How to fit the observed shocks into a random model?

Hello everyone!

In dynare,
The deterministic model means perfect foresight, and the shocks are set with exact value;
The stochastic model means imperfect foresight, and the shocks are set with its variance.

I have built a stochastic model (RBC), and I have calibrated the parameters and the realized values of TFP shocks from historical Marco data. Now I want to introduce the realized values of TFP shocks into my stochastic model to see how the business cycle it generates would differ from the reality.

After reading the whole UserGuide, I still cant find the solution……if I choose stochastic model in dynare, I can only introduce the variance of shocks. if I choose deterministic model in dynare, the shocks will be perfect foreseen so it will not be in line with my model…

Thank you very much!

You could take a look at this post and I think it would be helpful for your problem

(P.S. I would probably call it rational expectation rather than imperfect foresight, and stochastic model rather than random model, just terminology… sounds a little weird to me.)

Yes, as indicated above, you need to use the simult_-function to feed in the shock series.

thank you stzfe! I read the code and it’s really helpful :grinning:

Thank you Professor Pfeifer! I tried simult_-function and it works.