An additional technical reason involves the concept of an “admissible” decision procedure—one which isn’t “dominated” by some other decision procedure, which is at least as good in all possible situations and better in some. It turns out that (ignoring a few technical details involving infinities or zero probabilities) the set of admissible decision procedures is the same as the set of Bayesian decision procedures.
However, the real reason for using Bayesian statistical methods is that they work well in practice. And this is also how one comes to sometimes not use Bayesian methods, because there are problems in which the computations for Bayesian methods are infeasible and/or the intellectual labour in defining a suitable prior is excessive.
An additional technical reason involves the concept of an “admissible” decision procedure—one which isn’t “dominated” by some other decision procedure, which is at least as good in all possible situations and better in some. It turns out that (ignoring a few technical details involving infinities or zero probabilities) the set of admissible decision procedures is the same as the set of Bayesian decision procedures.
However, the real reason for using Bayesian statistical methods is that they work well in practice. And this is also how one comes to sometimes not use Bayesian methods, because there are problems in which the computations for Bayesian methods are infeasible and/or the intellectual labour in defining a suitable prior is excessive.