A Monte Carlo procedure for checking identification in DSGE models

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 stru...

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Bibliographic Details
Published in:Journal of economic dynamics & control 2017-03, Vol.76, p.202-210
Main Authors: Le, Vo Phuong Mai, Meenagh, David, Minford, Patrick, Wickens, Michael
Format: Article
Language:English
Subjects:
Identification
Indirect inference
Monte Carlo
Reduced form
VAR
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Summary: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.
ISSN:0165-1889
1879-1743
DOI:10.1016/j.jedc.2017.01.009