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Testing the Invariance of Expectations Models of Inflation

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  • David Hendry
  • Jennifer L. Castle
  • Jurgen A. Doornik

Abstract

The new-Keynesian Phillips curve (NKPC) includes expected future inflation as a major feedforward variable to explain current inflation. Models of this type are regularly estimated by replacing the expected value by the actual future outcome, then using Instrumental Variables or Generalized Method of Moments methods to estimate the parameters. However, the underlying theory does not allow for various forms of non-stationarity in the data - despite the fact that crises, breaks and regimes shifts are relatively common. We investigate the consequences for NKPC estimation of breaks in data processes using the new technique of impulse-indicator saturation, and apply the resulting methods to salient published studies to check their viablility.

Suggested Citation

  • David Hendry & Jennifer L. Castle & Jurgen A. Doornik, 2010. "Testing the Invariance of Expectations Models of Inflation," Economics Series Working Papers 510, University of Oxford, Department of Economics.
    • Handle: RePEc:oxf:wpaper:510
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    1. Bjørnstad, Roger & Nymoen, Ragnar, 2008. "The New Keynesian Phillips Curve Tested on OECD Panel Data," Economics - The Open-Access, Open-Assessment E-Journal (2007-2020), Kiel Institute for the World Economy (IfW Kiel), vol. 2, pages 1-18.
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    Cited by:

    1. Russell, Bill & Chowdhury, Rosen Azad, 2013. "Estimating United States Phillips curves with expectations consistent with the statistical process of inflation," Journal of Macroeconomics, Elsevier, vol. 35(C), pages 24-38.
    2. De Grauwe, Paul & Macchiarelli, Corrado, 2015. "Animal spirits and credit cycles," Journal of Economic Dynamics and Control, Elsevier, vol. 59(C), pages 95-117.
    3. Hendry, David F., 2011. "On adding over-identifying instrumental variables to simultaneous equations," Economics Letters, Elsevier, vol. 111(1), pages 68-70, April.
    4. Sophocles Mavroeidis & Mikkel Plagborg-Møller & James H. Stock, 2014. "Empirical Evidence on Inflation Expectations in the New Keynesian Phillips Curve," Journal of Economic Literature, American Economic Association, vol. 52(1), pages 124-188, March.
    5. 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.
    6. Mariano Kulish & Adrian Pagan, 2016. "Issues in Estimating New Keynesian Phillips Curves in the Presence of Unknown Structural Change," Econometric Reviews, Taylor & Francis Journals, vol. 35(7), pages 1251-1270, August.
    7. J. James Reade & Ulrich Volz, 2011. "From the General to the Specific," Discussion Papers 11-18, Department of Economics, University of Birmingham.
    8. Abbas, Syed K. & Bhattacharya, Prasad Sankar & Sgro, Pasquale, 2016. "The new Keynesian Phillips curve: An update on recent empirical advances," International Review of Economics & Finance, Elsevier, vol. 43(C), pages 378-403.
    9. Adriana Cornea-Madeira & Cars Hommes & Domenico Massaro, 2019. "Behavioral Heterogeneity in U.S. Inflation Dynamics," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 37(2), pages 288-300, April.
    10. Syed Kanwar Abbas & Prasad Sankar Bhattacharya & Debdulal Mallick & Pasquale Sgro, 2016. "The New Keynesian Phillips Curve in a Small Open Economy: Empirical Evidence from Australia," The Economic Record, The Economic Society of Australia, vol. 92(298), pages 409-434, September.
    11. Nymoen, Ragnar & Swensen, Anders Rygh & Tveter, Eivind, 2012. "Interpreting the evidence for New Keynesian models of inflation dynamics," Journal of Macroeconomics, Elsevier, vol. 34(2), pages 253-263.

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    More about this item

    Keywords

    New-Keynesian Phillips curve; inflation expectations; structural breaks; impulse-indicator saturation;
    All these keywords.

    JEL classification:

    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes

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