Just for the better understanding:

When I run a bayesian estimation, what is dynare doing before the metropolis hastings iteration? From the code I know that dynare is something optimizing. But what?

So far I think this is going on:

- Declare the prior distributions to give informations to the parameters.
- Calculate the likelihood of the model (with the kalman filter?).
- Try to minimize the negative likelihood of the model to estimate the parameters?? Is this the optimisation step??
- Explore the posterior statistical propeties of the parameters with the metropolis hastings algorithm (because integration is too difficult), by using the bayes-rule.

Did I understand the estimation right?