Blanchard & Kahn conditions are not satisfied: no stable equilibrium

Estimation ML/Bayesian estimation
1

Hi all,
I get the following error message when running the code: “Blanchard & Kahn conditions are not satisfied: no stable equilibrium.”.
I’m currently looking for the cause, but it’s not clear. If anyone knows, I would be grateful if you could point out what went wrong.
Thank you in advance!
Hz.mod (11.8 KB)

2

See

3

Dear Johannes,
As your suggestion, I used diffuse_filter in the estimation-command.However, new problems arised.

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

The rank condition is verified.

initial_estimation_checks:: The forecast error variance in the multivariate Kalman filter became singular.
initial_estimation_checks:: This is often a sign of stochastic singularity, but can also sometimes happen by chance
initial_estimation_checks:: for a particular combination of parameters and data realizations.
initial_estimation_checks:: If you think the latter is the case, you should try with different initial values for the estimated parameters.

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 initial_estimation_checks (line 153)
initial_estimation_checks:: The forecast error variance in the multivariate Kalman filter became singular.
error initial_estimation_checks (line 153)
error(‘initial_estimation_checks:: The forecast error variance in the multivariate Kalman filter became singular.’)
error dynare_estimation_1 (line 164)
oo_ = initial_estimation_checks(objective_function,xparam1,dataset_,dataset_info,M_,estim_params_,options_,bayestopt_,bounds,oo_);
error dynare_estimation (line 105)
dynare_estimation_1(var_list,dname);
error papert.driver (line 1150)
oo_recursive_=dynare_estimation(var_list_);
error dynare (line 293)
evalin(‘base’,[fname ‘.driver’]) ;

4

Now your are facing stochastic singularity, because you are not allowed to observed a perfect linear combination of variables.

Take

Ghat = That*Tss/Gss+Mhat*Mss/Gss-(Mhat(-1)-pihat)*Mss/(Gss*piss);

From what I can see, all variables in that equation are declared as observed.