(pag. 70-77).
I think it happens because variance almost 0 at the mode is propagating to metropolis hasting.
Is this result normal or is this a problem and I should be worry. How could I fix this?

I am thinking to modify priors so that they have mean and variance similar to the computed at mode.

Your MCMC did clearly not converge yet. You may need a lot more draws. How did the mode_check plots look like? And what was the acceptance rate during the MCMC?

I suspect I will get Variance 0 after MCMC even if I set more draws, because the Ramdom Walk Metropolis Hasting draws random numbers from nomal distribution with variance based in the mode which is zero for several parameters.

Judging from the mode check plots a few parameters are still away from their mode. I’m talking about: rho_i, phi_i, kappa_b, etaf, a22, a13, a21 and a32. I guess you used mode_compute=6, since you are able to estimate the model right after mode finding. If you would have used another mode finding routine you would have ended up with a warning message saying that the hessian matrix at the “mode” is not positive definite. However, under mode_compute=6 you might need a lot more draws later for the MCMC. The explanation for this can be found here . Since you are working with a larger model I would say in the millions.

This still suggests a problem in mode-finding. Given the size of your model, debugging this amounts to finding a needle in a haystack. Maybe you should start from a smaller model that works.