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Forecasting output gaps in the G-7 countries: the role of correlated innovations and structural breaks

Author

Listed:
  • Mardi Dungey
  • Jan P.A.M. Jacobs
  • Jing Tian

Abstract

Trend GDP and output gaps play an important role in fiscal and monetary policy formulation, often including the need for forecasts. In this article, we focus on forecasting trend GDP and output gaps with Beveridge-Nelson trend-cycle decompositions trend-cycle decompositions and investigate how these are affected by assumptions concerning correlated innovations and structural breaks. We evaluate expanding window, one-step-ahead forecasts indirectly for the G-7 countries on the basis of real GDP growth rate forecasts. We find that correlated innovations affect real GDP growth rate forecasts positively, while allowing for structural breaks works for some countries but not for all. In the face of uncertainty, the evidence supports that in making forecasts of trends and output gap policy-makers should focus on allowing for the correlation of shocks as an order of priority higher than unknown structural breaks.

Suggested Citation

  • Mardi Dungey & Jan P.A.M. Jacobs & Jing Tian, 2017. "Forecasting output gaps in the G-7 countries: the role of correlated innovations and structural breaks," Applied Economics, Taylor & Francis Journals, vol. 49(45), pages 4554-4566, September.
    • Handle: RePEc:taf:applec:v:49:y:2017:i:45:p:4554-4566
    DOI: 10.1080/00036846.2017.1284998
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    Cited by:

    1. Cremaschini, Alessandro & Maruotti, Antonello, 2023. "A finite mixture analysis of structural breaks in the G-7 gross domestic product series," Research in Economics, Elsevier, vol. 77(1), pages 76-90.
    2. Amy Y. Guisinger & Michael T. Owyang & Hannah Shell, 2018. "Comparing Measures of Potential Output," Review, Federal Reserve Bank of St. Louis, vol. 100(4), pages 297-316.

    More about this item

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • C82 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Methodology for Collecting, Estimating, and Organizing Macroeconomic Data; Data Access

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