Dear all,
I know this has been questioned here numerous times, but having done everything I read in this forum the problem is still there. I am trying to estimate a BGG type of model with an uncertainty shock among other shocks. I have transformed the data as the observation equations in log deviations, I have more or equal shocks than observables, I checked the model_diagnostics and also the identification command. All shocks are identified. I keep getting the following well known error:
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)
Any ideas on what’s wrong?
Thanks,
Stelios
BGG_estim.zip (10.9 KB)