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A Monte Carlo procedure for checking identification in DSGE models

Le, Vo, Meenagh, David, Minford, Anthony and Wickens, Michael 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: 29 Jun 2019 16:34
URI: http://orca.cf.ac.uk/id/eprint/98106

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