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Real-time Forecasting of Inflation and Output Growth in the Presence of Data Revisions

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  • Clements, Michael P.

    (University of Warwick)

  • Galvão, Ana Beatriz

    (Queen Mary University of London)

Abstract

We show how to improve the accuracy of real-time forecasts from models that include au-toregressive terms by estimating the models on ‘lightly-revised’data instead of using data from the latest-available vintage. Forecast accuracy is improved by reorganizing the data vintages employed in the estimation of the model in such a way that the vintages used in estimation are of a similar maturity to the data in the forecast loss function. The size of the expected reductions in mean squared error depend on the characteristics of the data revision process. Empirically, we …nd RMSFE gains of 2-4% when forecasting output growth and in‡ation with AR models, and gains of the order of 8% with ADL models.

Suggested Citation

  • Clements, Michael P. & Galvão, Ana Beatriz, 2010. "Real-time Forecasting of Inflation and Output Growth in the Presence of Data Revisions," The Warwick Economics Research Paper Series (TWERPS) 953, University of Warwick, Department of Economics.
    • Handle: RePEc:wrk:warwec:953
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    Cited by:

    1. Carlos A. Medel, 2013. "How informative are in-sample information criteria to forecasting? The case of Chilean GDP," Latin American Journal of Economics-formerly Cuadernos de Economía, Instituto de Economía. Pontificia Universidad Católica de Chile., vol. 50(1), pages 133-161, May.
    2. Clark, Todd & McCracken, Michael, 2013. "Advances in Forecast Evaluation," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 1107-1201, Elsevier.
    3. Clements Michael P., 2012. "Forecasting U.S. Output Growth with Non-Linear Models in the Presence of Data Uncertainty," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 16(1), pages 1-27, January.
    4. Christiane Baumeister & Lutz Kilian, 2011. "Real-Time Forecasts of the Real Price of Oil," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 30(2), pages 326-336, September.
    5. Michael P. Clements & Ana Beatriz Galvão, 2011. "Improving Real-time Estimates of Output Gaps and Inflation Trends with Multiple-vintage Models," Working Papers 678, Queen Mary University of London, School of Economics and Finance.
    6. Drechsel, Katja & Scheufele, Rolf, 2012. "The performance of short-term forecasts of the German economy before and during the 2008/2009 recession," International Journal of Forecasting, Elsevier, vol. 28(2), pages 428-445.
    7. Cecilia Frale & Valentina Raponi, 2011. "Revisions in ocial data and forecasting," Working Papers LuissLab 1194, Dipartimento di Economia e Finanza, LUISS Guido Carli.

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    Keywords

    real-time data ; news and noise revisions ; optimal forecasts ; multi-vintage models. JEL Classification: C53;
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