Error in mode finding
Posted: Tue Sep 23, 2014 8:50 amDear helper,
I constructed a log-linearized model. I transformed my data according to your guide paper. To be specific, I first take log-difference and then demean the non-stationary data. As for the stationary data, for example inflation and interest rate, I just take log and demean the data. Thus I think my observables exactly represent the percentage deviation from the steady state, which can match my model variable correctly. I set "mode_compute=6". I also have used the "identification" command, which shows that
==== Identification analysis ====
Testing prior mean
-----------
Parameter error:
The model does not solve for prior_mean with error code info = 3
info==3 %! Blanchard & Kahn conditions are not satisfied: no stable equilibrium.
-----------
Try sampling up to 50 parameter sets from the prior.
All parameters are identified in the model (rank of H).
All parameters are identified by J moments (rank of J)
==== Identification analysis completed ====
Q1: Does it mean all the parameters are identified? If yes, why does it show that "The model does not solve for prior_mean with error code info = 3
info==3 %! Blanchard & Kahn conditions are not satisfied: no stable equilibrium." ?
Q2: Since mode_compute=6 is very inefficient and it takes about 3 hours for each round, when I set "mode_compute=4", it first shows that
POSTERIOR KERNEL OPTIMIZATION PROBLEM!
(minus) the hessian matrix at the "mode" is not positive definite!
=> posterior variance of the estimated parameters are not positive.
You should try to change the initial values of the parameters using
the estimated_params_init block, or use another optimization routine.
Warning: The results below are most likely wrong!
> In dynare_estimation_1 at 694
In dynare_estimation at 89
In code at 1033
In dynare at 180
And then stop Error using chol
Matrix must be positive definite.
Error in metropolis_hastings_initialization (line 68)
d = chol(vv);
Error in random_walk_metropolis_hastings (line 62)
[ ix2, ilogpo2, ModelName, MetropolisFolder, fblck, fline, npar, nblck, nruns, NewFile,
MAX_nruns, d ] = ...
Error in dynare_estimation_1 (line 782)
feval(options_.posterior_sampling_method,objective_function,options_.proposal_distribution,xparam1,invhess,bounds,dataset_,options_,M_,estim_params_,bayestopt_,oo_);
Error in dynare_estimation (line 89)
dynare_estimation_1(var_list,dname);
Error in code (line 1033)
dynare_estimation(var_list_);
Error in dynare (line 180)
evalin('base',fname) ;
What is the problem and how to fix it?
Q3: As for the graphs of impulse response functions, I found it seems to be odd, which means that it fluctuates up and down the steady state for two or three tims, and some converge to the steady state very quickly. Is this result reliable? If not, how to fix it?
Here attached the impulse response graphs and my code&data file. Any help is highly appreciated!
Regards,
I constructed a log-linearized model. I transformed my data according to your guide paper. To be specific, I first take log-difference and then demean the non-stationary data. As for the stationary data, for example inflation and interest rate, I just take log and demean the data. Thus I think my observables exactly represent the percentage deviation from the steady state, which can match my model variable correctly. I set "mode_compute=6". I also have used the "identification" command, which shows that
==== Identification analysis ====
Testing prior mean
-----------
Parameter error:
The model does not solve for prior_mean with error code info = 3
info==3 %! Blanchard & Kahn conditions are not satisfied: no stable equilibrium.
-----------
Try sampling up to 50 parameter sets from the prior.
All parameters are identified in the model (rank of H).
All parameters are identified by J moments (rank of J)
==== Identification analysis completed ====
Q1: Does it mean all the parameters are identified? If yes, why does it show that "The model does not solve for prior_mean with error code info = 3
info==3 %! Blanchard & Kahn conditions are not satisfied: no stable equilibrium." ?
Q2: Since mode_compute=6 is very inefficient and it takes about 3 hours for each round, when I set "mode_compute=4", it first shows that
POSTERIOR KERNEL OPTIMIZATION PROBLEM!
(minus) the hessian matrix at the "mode" is not positive definite!
=> posterior variance of the estimated parameters are not positive.
You should try to change the initial values of the parameters using
the estimated_params_init block, or use another optimization routine.
Warning: The results below are most likely wrong!
> In dynare_estimation_1 at 694
In dynare_estimation at 89
In code at 1033
In dynare at 180
And then stop Error using chol
Matrix must be positive definite.
Error in metropolis_hastings_initialization (line 68)
d = chol(vv);
Error in random_walk_metropolis_hastings (line 62)
[ ix2, ilogpo2, ModelName, MetropolisFolder, fblck, fline, npar, nblck, nruns, NewFile,
MAX_nruns, d ] = ...
Error in dynare_estimation_1 (line 782)
feval(options_.posterior_sampling_method,objective_function,options_.proposal_distribution,xparam1,invhess,bounds,dataset_,options_,M_,estim_params_,bayestopt_,oo_);
Error in dynare_estimation (line 89)
dynare_estimation_1(var_list,dname);
Error in code (line 1033)
dynare_estimation(var_list_);
Error in dynare (line 180)
evalin('base',fname) ;
What is the problem and how to fix it?
Q3: As for the graphs of impulse response functions, I found it seems to be odd, which means that it fluctuates up and down the steady state for two or three tims, and some converge to the steady state very quickly. Is this result reliable? If not, how to fix it?
Here attached the impulse response graphs and my code&data file. Any help is highly appreciated!
Regards,