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Combining VAR and DSGE forecast densities

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  • Wolden Bache, Ida
  • Sofie Jore, Anne
  • Mitchell, James
  • Vahey, Shaun P.

Abstract

A popular macroeconomic forecasting strategy utilizes 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 use the linear opinion pool to combine inflation forecast densities from many vector autoregressions (VARs) and a policymaking DSGE model. The DSGE receives a substantial weight in the pool (at 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, but produces well-calibrated forecast densities for inflation.

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Bibliographic Info

Article provided by Elsevier in its journal Journal of Economic Dynamics and Control.

Volume (Year): 35 (2011)
Issue (Month): 10 (October)
Pages: 1659-1670

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Handle: RePEc:eee:dyncon:v:35:y:2011:i:10:p:1659-1670

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Web page: http://www.elsevier.com/locate/jedc

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

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References

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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. Wolters, Maik Hendrik, 2012. "Evaluating point and density forecasts of DSGE models," MPRA Paper 36147, University Library of Munich, Germany.
  2. 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.
  3. 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.
  4. 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.
  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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