The goal of this paper is to develop formal techniques for analyzing the relative in-sample performance of two competing, misspecified models in the presence of possible data instability. The central idea of our methodology is to propose a measure of the models' local relative performance: the...

The goal of this paper is to develop formal tests to evaluate the relative in-sample performance of two competing, misspecified non-nested models in the presence of possible data instability. Compared to previous approaches to model selection, which are based on measures of global performance,...

The goal of this article is to develop formal tests to evaluate the relative in‐sample performance of two competing, misspecified, nonnested models in the presence of possible data instability. Compared to previous approaches to model selection, which are based on measures of global...