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

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Author Info
Jondeau, E.
Le Bihan, H.

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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.

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Paper provided by Banque de France in its series Documents de Travail with number 103.

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Length: 47 pages
Date of creation: 2003
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Handle: RePEc:bfr:banfra:103

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

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Find related papers by JEL classification:
C10 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: General - - - General
C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions
E31 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Price Level; Inflation; Deflation

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Cited by:
(explanations, Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.)

  1. André Kurmann, 2004. "Maximum Likelihood Estimation of Dynamic Stochastic Theories with an Application to New Keynesian Pricing," Macroeconomics 0409028, EconWPA. [Downloadable!]
    Other versions:
  2. Andreas Beyer & Roger E. A. Farmer & Jérôme Henry & Massimiliano Marcellino, 2007. "Factor Analysis in a Model with Rational Expectations," NBER Working Papers 13404, National Bureau of Economic Research, Inc. [Downloadable!] (restricted)
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  3. Fabio Milani, 2005. "Adaptive Learning and Inflation Persistence," Working Papers 050607, University of California-Irvine, Department of Economics. [Downloadable!]
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  4. Beyer, Andreas & Farmer, Roger E A & Henry, Jérôme & Marcellino, Massimiliano, 2005. "Factor Analysis in a New-Keynesian Model," CEPR Discussion Papers 5266, C.E.P.R. Discussion Papers. [Downloadable!] (restricted)
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  5. Florian PELGRIN & Alain GUAY & Richard LUGER, 2004. "The New Keynesian Phillips Curve: An empirical assessment," Econometric Society 2004 North American Summer Meetings 418, Econometric Society. [Downloadable!]
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  6. Hasan Bakhshi & Hashmat Khan & Barbara Rudolf, . "The Phillips curve under state-dependent pricing," Bank of England working papers 227, Bank of England. [Downloadable!]
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  7. Ieva Rubene & Paolo Guarda, 2004. "The new Keynesian Phillips curve: empirical results for Luxembourg," BCL working papers 11, Central Bank of Luxembourg. [Downloadable!]
  8. Tillmann, Peter, 2005. "The New Keynesian Phillips Curve in Europe : does it fit or does it fail?," Discussion Paper Series 1: Economic Studies 2005,04, Deutsche Bundesbank, Research Centre. [Downloadable!]
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