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ML vs GMM Estimates of Hybrid Macroeconomic Models (With an Application to the New Phillips Curve)

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  • Jondeau, E.
  • Le Bihan, H.

Abstract

Many macroeconomic models involve hybrid equations, in which some variables are a function of both their lags and their expected future value. The hybrid "New Keynesian" Phillips Curve is a prominent example. Estimates of such hybrid models have produced conflicting empirical results: Studies which use ML estimation tend to find the forward-looking component to be small, while those using GMM have reported the inflation dynamics to be predominantly forward-looking. This paper provides a rationalization for this empirical conflict. Allowing for two alternative and straightforward mis-specifications (measurement error and omitted dynamics) in a hybrid model, we show that the ML estimator tends to undervalue the weight of the forward-looking component, while the GMM estimator tends to overstate it. This result is shown to hold analytically in a simple DGP. Monte-Carlo experiments indicate that it remains valid in a wide range of more plausible DGPs. Simulations also suggest that the gap obtained between the two estimators in the context of the new Phillips curve can more readily be accounted for by mis-specification, than by the finite-sample biases.

Suggested Citation

  • Jondeau, E. & Le Bihan, H., 2003. "ML vs GMM Estimates of Hybrid Macroeconomic Models (With an Application to the New Phillips Curve)," Working papers 103, Banque de France.
  • Handle: RePEc:bfr:banfra:103
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    References listed on IDEAS

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    Citations

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    Cited by:

    1. André Kurmann, 2004. "Maximum Likelihood Estimation of Dynamic Stochastic Theories with an Application to New Keynesian Pricing," Cahiers de recherche 0421, CIRPEE.
    2. Bakhshi, Hasan & Khan, Hashmat & Rudolf, Barbara, 2007. "The Phillips curve under state-dependent pricing," Journal of Monetary Economics, Elsevier, vol. 54(8), pages 2321-2345, November.
    3. Fabio Milani, 2005. "Adaptive Learning and Inflation Persistence," Macroeconomics 0506013, EconWPA.
    4. Fabio Rumler, 2007. "Estimates of the Open Economy New Keynesian Phillips Curve for Euro Area Countries," Open Economies Review, Springer, vol. 18(4), pages 427-451, September.
    5. Alain Guay & Florian Pelgrin, 2007. "Using Implied Probabilities to Improve Estimation with Unconditional Moment Restrictions," Cahiers de recherche 0747, CIRPEE.
    6. James M. Nason & Gregor W. Smith, 2008. "Identifying the new Keynesian Phillips curve," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 23(5), pages 525-551.
    7. Andreas Beyer & Roger E. A. Farmer & Jérôme Henry & Massimiliano Marcellino, 2008. "Factor analysis in a model with rational expectations," Econometrics Journal, Royal Economic Society, vol. 11(2), pages 271-286, July.
    8. Jondeau, Eric & Le Bihan, Herve, 2005. "Testing for the New Keynesian Phillips Curve. Additional international evidence," Economic Modelling, Elsevier, vol. 22(3), pages 521-550, May.
    9. Beyer, Andreas & Farmer, Roger E. A. & Henry, Jérôme & Marcellino, Massimiliano, 2005. "Factor analysis in a New-Keynesian model," Working Paper Series 510, European Central Bank.
    10. Sophocles Mavroeidis, 2006. "Testing the New Keynesian Phillips Curve Without Assuming Identification," Working Papers 2006-13, Brown University, Department of Economics.
    11. Peter Tillmann, 2009. "The New Keynesian Phillips curve in Europe: does it fit or does it fail?," Empirical Economics, Springer, vol. 37(3), pages 463-473, December.
    12. Ieva Rubene & Paolo Guarda, 2004. "The new Keynesian Phillips curve: empirical results for Luxembourg," BCL working papers 11, Central Bank of Luxembourg.
    13. Florian PELGRIN & GUAY Alain & LUGER Richard, 2004. "The New Keynesian Phillips Curve: An Empirical Assessment," Computing in Economics and Finance 2004 212, Society for Computational Economics.

    More about this item

    Keywords

    Rational-expectation model ; GMM estimator ; ML estimator ; Inflation ; New Phillips curve;

    JEL classification:

    • C10 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - General
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • E31 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Price Level; Inflation; Deflation

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