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Trend-Cycle Decomposition Of Output And Euro Area Inflation Forecasts: A Real-Time Approach Based On Model Combination

Author

Listed:
  • Guérin, Pierre
  • Maurin, Laurent
  • Mohr, Matthias

Abstract

This paper estimates univariate and multivariate trend-cycle decomposition models of GDP and considers the novel possibility of regime switches in the growth of potential output. We compute both ex post and real-time estimates of the output gap to check the stability of our estimates to GDP data revisions. We find some evidence of regime changes in the growth of potential output during the recessions experienced by the euro area. We also run a forecasting experiment to evaluate the predictive power of the output gap for inflation. The benchmark autoregressive model tends to obtain the best forecasts for one-quarter-ahead forecasts, but the output gap measures help to forecast inflation for longer horizons.

Suggested Citation

  • Guérin, Pierre & Maurin, Laurent & Mohr, Matthias, 2015. "Trend-Cycle Decomposition Of Output And Euro Area Inflation Forecasts: A Real-Time Approach Based On Model Combination," Macroeconomic Dynamics, Cambridge University Press, vol. 19(2), pages 363-393, March.
    • Handle: RePEc:cup:macdyn:v:19:y:2015:i:02:p:363-393_00
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    Cited by:

    1. Mendieta-Muñoz, Ivan, 2017. "On The Interaction Between Economic Growth And Business Cycles," Macroeconomic Dynamics, Cambridge University Press, vol. 21(4), pages 982-1022, June.
    2. James Morley & Benjamin Wong, 2020. "Estimating and accounting for the output gap with large Bayesian vector autoregressions," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 35(1), pages 1-18, January.
    3. Pichette, Lise & Robitaille, Marie-Noëlle & Salameh, Mohanad & St-Amant, Pierre, 2019. "Dismiss the output gaps? To use with caution given their limitations," Economic Modelling, Elsevier, vol. 76(C), pages 199-215.
    4. Daniel Gros & Alessandro Liscai & Farzaneh Shamsfakhr, 2022. "Planned Fiscal Consolidation and Under-Estimated Multipliers: Revisiting the Evidence and Relevance for the Euro Area," EconPol Policy Reports 35, ifo Institute - Leibniz Institute for Economic Research at the University of Munich.
    5. Zivile Zekaite & Gabe de Bondt & Elke Hahn, 2017. "Alice: A New Inflation Monitoring Tool," EcoMod2017 10414, EcoMod.
    6. González-Astudillo, Manuel, 2019. "An output gap measure for the euro area: Exploiting country-level and cross-sectional data heterogeneity," European Economic Review, Elsevier, vol. 120(C).
    7. Lise Pichette & Marie-Noëlle Robitaille & Mohanad Salameh & Pierre St-Amant, 2018. "Dismiss the Gap? A Real-Time Assessment of the Usefulness of Canadian Output Gaps in Forecasting Inflation," Staff Working Papers 18-10, Bank of Canada.
    8. Bassi, Federico, 2024. "Excess capacity and hysteresis in EU Countries. A structural approach," Structural Change and Economic Dynamics, Elsevier, vol. 71(C), pages 116-134.
    9. Susanne Maidorn, 2018. "Is there a trade-off between procyclicality and revisions in EC trend TFP estimations?," Empirica, Springer;Austrian Institute for Economic Research;Austrian Economic Association, vol. 45(1), pages 59-82, February.
    10. Andrew B. Martinez & Alexander D. Schibuola & David Beckworth, 2025. "The Reliability of the Nominal GDP Expectations Gap," Working Papers 2025-004, The George Washington University, The Center for Economic Research.

    More about this item

    JEL classification:

    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles
    • E37 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Forecasting and Simulation: Models and Applications

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