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Parameter bias in an estimated DSGE model: does nonlinearity matter?

Yasuo Hirose and Takeki Sunakawa ()

CAMA Working Papers from Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University

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.

Keywords: Nonlinearity; Zero lower bound; DSGE model; Parameter bias; Bayesian estimation (search for similar items in EconPapers)
JEL-codes: C32 E30 E52 (search for similar items in EconPapers)
New Economics Papers: this item is included in nep-dge, nep-ecm, nep-mac and nep-mon
Date: 2015-11
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Related works:
Working Paper: Parameter Bias in an Estimated DSGE Model:Does Nonlinearity Matter? (2016) Downloads
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Persistent link: https://EconPapers.repec.org/RePEc:een:camaaa:2015-46

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