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Issues in Estimating New-Keynesian Phillips Curves in the Presence of Unknown Structural Change

Author

Listed:
  • Mariano Kulish

    (University of New South Wales)

  • Adrian Pagan

    (University of Sydney)

Abstract

Structural change has been conjectured to lead to an upward bias in the estimated forward expectations coefficient in New-Keynesian Phillips curves. We present a simple New-Keynesian model that enables us to assess this proposition. In particular, we investigate the issue of upward bias in the estimated coefficients of the expectations variable in the New-Keynesian Phillips curve based on a model where we can see what causes the structural breaks and how to control for them. We find that structural breaks in the means of the series can often change the properties of instruments a great deal, and may well be a bigger source of small-sample bias than that due to specification error. Moreover, we also find that the direction of the specification bias is not predictable. It is necessary to check for weak instruments before deciding that the magnitude of any estimator bias reflects specification errors coming from structural change.

Suggested Citation

  • Mariano Kulish & Adrian Pagan, 2013. "Issues in Estimating New-Keynesian Phillips Curves in the Presence of Unknown Structural Change," RBA Research Discussion Papers rdp2013-11, Reserve Bank of Australia.
    • Handle: RePEc:rba:rbardp:rdp2013-11
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    References listed on IDEAS

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    1. Mariano Kulish & Adrian Pagan, 2017. "Estimation and Solution of Models with Expectations and Structural Changes," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 32(2), pages 255-274, March.
    2. Leandro M. Magnusson & Sophocles Mavroeidis, 2010. "Identification-Robust Minimum Distance Estimation of the New Keynesian Phillips Curve," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 42(2-3), pages 465-481, March.
    3. Guido Ascari, 2004. "Staggered Prices and Trend Inflation: Some Nuisances," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 7(3), pages 642-667, July.
    4. Bill Russell & Anindya Banerjee & Issam Malki & Natalia Ponomareva, 2010. "A Multiple Break Panel Approach To Estimating United States Phillips Curves," Dundee Discussion Papers in Economics 232, Economic Studies, University of Dundee.
    5. Nymoen, Ragnar & L. Castle, Jennifer & A. Doornik, Jurgen & F. Hendry, David, 2010. "Testing the Invariance of Expectations Models of Inflation," Memorandum 21/2010, Oslo University, Department of Economics.
    6. Timothy Cogley & Argia M. Sbordone, 2008. "Trend Inflation, Indexation, and Inflation Persistence in the New Keynesian Phillips Curve," American Economic Review, American Economic Association, vol. 98(5), pages 2101-2126, December.
    7. Jennifer L. Castle & Jurgen A. Doornik & David F. Hendry & Ragnar Nymoen, 2014. "Misspecification Testing: Non-Invariance of Expectations Models of Inflation," Econometric Reviews, Taylor & Francis Journals, vol. 33(5-6), pages 553-574, August.
    8. Sophocles Mavroeidis, 2004. "Weak Identification of Forward‐looking Models in Monetary Economics," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 66(s1), pages 609-635, September.
    9. Gali, Jordi & Gertler, Mark, 1999. "Inflation dynamics: A structural econometric analysis," Journal of Monetary Economics, Elsevier, vol. 44(2), pages 195-222, October.
    10. Binder,M. & Pesaran,H.M., 1995. "Multivariate Rational Expectations Models and Macroeconomic Modelling: A Review and Some New Results," Cambridge Working Papers in Economics 9415, Faculty of Economics, University of Cambridge.
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    Cited by:

    1. Garratt, Anthony & Lee, Kevin & Shields, Kalvinder, 2016. "Information rigidities and the news-adjusted output gap," Journal of Economic Dynamics and Control, Elsevier, vol. 70(C), pages 1-17.

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    More about this item

    Keywords

    expectations; structural change; regime change; weak instruments; IV estimation; Phillips curves;
    All these keywords.

    JEL classification:

    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • 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
    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
    • E52 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit - - - Monetary Policy

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