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Combining VAR and DSGE forecast densities

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Author Info

  • Ida Wolden Bache

    () (Norges Bank)

  • Anne Sofie Jore

    () (Norges Bank)

  • James Mitchell

    (NIESR)

  • Shaun P. Vahey

    (Melbourne Business School)

Abstract

A popular macroeconomic forecasting strategy takes combinations across many models to hedge against instabilities of unknown timing; see (among others) Stock and Watson (2004), Clark and McCracken (2010), and Jore et al. (2010). Existing studies of this forecasting strategy exclude Dynamic Stochastic General Equilibrium (DSGE) models, despite the widespread use of these models by monetary policymakers. In this paper, we combine inflation forecast densities utilizing an ensemble system comprising many Vector Autoregressions (VARs), and a policymaking DSGE model. The DSGE receives substantial weight (for short horizons) provided the VAR components exclude structural breaks. In this case, the inflation forecast densities exhibit calibration failure. Allowing for structural breaks in the VARs reduces the weight on the DSGE considerably, and produces well-calibrated forecast densities for inflation.

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Bibliographic Info

Paper provided by Norges Bank in its series Working Paper with number 2009/23.

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Length: 24 pages
Date of creation: 05 Nov 2009
Date of revision:
Handle: RePEc:bno:worpap:2009_23

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Related research

Keywords: Ensemble modeling; Forecast densities; Forecast evaluation; VAR models; DSGE models;

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References

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  1. Todd E. Clark & Michael W. McCracken, 2007. "Averaging forecasts from VARs with uncertain instabilities," Finance and Economics Discussion Series 2007-42, Board of Governors of the Federal Reserve System (U.S.).
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Citations

Blog mentions

As found by EconAcademics.org, the blog aggregator for Economics research:
  1. DSGE models and forecasting
    by Christian Zimmermann in NEP-DGE blog on 2009-12-21 00:35:25
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Cited by:
  1. Knut Are Aastveit & Karsten R. Gerdrup & Anne Sofie Jore & Leif Anders Thorsrud, 2011. "Nowcasting GDP in real-time: A density combination approach," Working Paper 2011/11, Norges Bank.
  2. Wolters, Maik Hendrik, 2012. "Evaluating point and density forecasts of DSGE models," MPRA Paper 36147, University Library of Munich, Germany.
  3. Periklis Gogas & Theophilos Papadimitriou & Elvira Takli, 2013. "Comparison of Simple Sum and Divisia Monetary Aggregates in GDP Forecasting: A Support Vector Machines Approach," Working Paper Series 04_13, The Rimini Centre for Economic Analysis.
  4. Wolters, Maik H., 2011. "Forecasting under Model Uncertainty," Annual Conference 2011 (Frankfurt, Main): The Order of the World Economy - Lessons from the Crisis 48723, Verein für Socialpolitik / German Economic Association.
  5. Jakub Ryšánek, 2010. "Combining VAR Forecast Densities Using Fast Fourier Transform," Acta Oeconomica Pragensia, University of Economics, Prague, vol. 2010(5), pages 72-88.

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