I am trying to estimate a multinomial logit model using an offset variable with the mlogit package of R
Using the syntax here [https://stat.ethz.ch/R-manual/R-devel/library/stats/html/formula.html] it seems that the correct way to do this is to use something like this
v <- mFormula(choice ~ gc + log_gc + offset(log_attr) + 0)
which you would then pass to the model estimation as
model <- mlogit(v, mlogit_data)
Printing the coefficients seems to indicate that the parameter has not been estimated
model$coefficients gc log_gc -0.003023088 -0.477115780 attr(,"fixed") gc log_gc
However these parameters are exactly the same as the parameters I get if I don't include the variable log_attr at all... ie
v_no_log_attr <- mFormula(choice ~ gc + log_gc + 0) model_no_log_attr <- mlogit(v_no_log_attr, mlogit_data) model_no_log_attr$coefficients gc log_gc -0.003023088 -0.477115780 attr(,"fixed") gc log_gc FALSE FALSE
Given that the data has significant variation in this variable, I feel that this is unexpected and that the mlogit package is simply ignoring the offset variable.
Is this possible to do with this package? Do I have a misunderstanding of how to perform the estimation?