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Journal Article

Forecasting data revisions of GDP: a mixed frequency approach

Authors

  • Boysen-Hogrefe
  • J.

Publication Date

Key Words

Data revisions - GDP - Real-time data - Mixed frequency - Factor model

Releases of GDP data undergo a series of revisions over time. These revisions have an impact on the results of macroeconometric models documented by the growing literature on real-time data applications. Revisions of U.S. GDP data can be explained and are partly predictable according to Faust et al. (J. Money Credit Bank. 37(3):403–419, 2005) or Fixler and Grimm (J. Product. Anal. 25:213–229, 2006). This analysis proposes the inclusion of mixed frequency data for forecasting GDP revisions. Thereby, the information set available around the first data vintage can be better exploited than the pure quarterly data. In-sample and out-of-sample results suggest that forecasts of GDP revisions can be improved by using mixed frequency data.

Kiel Institute Expert

  • Prof. Dr. Jens Boysen-Hogrefe
    Kiel Institute Researcher

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