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Estimating New-Keynesian Phillips Curves: A Full Information Maximum Likelihood Approach

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  • Lindé, Jesper

    (Research Department, Central Bank of Sweden)

Abstract

The New-Keynesian Phillips curve has recently become an important ingredient in monetary policy models. However, using limited information methods, the empirical support for the New-Keynesian Phillips curve appear to be mixed. This paper argues, by means of Monte Carlo simulations with a simple New-Keynesian sticky price model, that single equations methods, e.g. GMM, are likely to produce imprecise and biased estimates. Then, it is argued that estimating the model with full information maximum likelihood (FIML) is a useful way of obtaining better estimates. Finally, a version of the model used in the Monte Carlo simulations is estimated on U.S. data with FIML and although the pure forward-looking New-Keynesian Phillips curve is rejected, a version with both forward- and backward-looking components provides a reasonable approximation of U.S. inflation dynamics.

Suggested Citation

  • Lindé, Jesper, 2001. "Estimating New-Keynesian Phillips Curves: A Full Information Maximum Likelihood Approach," Working Paper Series 129, Sveriges Riksbank (Central Bank of Sweden), revised 01 Mar 2005.
  • Handle: RePEc:hhs:rbnkwp:0129
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    More about this item

    Keywords

    Monetary policy rule; New-Keynesian Phillips curve; Rational expectations IS-curve; Backward-looking Phillips curve; Measurement errors; Full Information Maximum Likelihood estimation;
    All these keywords.

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
    • E52 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit - - - Monetary Policy

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