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Forecasting Data Vintages

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  • Tara M. Sinclair

    () (George Washington University)

Abstract

This article provides a discussion of Clements and Galvão’s “Forecasting with Vector Autoregressive Models of Data Vintages: US output growth and inflation.” Clements and Galvão argue that a multiple-vintage VAR model can be useful for forecasting data that are subject to revisions. Clements and Galvão draw a “distinction between forecasting future observations and revisions to past data,” which brings yet another real time data issue to the attention of forecasters. This comment discusses the importance of taking data revisions into consideration and compares the multiple-vintage VAR approach of Clements and Galvão to a state-space approach.

Suggested Citation

  • Tara M. Sinclair, 2012. "Forecasting Data Vintages," Working Papers 2012-001, The George Washington University, Department of Economics, Research Program on Forecasting.
  • Handle: RePEc:gwc:wpaper:2012-001
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    File URL: https://www2.gwu.edu/~forcpgm/2012-001.pdf
    File Function: First version, 2012
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    References listed on IDEAS

    as
    1. Evan F. Koenig & Sheila Dolmas & Jeremy Piger, 2003. "The Use and Abuse of Real-Time Data in Economic Forecasting," The Review of Economics and Statistics, MIT Press, vol. 85(3), pages 618-628, August.
    2. N. Kundan Kishor & Evan F. Koenig, 2009. "VAR Estimation and Forecasting When Data Are Subject to Revision," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 30(2), pages 181-190, July.
    Full references (including those not matched with items on IDEAS)

    More about this item

    Keywords

    Real time data; Evaluating forecasts; Forecasting practice; Time series; Econometric models;

    JEL classification:

    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods

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