In Smets and Wouters (2007), they compare different model specifications using a pre-sample period as a training sample according to Sims’s comments in his 2003 paper. This is claimed to increase the comparability of the marginal likelihood of various models. In their Dynare code, the following commands are for the calculation of the marginal likelihood with training sample:
// Calculation the marginal likelihood with training period (40 observations between '56 and '65)
// estimation(optim=(‘MaxIter’,200),datafile=usmodel_data,mode_compute=0,mode_file=usmodel_hist_dsge_f19_7_31_mode ,first_obs=31,nobs=200,presample=4,lik_init=2,prefilter=0,mh_replic=0,mh_nblocks=2,mh_jscale=0.20,mh_drop=0.2);
According to their documentation, mode_file=usmodel_hist_dsge_f19_7_31_mode is for the sample 1956:1-1965:4, then why nobs=200? ALso, mode_file=usmodel_hist_dsge_f19_7_3144_mode is for the sample 1956:1-2004:4, then why nobs=44?
My questions are:
- How to understand these commands?
- Does Dynare automatically take the training sample method into account? If not, how can this method be realized in Dynare?
Thanks a lot!