# How to estimate an mlogit (R package) model with a fixed (offset) variable

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?