I have successfully run my model with 7 shocks and 7 measurement equations. However, when it comes to estimation, Dynare encounters a problem of stochastic singularity. The error message is the following:
Blockquote 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.
Blockquote 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):
In the forum, Prof. Pfeifer mentioned that this usually occurs when the model implies at least one observable to be an exact linear combination of the other ones. But as far as I can see, this does not seem to be the problem in my model.
Also looking at the suggestions in the forum, I read that it is a good idea to run the code with just one varobs; i tried to do so by just including devlnY and indeed it is working fine.
I would like to ask you if there is any way I can include also the other variables in my database as observable.
Thank you for your help.