Comparing different data descriptors in Indirect Inference tests on DSGE models

A. Patrick Minford, Michael R. Wickens and Yongdeng Xu

No 11816, CEPR Discussion Papers from C.E.P.R. Discussion Papers

Abstract: 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.

Keywords: Dgse model; Auxiliary models; Simulated moments method; indirect inference (search for similar items in EconPapers)
Date: 2017-01
New Economics Papers: this item is included in nep-dge and nep-mac
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Citations: View citations in EconPapers (1)

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Related works:
Journal Article: Comparing different data descriptors in Indirect Inference tests on DSGE models (2016)
Working Paper: Comparing different data descriptors in Indirect Inference tests on DSGE models (2016)
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