I have estimated a DSGE model in dynare by using bayesian techniques.
I would like to obtain the Kalman filter estimate of an endogenous variable used in the model at the posterior mode, in order to compare its evolution (i.e., the path of the variable generated by the model) against its observed evolution (the observed time series).
Essentially, I would like to replicate figure 5, pag 116, of the paper I attached to this message.
How does this can be accomplished into dynare?

For observed variables, the smoothed variables from the Kalman filter will always be equal to the observed ones. JPT compare the smoothed variable to outside evidence not used for the model estimation

To generate the smoothed variables at the mode, use estimation with

Or alternatively, if you run estimation with MCMC, use the

oo_.SmoothedVariables.VariableName should only generated if you do not run a Metropolis or use the calib_smoother-command. It should be the smoothed variable at the posterior mode. In contrast, oo_.SmoothedVariables.Mean.VariableName is the mean smoothed estimate after a Metropolis run, where the mean is taken over the posterior draws

I am using the latest version and just checked the following. The oo_.SmoothedVariables.VariableName is generated in the following cases:

1.After a MCMC without the smoother option;
2.When a previous mcmc is loaded with the load_mh_file without the smoother option;
3. After a MCMC when “shock_decomposition” is specified (with and without the smoother option);

What oo_.SmoothedVariables.VariableName represents in this case?

My guess is that this is the smoothed variable at the mean.