It never occurred to me that imposing finite bounds might increase the complexity of a simulation
As a trivial point, imposing finite bounds means that you can't use the normal distribution, for example :-)
Not true: it means you shouldn't use a normal distribution, and when you do you should say so up front. I see no reason not to apply normal distributions if your limit is high (say, greater than 4 sigmas--social science is much fuzzier than physical science). Better yet, make your limit a function of the number of observations you have. As the probability of getting into the long tail gets higher, make the tail longer.
As per a recent comment this thread is meant to voice contrarian opinions, that is anything this community tends not to agree with. Thus I ask you to post your contrarian views and upvote anything you do not agree with based on personal beliefs. Spam and trolling still needs to be downvoted.