Dear Professor Pfeifer,
When I use Bayesian approach to estimate the parameters in the model, I choose, for example, 6 observation series as there are 6 shocks and get results which seem ideal. However, when I change one of the series to a new one (e.g. I substitute output series for interest rate series), the results still seem acceptable while the values of estimated parameters are a little different and the conditional variance decomposition of variables is quite different.
Is this normal when doing bayesian estimation? Does this mean the results are not robust ? Or I just need to compare the model implied moments with data moments and choose the more fitted results ?
Thank you for your time.