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Modelling and Forecasting Fiscal Variables for the Euro Area

  • Carlo A. Favero
  • Massimiliano Marcellino

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 autoregressive moving average models, Vector autoregressions, small-scale semistructural models at the national and Euro area level, institutional forecasts (Organization for Economic Co-operation and Development), 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, because of their parsimonious specification. Copyright 2005 Blackwell Publishing Ltd.

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Article provided by Department of Economics, University of Oxford in its journal Oxford Bulletin of Economics & Statistics.

Volume (Year): 67 (2005)
Issue (Month): s1 (December)
Pages: 755-783

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Handle: RePEc:bla:obuest:v:67:y:2005:i:s1:p:755-783
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  1. 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.
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