Working Paper: CEPR ID: DP9411
Authors: Vo Phuong Mai Le; Patrick Minford; Michael Wickens
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.
Keywords: DSGE model; indirect inference; monte carlo
JEL Codes: C13; C51; C52; E32
Edges that are evidenced by causal inference methods are in orange, and the rest are in light blue.
| Cause | Effect |
|---|---|
| DSGE model is exactly identified (E13) | all coefficients can be uniquely derived from its reduced-form solution (C29) |
| DSGE model is over-identified (E13) | multiple sets of structural coefficients can yield the same reduced-form solution (C30) |
| DSGE model is under-identified (E13) | not all structural coefficients can be derived (C29) |
| numerical procedure (C89) | identification status of the model can be reliably assessed (C52) |
| Monte Carlo method (C15) | identification status of the model can be reliably assessed (C52) |
| certain specifications (L15) | lead to over-identification (D91) |
| other specifications (Y90) | result in under-identification (C50) |