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Parameter Bias in an Estimated DSGE Model

Author

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  • Yasuo Hirose

    () (Keio University)

  • Takeki Sunakawa

    () (The University of Tokyo, CEAFJP - Centre d’études avancées franco-japonais de Paris - FFJ - Fondation France-Japon de l'EHESS - EHESS - École des hautes études en sciences sociales)

Abstract

How can parameter estimates be biased in a dynamic stochastic general equilibrium model that omits nonlinearity in the economy? To answer this question, we simulate data from a fully nonlinear New Keynesian model with the zero lower bound constraint and estimate a linearized version of the model. Monte Carlo experiments show that significant biases are detected in the estimates of monetary policy parameters and the steady-state inflation and real interest rates. These biases arise mainly from neglecting the zero lower bound constraint rather than linearizing equilibrium conditions. With fixed parameters, the variance-covariance matrix and impulse response functions of observed variables implied by the linearized model substantially differ from those implied by its nonlinear counterpart. However, we find that the biased estimates of parameters in the estimated linear model can make most of the differences small.

Suggested Citation

  • Yasuo Hirose & Takeki Sunakawa, 2016. "Parameter Bias in an Estimated DSGE Model," Working Papers halshs-01661908, HAL.
  • Handle: RePEc:hal:wpaper:halshs-01661908
    Note: View the original document on HAL open archive server: https://halshs.archives-ouvertes.fr/halshs-01661908
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    Cited by:

    1. Best Gabriela & Kapinos Pavel, 2016. "Monetary policy and news shocks: are Taylor rules forward-looking?," The B.E. Journal of Macroeconomics, De Gruyter, vol. 16(2), pages 335-360, June.
    2. Marcin Bielecki & Michał Brzoza-Brzezina & Marcin Kolasa & Krzysztof Makarski, 2017. "Could the boom-bust in the eurozone periphery have been prevented?," GRAPE Working Papers 17, GRAPE Group for Research in Applied Economics.

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    Keywords

    Bayesian estimation; Nonlinearity; Zero lower bound; DSGE Model;

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