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Monetary policy indeterminacy in the U.S.: results from a classical test

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Author Info

  • Efrem Castelnuovo

    (Università di Padova)

  • Luca Fanelli

    ()
    (Università di Bologna)

Abstract

We work with a newly developed method to empirically assess whether a specified new-Keynesian business cycle monetary model estimated with U.S. quarterly data is consistent with a unique equilibrium or multiple equilibria under rational expectations. We conduct classical tests to verify if the structural model is correctly specified. Conditional on a positive answer, we formally assess if such model is either consistent with a unique equilibrium or with indeterminacy. Importantly, our full-system approach requires neither the use of prior distributions nor that of nonstandard inference. The case of an indeterminate equilibrium in the pre-1984 sample and of a determinate equilibrium in the post-1984 sample is favored by the data. The long-run coefficients on inflation and the output gap in the monetary policy rule are found to be weakly identified. However, our results are further supported by a proposed identification-robust indicator of indeterminacy

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Bibliographic Info

Paper provided by Department of Statistics, University of Bologna in its series Quaderni di Dipartimento with number 8.

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Length: 32
Date of creation: 2011
Date of revision:
Handle: RePEc:bot:quadip:112

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Related research

Keywords: GMM; Indeterminatezza; Massima Verosimiglianza; Errata specificazione; modello neo-Keynesiano per il ciclo economico; VAR; Identificazione debole GMM; Indeterminacy; Maximum Likelihood; Misspecification; new-Keynesian business cycle model; VAR; Weak identification.;

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Cited by:
  1. Fanelli, Luca, 2012. "Determinacy, indeterminacy and dynamic misspecification in linear rational expectations models," Journal of Econometrics, Elsevier, vol. 170(1), pages 153-163.
  2. Gunnar Bårdsen & Luca Fanelli, 2013. "Frequentist evaluation of small DSGE models," Working Paper Series 14113, Department of Economics, Norwegian University of Science and Technology.

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