Hi all,
I have a question about how stoch simul works if I put this command after doing Bayesian estimation. Ideally I would like stochastic simulation to use all the estimated parameters and perform the simulation to print theoretical moments and correlations. But I suspect, it does not do it. It basically takes the parameter values declared at the start of the mod file and ignores all the estimated parameters to do the stoch simul. Am I right?

No after the estimation command the parameter values are updated according to the inference. If you do not run a MCMC, the estimated parameters are updated to the posterior mode estimate. If you run a MCMC (mh_replic>0) the estimated parameters are updated to the posterior mean. If you find an example where this is not the case, it may be a bug on our side.

Hi Stephane,
Thank you for your email response to my query.
I attach a code and the datafile where stochastic simulation follows the Bayesian estimation and I see a major difference in variance decomposition results.

There is one more strange thing happening in this code which I can’t resolve. I have brought a variable iR which is fixed at irbar always. However, in variance decomposition, its variance is explained by two shocks. Since iR is a constant, its variance is zero by default. How come its variance is explained some shocks? This is very puzzling to me. I am using dynare 4.5.4…

Thank you for this comment. I am aware of this issue. However, I don’t quite see why parameter dependence is an issue here. In fact the model has a steady state at biglamda=1.02. No obvious problem is detected in model diagnostics.

The problem only occurs at the estimation level. I am setting the prior in such a way that biglamda is plausible. This is based on Japanese data and biglanda=1.02 may be too high. Thus I don’t see what is really the issue here.

STEADY-STATE RESULTS:

m 0.951557
iL 0.0509091
k 20.635
h 1.75179
y 4.22659
c 2.31622
i 0.910368
d 1.04818
mR 0.994868
mT 0.760232
mRprop 0.566844
mm 1.03037
S 15.1376
pii 0.02
Q 1
realW 1.15811
Adj 0
Adjprime 0
P_Pw 1.33333
A 1
div 0.10784
Debt 9.82259
ytd 1.05091
Rytd 1.0303
hpr 1.05091
rhpr 1.0303
rk 0.030303
bg 0.648886
G 1
T 0.991378
lamda 0.4
Zx 1
ip 0.001
ytm2 0.0296556
Sr 22
tp 0.0198026
nytm 0.0496556
mR_d 0.949142
log_y 1.44139
log_c 0.839936
log_i -0.0939066
log_G 0
log_mR -0.0051453
log_mT -0.274131
log_d 0.0470518
log_h 0.560637
log_Q 0
log_S 2.71718
log_k 3.02699
mbgrate 1.02
y_obs 0
i_obs 0
G_obs 0
c_obs 0
mR_obs 0
mT_obs 0
d_obs 0
h_obs 0
k_obs 0
Q_obs 0
S_obs 0
MODEL_DIAGNOSTICS: No obvious problems with this mod-file were detected.

I will be grateful if you please elaborate a bit on this.

which both depend on biglamda. For the first run with biglamda=1.02, everything works fine. But in estimation, the prior mean is biglamda=1.01. As the two composite parameters above are not updated to reflect the new value for biglamda, you get an error message.

Thanks for this. I don’t know how to merge this. I am using dynare 4.5.2.

I think I will bypass the MCMC by setting mh_replic to zero and only use mode compute and then put stochastic simulation right below it. I believe that I will then get VD based on stochastic simulation using the posterior mode estimates. This should be bug free. Am I right?