Blanchard-Khan Condition is verified

General DSGE Modeling Macroeconomic Model Data Base
1

Hi all, I have a problem with this model where I get the following error

There are 15 eigenvalue(s) larger than 1 in modulus
for 15 forward-looking variable(s)

The rank condition is verified.

You did not declare endogenous variables after the estimation/calib_smoother command.
Error in computing likelihood for initial parameter values

ESTIMATION_CHECKS: There was an error in computing the likelihood for initial parameter values.
ESTIMATION_CHECKS: If this is not a problem with the setting of options (check the error message below),
ESTIMATION_CHECKS: you should try using the calibrated version of the model as starting values. To do
ESTIMATION_CHECKS: this, add an empty estimated_params_init-block with use_calibration option immediately before the estimation
ESTIMATION_CHECKS: command (and after the estimated_params-block so that it does not get overwritten):

Error using print_info
Error using print_info
Blanchard & Kahn conditions are not satisfied: indeterminacy.
Error in initial_estimation_checks (line 305)
print_info(info, DynareOptions.noprint, DynareOptions)
Error in dynare_estimation_1 (line 159)
oo_ = initial_estimation_checks(objective_function,xparam1,dataset_,dataset_info,M_,estim_params_,options_,bayestopt_,bounds,oo_);
Error in dynare_estimation (line 118)
dynare_estimation_1(var_list,dname);
Error in Cai_4HW5.driver (line 840)
oo_recursive_=dynare_estimation(var_list_);
Error in dynare (line 281)
evalin(‘base’,[fname ‘.driver’]);
Cai_4HW5.mod (20.1 KB)

I really don’t understand what the problem is, since rank condition IS VERIFIED.
Find attached the file

Thank you
Guido

2

You did not provide the data file. Have you tried starting the estimation with the parameter values you used for calibrating the model?

4

Hi, Thanks a lot for the fast reply.
First of all I attach the data file (sorry for that
SW_Data4HW.xls (271 KB)

I read a previous thread here and addeed:
estimated_params_init(use_calibration);

end;

that I imagine it does exactly what you were saying. However doing this leads to NaN s.d. in posterior distribution of parameters. Is that normal since I included this estimated_params_init(use_calibration); ?

Thank you

5

It seems your estimation gets stuck in a corner. Are you sure your priors/starting values match the data?