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Dóra Kocsis
dynare
Commits
81159272
Commit
81159272
authored
Sep 21, 2011
by
Stéphane Adjemian
Browse files
Reduced the number of MCMC simulations. Deleted trailing whitespace.
parent
c309b0cf
Changes
2
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tests/dsge-var/dsgevar_forward_calibrated_lambda.mod
View file @
81159272
//$ Declaration of the endogenous variables of the DSGE model.
var a g mc mrs n winf pie r rw y;
//$ Declaration of the exogenous variables of the DSGE model.
//$ Declaration of the exogenous variables of the DSGE model.
varexo e_a e_g e_lam e_ms;
//$ Declaration of the deep parameters
parameters invsig delta gam rho gampie gamy rhoa rhog bet
parameters invsig delta gam rho gampie gamy rhoa rhog bet
thetabig omega eps ;
eps=6;
...
...
@@ -22,7 +22,7 @@ rhog=0.5;
rho=0.5;
//$ Specification of the DSGE model used as a prior of the VAR model.
//$ Specification of the DSGE model used as a prior of the VAR model.
model(linear);
y=y(+1)-(1/invsig)*(r-pie(+1)+g(+1)-g);
...
...
@@ -45,7 +45,7 @@ end;
//$ Declaration of the prior beliefs about the deep parameters.
//$ Declaration of the prior beliefs about the deep parameters.
estimated_params;
stderr e_a, uniform_pdf,,,0,2;
stderr e_g, uniform_pdf,,,0,2;
...
...
@@ -67,13 +67,13 @@ estimated_params;
end;
//$ Declaration of the observed endogenous variables. Note that they are the variables of the VAR (4 by default) and that we must
//$ have as many observed variables as exogenous variables.
//$ Declaration of the observed endogenous variables. Note that they are the variables of the VAR (4 by default) and that we must
//$ have as many observed variables as exogenous variables.
varobs pie r rw y;
options_.gradient_method = 3;
//$ The option bayesian_irf triggers the computation of the DSGE-VAR and DSGE posterior distribution of the IRFs.
//$ The Dashed lines are the first, fifth (ie the median) and ninth posterior deciles of the DSGE-VAR's IRFs, the bold dark curve is the
//$ posterior median of the DSGE's IRfs and the shaded surface covers the space between the first and ninth posterior deciles of the DSGE's IRFs.
estimation(datafile=datarabanal_hybrid,first_obs=50,mh_nblocks = 1,nobs=90,dsge_var=.8,mode_compute=4,mh_replic=
4
000,bayesian_irf);
//$ The Dashed lines are the first, fifth (ie the median) and ninth posterior deciles of the DSGE-VAR's IRFs, the bold dark curve is the
//$ posterior median of the DSGE's IRfs and the shaded surface covers the space between the first and ninth posterior deciles of the DSGE's IRFs.
estimation(datafile=datarabanal_hybrid,first_obs=50,mh_nblocks = 1,nobs=90,dsge_var=.8,mode_compute=4,mh_replic=
2
000,bayesian_irf);
tests/dsge-var/dsgevar_forward_estimated_lambda.mod
View file @
81159272
//$ Declaration of the endogenous variables of the DSGE model.
var a g mc mrs n winf pie r rw y;
//$ Declaration of the exogenous variables of the DSGE model.
//$ Declaration of the exogenous variables of the DSGE model.
varexo e_a e_g e_lam e_ms;
//$ Declaration of the deep parameters and of dsge_prior_weight
parameters invsig delta gam rho gampie gamy rhoa rhog bet
parameters invsig delta gam rho gampie gamy rhoa rhog bet
thetabig omega eps ;
eps=6;
...
...
@@ -22,7 +22,7 @@ rhog=0.5;
rho=0.5;
//$ Specification of the DSGE model used as a prior of the VAR model.
//$ Specification of the DSGE model used as a prior of the VAR model.
model(linear);
y=y(+1)-(1/invsig)*(r-pie(+1)+g(+1)-g);
...
...
@@ -45,7 +45,7 @@ end;
//$ Declaration of the prior beliefs about the deep parameters and the weight of the DSGE prior.
//$ Declaration of the prior beliefs about the deep parameters and the weight of the DSGE prior.
estimated_params;
stderr e_a, uniform_pdf,,,0,2;
stderr e_g, uniform_pdf,,,0,2;
...
...
@@ -68,13 +68,13 @@ estimated_params;
end;
//$ Declaration of the observed endogenous variables. Note that they are the variables of the VAR (4 by default) and that we must
//$ have as many observed variables as exogenous variables.
//$ Declaration of the observed endogenous variables. Note that they are the variables of the VAR (4 by default) and that we must
//$ have as many observed variables as exogenous variables.
varobs pie r rw y;
options_.gradient_method = 3;
//$ The option bayesian_irf triggers the computation of the DSGE-VAR and DSGE posterior distribution of the IRFs.
//$ The Dashed lines are the first, fifth (ie the median) and ninth posterior deciles of the DSGE-VAR's IRFs, the bold dark curve is the
//$ posterior median of the DSGE's IRfs and the shaded surface covers the space between the first and ninth posterior deciles of the DSGE's IRFs.
estimation(datafile=datarabanal_hybrid,first_obs=50,mh_nblocks = 1,nobs=90,dsge_var,mode_compute=4,mh_replic=
4
000,bayesian_irf);
//$ The Dashed lines are the first, fifth (ie the median) and ninth posterior deciles of the DSGE-VAR's IRFs, the bold dark curve is the
//$ posterior median of the DSGE's IRfs and the shaded surface covers the space between the first and ninth posterior deciles of the DSGE's IRFs.
estimation(datafile=datarabanal_hybrid,first_obs=50,mh_nblocks = 1,nobs=90,dsge_var,mode_compute=4,mh_replic=
2
000,bayesian_irf);
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