Comparing different data descriptors in Indirect Inference tests on DSGE models
A. Patrick Minford,
Michael Wickens and
Yongdeng Xu ()
Economics Letters, 2016, vol. 145, issue C, 157-161
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)
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (6) Track citations by RSS feed
Downloads: (external link)
Full text for ScienceDirect subscribers only
Working Paper: Comparing different data descriptors in Indirect Inference tests on DSGE models (2017)
Working Paper: Comparing different data descriptors in Indirect Inference tests on DSGE models (2016)
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
Persistent link: https://EconPapers.repec.org/RePEc:eee:ecolet:v:145:y:2016:i:c:p:157-161
Access Statistics for this article
Economics Letters is currently edited by Economics Letters Editorial Office
More articles in Economics Letters from Elsevier
Bibliographic data for series maintained by Haili He ().