A Monte Carlo procedure for checking identification in DSGE models

Le, Vo Phuong Mai ORCID: https://orcid.org/0000-0003-3374-9694, Meenagh, David ORCID: https://orcid.org/0000-0002-9930-7947, Minford, Anthony ORCID: https://orcid.org/0000-0003-2499-935X and Wickens, Michael ORCID: https://orcid.org/0000-0002-6862-0674 2017. A Monte Carlo procedure for checking identification in DSGE models. Journal of Economic Dynamics and Control 76 , pp. 202-210. 10.1016/j.jedc.2017.01.009

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Abstract

We propose a numerical method, based on indirect inference, for checking the identification of a DSGE model. Monte Carlo samples are generated from the model’s true structural parameters and a VAR approximation to the reduced form estimated for each sample. We then search for a different set of structural parameters that could potentially also generate these VAR parameters. If we can find such a set, the model is not identified. The test is both an alternative to using the rank condition and also can establish whether there is empirically weak identification.

Item Type:	Article
Date Type:	Publication
Status:	Published
Schools:	Advanced Research Computing @ Cardiff (ARCCA) Business (Including Economics)
Uncontrolled Keywords:	Identification Indirect inference Monte Carlo VAR Reduced form
Publisher:	Elsevier
ISSN:	0165-1889
Date of First Compliant Deposit:	17 February 2017
Date of Acceptance:	14 January 2017
Last Modified:	20 Nov 2024 12:15
URI:	https://orca.cardiff.ac.uk/id/eprint/98106

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