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VAR estimation and forecasting when data are subject to revision

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  • N. Kundan Kishor
  • Evan F. Koenig

Abstract

Conventional VAR estimation and forecasting ignores the fact that economic data are often subject to revision many months or years after their initial release. This paper shows how VAR analysis can be modified to account for such revisions. The proposed approach assumes that government statistical releases are efficient with a finite lag. It takes no stand on whether earlier revisions are ?noise? or ?news.? The technique is illustrated using data on employment and the unemployment rate, real GDP and the unemployment rate, and real GDP and the GDP/consumption ratio. In each case, the proposed procedure outperforms conventional VAR analysis and the more-restrictive methods for handling the data-revision problem that are found in the existing literature.

Suggested Citation

  • N. Kundan Kishor & Evan F. Koenig, 2005. "VAR estimation and forecasting when data are subject to revision," Working Papers 0501, Federal Reserve Bank of Dallas.
    • Handle: RePEc:fip:feddwp:05-01
    Note: Published as: Kishor, N. Kundan and Evan F. Koenig (2012), "VAR Estimation and Forecasting When Data Are Subject to Revision," Journal of Business and Economic Statistics 30 (2): 181-190.
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