Comparing different data descriptors in indirect inference tests on DSGE models

Patrick Minford, Michael Wickens and Yongdeng Xu

Indirect inference testing can be carried out with a variety of auxiliary models. Asymptotically these different models make no difference. However, in small samples power can differ. We explore small sample power with three different auxiliary models: a VAR, average Impulse Response Functions and Moments. The latter corresponds to the Simulated Moments Method. We find that in a small macro model there is no difference in power. But in a large complex macro model the power with Moments rises more slowly with increasing misspecification than with the other two which remain similar.

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Year of publication:	May 2016
Authors:	Minford, Patrick ; Wickens, Michael R. ; Xu, Yongdeng
Publisher:	Cardiff, United Kingdom : Cardiff Business School, Cardiff University
Subject:	Indirect Inference \| DGSE model \| Auxiliary Models \| Simulated Moments Method \| Induktive Statistik \| Statistical inference \| DSGE-Modell \| DSGE model \| Dynamisches Gleichgewicht \| Dynamic equilibrium \| Schätztheorie \| Estimation theory \| VAR-Modell \| VAR model \| Simulation \| Bootstrap-Verfahren \| Bootstrap approach \| Statistische Methodenlehre \| Statistical theory \| Statistischer Test \| Statistical test