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
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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).
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Try sampling up to 50 parameter sets from the prior.
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Identification stopped:
The model did not solve for any of 50 attempts of random samples from the prior
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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?