I understand that binning is generally frowned upon as you are "throwing away information". However, I'm not sure whether I should in this instance.
I am running a logit regression. One of my control variables is continuous. However the majority of its observations are within spikes at 12 months, 24 months, 36 months, 48 months and 60 months (histogram shown below). It is fairly uncommon to observe any months in between (other than within the first year). As you can see, it is behaving "almost" like a discrete variable.
I have considered banding this by year (i.e. 0-1 year, 1-2 years, etc.). Would this be advisable, or is it still a bad decision to bin in this instance? Note the pseudo R2 value and classification of the model rose with these bands, albeit small.