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Evaluating the New Keynesian Phillips Curve under VAR-based learning

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  • Fanelli, Luca

Abstract

This paper proposes the evaluation of the New Keynesian Phillips Curve (NKPC) under a new learning mechanism where VAR learning dynamics is combined with the idea of testing the validity of the forward-looking model of inflation dynamics. The key assumption is that agents’ perceived law of motion is a VAR whose parameters are updated by recursive least squares. Differently from standard adaptive learning methods, agents test sequentially the cross-equation restrictions that the NKPC imposes on the VAR as the information set increases. When the restrictions are not rejected agents learn under the restricted system and exploit the cross-equation restrictions to forecast inflation. It is thus possible to check how much and in which periods agents’ beliefs are consistent with the restrictions of the theory. The empirical analysis on quarterly data on the euro area shows that the NKPC with negligible backward-looking parameter is not rejected when the model is evaluated over the period 1984-2005 under the proposed learning mechanism. The result, however, is not fully robust to specifications based on non stationary variables and points out that learning may represent a remarkable source of euro area inflation persistence but not its only determinant.

Suggested Citation

  • Fanelli, Luca, 2007. "Evaluating the New Keynesian Phillips Curve under VAR-based learning," MPRA Paper 1616, University Library of Munich, Germany.
  • Handle: RePEc:pra:mprapa:1616
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    Cited by:

    1. Giovanni Angelini & Luca Fanelli, 2016. "Misspecification and Expectations Correction in New Keynesian DSGE Models," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 78(5), pages 623-649, October.
    2. Katarina Juselius, 2011. "On the Role of Theory and Evidence in Macroeconomics," Chapters,in: The Elgar Companion to Recent Economic Methodology, chapter 17 Edward Elgar Publishing.
    3. Luca Fanelli & Giulio Palomba, 2011. "Simulation‐based tests of forward‐looking models under VAR learning dynamics," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 26(5), pages 762-782, August.
    4. Katarina Juselius, 2009. "Time to reject the privileging of economic theory over empirical evidence? A Reply to Lawson (2009)," Discussion Papers 09-16, University of Copenhagen. Department of Economics.
    5. Ordóñez, Javier & Jusélius, Katarina, 2009. "Balassa-Samuelson and Wage, Price and Unemployment Dynamics in the Spanish Transition to EMU Membership," Economics - The Open-Access, Open-Assessment E-Journal, Kiel Institute for the World Economy (IfW), vol. 3, pages 1-30.
    6. Jusélius, Katarina, 2009. "Special Issue on Using Econometrics for Assessing Economic Models: An Introduction," Economics - The Open-Access, Open-Assessment E-Journal, Kiel Institute for the World Economy (IfW), vol. 3, pages 1-20.

    More about this item

    Keywords

    Adaptive learning; Cross-equation restrictions; Forward-looking model of inflation dynamics; Perceived Law of Motion; Recursive Least Squares; VAR;

    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
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
    • E10 - Macroeconomics and Monetary Economics - - General Aggregative Models - - - General
    • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness

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