Testing DSGE models by indirect inference: a survey of recent findings

Meenagh, David ORCID: https://orcid.org/0000-0002-9930-7947, Minford, Patrick ORCID: https://orcid.org/0000-0003-2499-935X, Wickens, Michael ORCID: https://orcid.org/0000-0002-6862-0674 and Xu, Yongdeng ORCID: https://orcid.org/0000-0001-8275-1585 2019. Testing DSGE models by indirect inference: a survey of recent findings. Open Economies Review 30 (3) , pp. 593-620. 10.1007/s11079-019-09526-w

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Abstract

We review recent findings in the application of indirect inference to DSGE models. We show that researchers should tailor the power of their test to the model under investigation in order to achieve a balance between high power and finding a robust model; this will involve choosing only a limited number of variables on whose behaviour they should focus. Also recent work reveals that it makes little difference which these variables are or how their behaviour is measured whether via a VAR, IRFs or moments. We also review identification issues, how to test part of a model and whether alternative evaluation methods such as forecasting or likelihood ratio tests are potentially helpful.

Item Type:	Article
Date Type:	Publication
Status:	Published
Schools:	Advanced Research Computing @ Cardiff (ARCCA) Business (Including Economics)
Publisher:	Springer Verlag
ISSN:	0923-7992
Date of First Compliant Deposit:	5 March 2019
Date of Acceptance:	3 February 2019
Last Modified:	05 Aug 2024 16:12
URI:	https://orca.cardiff.ac.uk/id/eprint/120169

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