I did my first Bayesian estimation of my model. Do not have any experience in interpreting the posteriors though.
my posteriors on the shocks look unusually tight around the mode.
I have attached the posteriors (graphs) in a zip file.
My questions is:
Are the posteriors for the shocks
attached to this post normal ?
What is the interpretation for such graphs?
If the posterior looks very different from the prior, the data is very informative. This is perfectly fine unless you have well-founded suspicions that this cannot be correct.
It’s hard to have a good intuition on what a realistic shock autocorrelation is. Is there a reason to think that shock must be really persistent? Also note that ideally the model should provide propagation without relying on persistent shocks because we want to explain data with the model, not with exogenous stuff outside of the model.
refers to a shock on banking incentive parameter of Gertler Karadi (2011). and probably fits with the idea that it is a one time shock that is propagated through the model, hence does not need a high persistence.
May I please ask your opinion on a different type of posterior and diagnostics ?
Attachéd to this comment there is a ZIP folder with posteriors and diagnostics .
. I find it difficult to interpret
2. How close should the blue and red line be in diagnostics of Brooks&Gelman(1998) to be considered ok.
are the ones I have attached close enough ??