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Combining Forecast Densities from VARs with Uncertain Instabilities

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  • Dr. James Mitchell

Abstract

Recursive-weight forecast combination is often found to an ineffective method of improving point forecast accuracy in the presence of uncertain instabilities. We examine the effectiveness of this strategy for forecast densities using (many) VARs and ARs of output growth, inflation and interest rates. Our proposed recursiveweight density combination strategy, based on the recursive logarithmic score of the forecast densities, produces well-calibrated predictive densities for US real-time data by giving substantial weight to models that allow for structural breaks. In contrast, equal-weight combinations produce poorly-calibrated forecast densities for Great Moderation data.

Suggested Citation

  • Dr. James Mitchell, 2008. "Combining Forecast Densities from VARs with Uncertain Instabilities," National Institute of Economic and Social Research (NIESR) Discussion Papers 303, National Institute of Economic and Social Research.
    • Handle: RePEc:nsr:niesrd:303
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    Cited by:

    1. Wagner Piazza Gaglianone & Luiz Renato Lima, 2014. "Constructing Optimal Density Forecasts From Point Forecast Combinations," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 29(5), pages 736-757, August.
    2. Anne Sofie Jore & James Mitchell & Shaun P. Vahey, 2010. "Combining forecast densities from VARs with uncertain instabilities," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 25(4), pages 621-634.
    3. Garratt, Anthony & Mitchell, James & Vahey, Shaun P. & Wakerly, Elizabeth C., 2011. "Real-time inflation forecast densities from ensemble Phillips curves," The North American Journal of Economics and Finance, Elsevier, vol. 22(1), pages 77-87, January.
    4. Anthony Garratt & James Mitchell & Shaun P. Vahey, 2009. "Measuring Output Gap Uncertainty," Birkbeck Working Papers in Economics and Finance 0909, Birkbeck, Department of Economics, Mathematics & Statistics.
    5. Rossi, Barbara, 2013. "Advances in Forecasting under Instability," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 1203-1324, Elsevier.
    6. Francesco Ravazzolo & Shaun P Vahey, 2010. "Measuring Core Inflation in Australia with Disaggregate Ensembles," RBA Annual Conference Volume (Discontinued), in: Renée Fry & Callum Jones & Christopher Kent (ed.),Inflation in an Era of Relative Price Shocks, Reserve Bank of Australia.
    7. Filippo di Mauro & Filippo di Mauro, Fabio Fornari, 2014. "Going granular: The importance of firm-level equity information in anticipating economic activity," EcoMod2014 6809, EcoMod.

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