Dear forum. Methods I know so far for giving numerical values to parameters can be summarized to my best knowledge in: i) calibrating from previous literature findings, ii) IRF-matching (from an SVAR, as noted here), and iii) directly estimating from a BVAR posterior distribution.
I’d be grateful if you could guide me on other methods that could exist and, that are used and accepted as good empirical contrastation of DSGE models. And also if you may tell me some of the difficulty-robustness relationship in each approach. As for example BVAR could be the more robust, but requires a very good understanding of some special statistical and numerical methods.
I have seen published DSGE papers that use their criteria for calibrating the ability of the model to replicate second moments, at least in the sign. Is this approach robust?
Also, is IRF-matching commonly used in journal published papers about DSGE?
(By “robust” I’m referring to a method that is statistically valid, or at least is widely accepted in literature.)
Thanks, answers to this would really help me!