Comparing different data descriptors in Indirect Inference tests on DSGE models

A. Patrick Minford, Michael Wickens and Yongdeng Xu

No E2016/5, Cardiff Economics Working Papers from Cardiff University, Cardiff Business School, Economics Section

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: : Indirect Inference; DGSE model; Auxiliary Models; Simulated Moments Method (search for similar items in EconPapers)
JEL-codes: C12 C32 C52 E1 (search for similar items in EconPapers)
Pages: 11 pages
Date: 2016-05
New Economics Papers: this item is included in nep-dge, nep-ecm, nep-pr~ and nep-mac
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (13)

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Related works:
Working Paper: Comparing different data descriptors in Indirect Inference tests on DSGE models (2017)
Journal Article: Comparing different data descriptors in Indirect Inference tests on DSGE models (2016)
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