Dear Professor Pfeifer,
I use the Taylor Rule as follow in the model, in which rhoRUU means the Monetary Policy inertia and rhoYUU the interest rate response to output growth.
RU = rhoRUU * RU(-1) + (1-rhoRUU)( log(RUU) + rhopiUU(piU(+1)-log(piUU))
+ rhoYUU*( YU-log(YUU) ) ) + e_R;
But the when I doing the Bayesian estimation, the result displays that the posterior mean of rhoRUU is 0.2 (prior mean is 0.75) and the posterior mean of rhoYUU is 0.8 (prior mean is 0.1). Is this result very strange or just acceptable ?How does this happen?
Any reply will be appreciated. Thank you very much!