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Model Specification and Inflation Forecast Uncertainty

Author

Listed:
  • Gunnar Bårdsen

    (Department of Economics, Norwegian University of Science and Technology)

  • Eilev S. Jansen

    (Bank of Norway and Department of Economics, Norwegian University of Science and Technology)

  • Ragnar Nymoen

    (Department of Economics, University of Oslo)

Abstract

Three classes of inflation models are discussed: Standard Phillips curves, New Keynesian Phillips curves and Incomplete Competition models. Their relative merits in explaining and forecasting inflation are investigated theoretically and empirically. We establish that Standard Phillips-curve forecasts are robust to types of structural breaks that harm the Incomplete Competion model forecasts, but exaggerate forecast uncertainty in periods with no breaks. As the potential biases in after-break forecast errors for the Incomplete Competition model can be remedied by intercept corrections, it offers the best prospect of successful inflation forecasting.

Suggested Citation

  • Gunnar Bårdsen & Eilev S. Jansen & Ragnar Nymoen, 2000. "Model Specification and Inflation Forecast Uncertainty," Working Paper Series 1302, Department of Economics, Norwegian University of Science and Technology, revised 29 Jan 2002.
    • Handle: RePEc:nst:samfok:1302
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    References listed on IDEAS

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    Cited by:

    1. Gunnar Bårdsen & Eilev S. Jansen & Ragnar Nymoen, 2002. "The Empirical (ir)Relevance of the New Keynesian Phillips Curve," Working Paper Series 2102, Department of Economics, Norwegian University of Science and Technology.
    2. Bårdsen, Gunnar & Jansen, Eilev S. & Nymoen, Ragnar, 2003. "Testing the New Keynesian Phillips curve," Memorandum 18/2002, Oslo University, Department of Economics.
    3. Gunnar Bårdsen & Eilev S. Jansen & Ragnar Nymoen, 2004. "Econometric Evaluation of the New Keynesian Phillips Curve," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 66(s1), pages 671-686, September.
    4. Zied Ftiti & Fredj Jawadi, 2019. "Forecasting Inflation Uncertainty in the United States and Euro Area," Computational Economics, Springer;Society for Computational Economics, vol. 54(1), pages 455-476, June.
    5. Q. Farooq Akram & Ragnar Nymoen, 2006. "Model selection for monetary policy analysis – Importance of empirical validity," Working Paper 2006/13, Norges Bank.
    6. Eilev S. Jansen, 2002. "Statistical Issues in Macroeconomic Modelling," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 29(2), pages 193-213, June.
    7. Nymoen, Ragnar, 2005. "Evaluating a Central Bank’s Recent Forecast Failure," Memorandum 22/2005, Oslo University, Department of Economics.

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    More about this item

    Keywords

    monetary policy; inflation targeting; wages and prices; model specification; encompassing; model uncertainty; forecasting;
    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
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • E31 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Price Level; Inflation; Deflation
    • E52 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit - - - Monetary Policy

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