About a strange graph of posterior distribution

Hello everyone,
I have touble in estimating my model, the graph of posterior distribution is very strange as follows
And my code to estimate is

estimation(datafile=estimate_data, mh_jscale=1, mh_replic=2000, mh_nblocks=5, mode_check, mode_compute=6)
Thanks in advance

There is a massive problem with your estimation. You get various unit roots. There are two (potential) reasons:

  1. Your prior for rho_me has an asymptote at 1 that drives the posterior to that point. Thus, use a prior with an interior solution
  2. Unit roots most of the time come from a wrong observation equation where the trends are incorrectly handled. Please see Pfeifer(2013): “A Guide to Specifying Observation Equations for the Estimation of DSGE Models” sites.google.com/site/pfeiferecon/Pfeifer_2013_Observation_Equations.pdf.