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Factor Analysis in a Model with Rational Expectations

  • Andreas Beyer
  • Roger E. A. Farmer
  • Jérôme Henry
  • Massimiliano Marcellino

DSGE models are characterized by the presence of expectations as explanatory variables. To use these models for policy evaluation, the econometrician must estimate the parameters of expectation terms. Standard estimation methods have several drawbacks, including possible lack or weakness of identification of the parameters, misspecification of the model due to omitted variables or parameter instability, and the common use of inefficient estimation methods. Several authors have raised concerns over the implications of using inappropriate instruments to achieve identification. In this paper we analyze the practical relevance of these problems and we propose to combine factor analysis for information extraction from large data sets and GMM to estimate the parameters of systems of forward looking equations. Using these techniques, we evaluate the robustness of recent findings on the importance of forward looking components in the equations of a standard New-Keynesian model.

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Paper provided by National Bureau of Economic Research, Inc in its series NBER Working Papers with number 13404.

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Date of creation: Sep 2007
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Publication status: published as Andreas Beyer & Roger E. A. Farmer & Jér�me Henry & Massimiliano Marcellino, 2008. "Factor analysis in a model with rational expectations," Econometrics Journal, Royal Economic Society, vol. 11(2), pages 271-286, 07.
Handle: RePEc:nbr:nberwo:13404
Note: EFG ME
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  24. Massimiliano Marcellino & Carlo A. Favero & Francesca Neglia, 2005. "Principal components at work: the empirical analysis of monetary policy with large data sets," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 20(5), pages 603-620.
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