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Estimation of the TFP Gap for the Largest Five EMU Countries

Author

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  • Kai Carstensen
  • Felix Kießner
  • Thies Rossian

Abstract

In this paper we augment the Bayesian unobserved components model of the EU Commission to estimate the cyclical component of total factor productivity (TFP gap) with a factor structure to include a wide array of business cycle indicators. We demonstrate that this model extension considerably stabilizes the estimate of the of the TFP gap. Specifically, consider the usual autumn forecast of the EU Commission in October of a year T. For the last two “in-sample” years T − 2 and T − 1, and for the “now-cast” year T, the year-to-year revisions can be reduced by up to 30 percent. Improvements for the two “out-of-sample” years T + 1 and T + 2 also considered relevant by the EU Commission are quantitatively smaller (up to 10 percent) but still relevant. The results do vary across countries but are qualitatively robust with respect to different indicator sets, model specifications or vintages considered.

Suggested Citation

  • Kai Carstensen & Felix Kießner & Thies Rossian, 2023. "Estimation of the TFP Gap for the Largest Five EMU Countries," CESifo Working Paper Series 10245, CESifo.
  • Handle: RePEc:ces:ceswps:_10245
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    References listed on IDEAS

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    More about this item

    Keywords

    trend-cycle decomposition; unobserved components model; factor model; Bayesian estimation; total factor productivity; EU Commission;
    All these keywords.

    JEL classification:

    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • E37 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Forecasting and Simulation: Models and Applications

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