Hi everyone,

I run a Bayesian estimation of my model and I got a strange results and maybe sameone could help me.

In the attachment you can find the mode check of same parameters and you could clearly see that parameter chi_sb give me same issue.

As far as I know the red dot points tell me that the blanchard khan conditions are not satisfied.

Anyway If I run a simulation in one of that points everything is fine and I obtained coherent results.

After the estimation , I run the identification command to get same extra information and i obtained this error

==== Identification analysis ====

Testing prior mean

Parameter error:

The model does not solve for prior_mean with error code info = 19

## info==19 %! The steadystate routine thrown an exception (inconsistent deep parameters).

Try sampling up to 50 parameter sets from the prior.

## Identification stopped:

The model did not solve for any of 50 attempts of random samples from the prior

and finally using the model_diagnostic command I got

model diagnostic can’t obtain the steady state

Since It’s the first time that I obtained this strange results I have no idea how to detect my problem.

NB: If I get rid of chi_sb in the estimation block leaving the parameter calibrated and run the estimation I have no problem and the mode search results succesful

Any idea?

GR83_CheckPlots5.pdf (7.62 KB)