Impulse response analysis in a misspecified DSGE model: a comparison of full and limited information techniques

ABSTRACT

In this article, we examine the effect of estimation biases – introduced by model misspecification – on the impulse responses analysis for dynamic stochastic general equilibrium (DSGE) models. Thereby, we use full and limited information estimators to estimate a misspecified DSGE model and calculate impulse response functions (IRFs) based on the estimated structural parameters. It turns out that IRFs based on full information techniques can be unreliable under misspecification.

KEYWORDS:

• Impulse response analysis
• FIML
• GMM
• misspecification
• Monte Carlo
• DSGE

JEL CLASSIFICATION:

• C22
• C32
• C51
• E17

Acknowledgements

We thank Jörg Breitung, André Kurmann and Jesper Lindé for valuable comments. This paper has also benefited from discussions at the Australasian and the European Meeting of the Econometric Society 2013. The views expressed in this paper are those of the authors and not necessarily those of the Swiss National Bank or the Deutsche Bundesbank. Research for parts of this paper was carried out while the first author was visiting the European Central Bank.

Notes

¹ Giesen-Scheufele (2013) show that the systems approach is much more efficient than a single-equation set-up and both are equally robust to typical forms of misspecifications.