I have a confusion with the functionality of the dynare_sensitive command. I am trying to find the mean square error. I have found that the command dynare_sensitive works to find the rmse but I do not understand very well:

To use this command, is it necessary to make Bayesian estimates of the parameters of the model?

Does this command go before or after stoch_simul or where in the model does it go?

Can I find the errors of the variables with another command?

dynare_sensitivity computes rmse as one of the steps to carry out the sensitivity analysis as in Ratto’s computational economics paper I believe. Therefore, it doesn’t compute mse as output.

Yes.

It’s orthogonal I believe. You can run it after stoch_simul for sure.

clarify your question a bit?

Maybe formulate what you want to find in math so other people can help you better

The MSE is just an average squared deviation from some object. You can compute it for a variety of things. What is the exact object you are interested in?

I am evaluating different policy rules. Graph how each variable behaves before the shocks with each rule, it turns out that the graphs are very close visually, the difference is not seen. I needed to choose the best rule and I thought about using the mean square error as an indicator, something aspiring to measure the area under the curve. So I want to get the mean square error of each variable, I don’t know if this approach is wrong?
I hope to be clear

You again did not answer my question. Are you talking about the mean squared forecast error between actual data realizations and forecasts from the model?