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Measuring Output Gap Uncertainty

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  • Garratt, Anthony
  • Mitchell, James
  • Vahey, Shaun

Abstract

We propose a methodology for producing density forecasts for the output gap in real time using a large number of vector autoregessions in inflation and output gap measures. Density combination utilizes a linear mixture of experts framework to produce potentially non-Gaussian ensemble densities for the unobserved output gap. In our application, we show that data revisions alter substantially our probabilistic assessments of the output gap using a variety of output gap measures derived from univariate detrending filters. The resulting ensemble produces well-calibrated forecast densities for US inflation in real time, in contrast to those from simple univariate autoregressions which ignore the contribution of the output gap. Combining evidence from both linear trends and more flexible univariate detrending filters induces strong multi-modality in the predictive densities for the unobserved output gap. The peaks associated with these two detrending methodologies indicate output gaps of opposite sign for some observations, reflecting the pervasive nature of model uncertainty in our US data.

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Bibliographic Info

Paper provided by C.E.P.R. Discussion Papers in its series CEPR Discussion Papers with number 7742.

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Date of creation: Mar 2010
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Handle: RePEc:cpr:ceprdp:7742

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Keywords: Density combination; Ensemble Forecasting; Output gap uncertainty; VAR models;

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References

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  1. Athanasios Orphanides & Simon van Norden, 2004. "The reliability of inflation forecasts based on output gap estimates in real time," Finance and Economics Discussion Series 2004-68, Board of Governors of the Federal Reserve System (U.S.).
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Citations

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Cited by:
  1. Guérin, Pierre & Maurin, Laurent & Mohr, Matthias, 2011. "Trend-cycle decomposition of output and euro area inflation forecasts: a real-time approach based on model combination," Working Paper Series 1384, European Central Bank.
  2. Juan Manuel Julio, 2011. "Data Revisions and the Output Gap," BORRADORES DE ECONOMIA 007956, BANCO DE LA REPÚBLICA.
  3. Massimiliano Marcellino & Alberto Musso, 2010. "The Forecasting Performance of Real Time Estimates of the EURO Area Output Gap," Economics Working Papers ECO2010/15, European University Institute.
  4. 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.
  5. Paulo Mauricio Sánchez Beltrán & Luis Fernando Melo Velandia, 2013. "Combinación de brechas del producto colombiano," Borradores de Economia 775, Banco de la Republica de Colombia.
  6. Knut Are Aastveit & Karsten R. Gerdrup & Anne Sofie Jore & Leif Anders Thorsrud, 2011. "Nowcasting GDP in Real-Time: A Density Combination Approach," Working Papers 0003, Centre for Applied Macro- and Petroleum economics (CAMP), BI Norwegian Business School.
  7. Francesco Ravazzolo & Shaun P Vahey, 2010. "Measuring Core Inflation in Australia with Disaggregate Ensembles," RBA Annual Conference Volume, in: Renée Fry & Callum Jones & Christopher Kent (ed.), Inflation in an Era of Relative Price Shocks Reserve Bank of Australia.

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