I have a (I suspect) simple question. I have time series cross section data on voting behaviour in the Council of the European Union (the monthly number of yes, no and abstentions for each member state from 1999 to 2007). So basically the variables are counts, thus a Poisson/negative binomial regression would be appropriate, possibly with lagged dependent variables on the right hand side to control for time dependencies. I have seen papers with people using such negative binomial models to forecast, for instance the number of monthly legislative acts adopted in the future, and I have three questions in this regard:
How can i run a negative binomial regression on panel data without making any inferential mistakes?
How can I use a negative binomial model with lags to forecast future values of the dependent variable.
Can this be done in R?