A Property of the Kullback--Leibler Divergence for Location-scale Models

In this paper, we discuss a property of the Kullback–Leibler divergence measured between two models of the family of the location-scale distributions. We show that, if model $M_1$ and model $M_2$ are represented by location-scale distributions, then the minimum Kullback–Leibler divergence from $M_1$ to $M_2$, with respect to the parameters of $M_2$, is independent from the value of the parameters of $M_1$. Furthermore, we show that the property holds for models that can be transformed into location-scale distributions. We illustrate a possible application of the property in objective Bayesian model selection.