Hi,
this is the first time for me, actively using this forum. Hence, I would like to start with saying, that it is really helpful! I found out that most problems I had, have already been discussed by someone else.
Here is my problem/question: I estimate a huge model with about 56 equations and more than 40 parameters. I need to use the monte carlo based optimization routine (mode_compute = 6) to find starting values for the MH. I have several shocks in the model and I set some of them to to zero that seem to be of no importance after a first estimation. However, I forgot to cancel out the AR(1) parameters of 3 shocks that are set to 0, when estimating the model (so I estimated 3 unused parameters). After I realized this I repeated the estimation without estimating these parameter and the results dramtically changed!? In fact, the results with the unused parameters are much better! And I checked the code several times to be sure, that the parameters are unused (they only appear multiplied by a zero shock).
Now I have 3 questions:
-
Has anyone an explanation for this? I thought, that this would not change the estimation of any other parameter, since varying the unsed parameter does not change anything in the model dynamics.
-
Is it possible that this improves the starting values somehow, so that the MH converge to a different result?
-
Most important: Is the estimation reliable? I was really happy about the result!
Thanks for any comments/suggestions/solutions.
Best,
Michael