I’ll be checking the code, thanks. In the other hand, as far as I understand, as I’m using (more likely escenario) indirect inference the choosing of the filter is more a matter of making the simulation and the data comparable, in that sense it’s not extremely necessary to choose a “perfect” filter for my work and use regular HP will work good, am I right?
In the other hand, if considering Bayesian estimation with Dynare, it’s not completely clear to me as in
if few observations (~50 in my case, of about 7 variables) is too little for Bayesian estimation, for example if I were to perform an IRF-matching with an empirical VAR, having >6 variables would kill my degrees of freedom fastly, what would be the drawbacks of this kind in bayesian estimation? And if I were to adventure in trying this estimation, what should I read first?
Thanks!!