Testing Prior mean

Dear All,

I’m trying to check the identification of the priors of the model I’m going to estimate. I found this message as results of the test for prior mean (I used identification command):
==== Identification analysis ====

Testing prior mean

The rank of H (model) is deficient!

bh is not identified in the model!
[dJ/d(bh)=0 for all tau elements in the model solution!]

The rank of J (moments) is deficient!

bh is not identified by J moments!
[dJ/d(bh)=0 for all J moments!]

Monte Carlo Testing

Testing MC sample

All parameters are identified in the model (rank of H).

All parameters are identified by J moments (rank of J)

What is the main interpretation? Is there an identification problem? If I calibrate (not estimate) bh, I don’t have anymore this problem. But in case of estimation of the DSGE using bh estimated, what is the main issue of my estimation? Lack of identification? Do I need to check some other priors to avoid problems for bh?

Thanks for help!

Without seeing the mod-file it is hard to tell. The identification problem only seems to occur for one parameterization (prior mean), but not over the whole parameter space, which is reassuring.