Thinking beyond averages: Quantile regression modelling and military expenditure

The study of military spending has been an enduring concern within sociology and political science. Methodologically, one the biggest challenges lay in dealing with its heavy-tailed distribution influenced by growing separation between China United States from rest world. In presence outliers along continuum expenditure, we should be paying more attention to portions that don’t assume values reported at conditional mean. article uses quantile regression modelling (QRM) analyse nuanced relationship expenditure predictors. It argues classical linear produces average estimates cannot predict different subsets data’s distribution, meanwhile QRM relevant results search for noncentral often laying lower upper tails distribution.