We have a dataset with the level of export of a certain good towards Italy for almost all countries of the world for 15 years.
We want to infere the effect of the distance of such countries from italy on the exportation levels.
Since we have many time points for each country, I first though of using a mixed effect model with the countries as random intercept. But because my fixed effect of interest is the distance, and of course this values is unique for each countries, this would not make sense.
So, how should I include the impact of time on the relationship distance-exportation? Would it make sense to use time as the random intercept, even if it is expected that there is some degree of autocorrelation between the time points?