Unexpected results of hierarchical model for prediction of election results

Questions
3

Actually, the way you are modelling should be fine - the problem might be just the inefficiency of Metropolis then. You can generate posterior prediction like this maybe:
post_predi = np.random.binomial(p=trace['pm_event_prob'][:,10:], n=1)