GDP dynamics. This result is mostly due to the short sample available, the robustness of simple methods to structural breaks, and to the difficulty of modelling the joint behaviour of several variables in a period of substantial institutional and economic changes. A bootstrap experiment highlights that, even when the data are generated using the estimated small scale multi country model, simple time series models can produce more accurate forecasts, due to their parsimonious specification.

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Bibliographic Info

Paper provided by C.E.P.R. Discussion Papers in its series CEPR Discussion Papers with number 5294.

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Date of creation: Oct 2005
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Handle: RePEc:cpr:ceprdp:5294

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Keywords: euro area; fiscal forecasting; fiscal rules; forecast comparison;

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References

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  1. Roberto Perotti, 2002. "Estimating the effects of fiscal policy in OECD countries," Economics Working Papers 015, European Network of Economic Policy Research Institutes.
  2. Massimiliano Marcellino & James Stock & Mark Watson, 2005. "A Comparison of Direct and Iterated Multistep AR Methods for Forecasting Macroeconomic Time Series," Working Papers 285, IGIER (Innocenzo Gasparini Institute for Economic Research), Bocconi University.
  3. Clarida, R. & Gali, J. & Gertler, M., 1998. "Monetary Policy Rules and Macroeconomic Stability: Evidence and some Theory," Working Papers 98-01, C.V. Starr Center for Applied Economics, New York University.
  4. Lars Jonung & Martin Larch, 2006. "Improving fiscal policy in the EU: the case for independent forecasts," Economic Policy, CEPR & CES & MSH, vol. 21(47), pages 491-534, 07.
  5. Clements,Michael & Hendry,David, 1998. "Forecasting Economic Time Series," Cambridge Books, Cambridge University Press, number 9780521632423, December.
  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. Glenn Rudebusch & Lars E.O. Svensson, 1999. "Policy Rules for Inflation Targeting," NBER Chapters, in: Monetary Policy Rules, pages 203-262 National Bureau of Economic Research, Inc.
  8. Favero, Carlo A, 2002. "How do European Monetary and Fiscal Authorities Behave?," CEPR Discussion Papers 3426, C.E.P.R. Discussion Papers.
  9. Marcellino, Massimiliano, 2002. "Instability and Non-Linearity in the EMU," CEPR Discussion Papers 3312, C.E.P.R. Discussion Papers.
  10. Michael Artis & Massimiliano Marcellino & Tommaso Proietti, 2003. "Dating the Euro Area Business Cycle," Working Papers 237, IGIER (Innocenzo Gasparini Institute for Economic Research), Bocconi University.
  11. Marcellino, Massimiliano, 2002. "Forecast Pooling for Short Time Series of Macroeconomic Variables," CEPR Discussion Papers 3313, C.E.P.R. Discussion Papers.
  12. Massimiliano Marcellino, . "Forecasting EMU macroeconomic variables," Working Papers 216, IGIER (Innocenzo Gasparini Institute for Economic Research), Bocconi University.
  13. 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.
  14. Todd E. Clark & Michael W. McCracken, 2000. "Tests of Equal Forecast Accuracy and Encompassing for Nested Models," Econometric Society World Congress 2000 Contributed Papers 0319, Econometric Society.
  15. Francis X. Diebold & Robert S. Mariano, 1994. "Comparing Predictive Accuracy," NBER Technical Working Papers 0169, National Bureau of Economic Research, Inc.
  16. David Hendry & Michael Clements, 2001. "Pooling of Forecasts," Economics Series Working Papers 2002-W09, University of Oxford, Department of Economics.
  17. Perotti, Roberto, 2002. "Estimating the effects of fiscal policy in OECD countries," Working Paper Series 0168, European Central Bank.
  18. Banerjee, Anindya & Marcellino, Massimiliano & Masten, Igor, 2003. "Leading Indicators for Euro Area Inflation and GDP Growth," CEPR Discussion Papers 3893, C.E.P.R. Discussion Papers.
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Cited by:
  1. Teresa Leal & Javier J. Pérez & Mika Tujula & Jean-Pierre Vidal, 2008. "Fiscal Forecasting: Lessons from the Literature and Challenges," Fiscal Studies, Institute for Fiscal Studies, vol. 29(3), pages 347-386, 09.
  2. Fildes, Robert & Wei, Yingqi & Ismail, Suzilah, 2011. "Evaluating the forecasting performance of econometric models of air passenger traffic flows using multiple error measures," International Journal of Forecasting, Elsevier, vol. 27(3), pages 902-922, July.
  3. Henzel, Steffen R. & Mayr, Johannes, 2013. "The mechanics of VAR forecast pooling—A DSGE model based Monte Carlo study," The North American Journal of Economics and Finance, Elsevier, vol. 24(C), pages 1-24.
  4. Casadio, Paolo & Paradiso, Antonio & Rao, B. Bhaskara, 2011. "The dynamics of Italian public debt: Alternative paths for fiscal consolidation," MPRA Paper 30646, University Library of Munich, Germany.
  5. Kumar, Saten & Paradiso, Antonio, 2011. "Assessing Sustainability of the Irish Public Debt," MPRA Paper 35295, University Library of Munich, Germany.
  6. Steffen Henzel & Johannes Mayr, 2009. "The Virtues of VAR Forecast Pooling – A DSGE Model Based Monte Carlo Study," Ifo Working Paper Series Ifo Working Paper No. 65, Ifo Institute for Economic Research at the University of Munich.
  7. Nicholas Apergis & Arusha Cooray, 2013. "Forecasting fiscal variables: Only a strong growth plan can sustain the Greek austerity programs-Evidence from simultaneous and structural models," CAMA Working Papers 2013-25, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
  8. Marcellino, Massimiliano, 2006. "A Simple Benchmark for Forecasts of Growth and Inflation," CEPR Discussion Papers 6012, C.E.P.R. Discussion Papers.
  9. Todd E. Clark & Michael W. McCracken, 2006. "Forecasting of small macroeconomic VARs in the presence of instabilities," Research Working Paper RWP 06-09, Federal Reserve Bank of Kansas City.
  10. Todd E. Clark & Michael W. McCracken, 2008. "Averaging forecasts from VARs with uncertain instabilities," Working Papers 2008-030, Federal Reserve Bank of St. Louis.
  11. Hasko, Harri, 2007. "‘Some unpleasant fiscal arithmetic’: the role of monetary and fiscal policy in public debt dynamics since the 1970s," Research Discussion Papers 28/2007, Bank of Finland.
  12. Esposito, Piero & Paradiso, Antonio & Rao, B. Bhaskara, 2011. "The dynamics of Spanish public debt and sustainable paths for fiscal consolidation," MPRA Paper 32563, University Library of Munich, Germany.
  13. Mayr, Johannes, 2010. "Forecasting Macroeconomic Aggregates," Munich Dissertations in Economics 11140, University of Munich, Department of Economics.
  14. Esposito, Piero & Paradiso, Antonio & Rao, B. Bhaskara, 2011. "The dynamics of French public debt: Paths for fiscal consolidations," MPRA Paper 32564, University Library of Munich, Germany.

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