Sentiment shock and Kalman filter

Estimation ML/Bayesian estimation
1

Dear Johannes,
Thank you very much for your guidance last time, I am grateful.
I have a question regarding a DSGE model with the stock market.
In my model, i have incorporated a sentiment shock to capture investors’ behaviour that makes realised future stock market index price deviates from agents’ expected index price, the following is my specification:
Ps(+1)=E(Ps(+1))+U
Ps(+1) is realised future stock market index price.
E(Ps(+1)) is expected future stock market index price, E is expectation, U is sentiment shock
U is identically and independently distributed with mean zero and constant variance.

I have incorporated this specification of sentiment shock into my Dynare program and the model is well identified.

I am wondering that does incorporation of my sentiment shock is ok with Kalman filter?

And is it appropriate or not appropriate to call this shock sentiment shock?

Thank you very much and look forward to hearing from you.

Best regards,

Jesse
PhD Candidate

2

I don’t see why you should have a problem with the Kalman filter/estimation. I am not sure I understand the setuo, though. What is the information set of the expectations here? And how did you enter the equation into Dynare?