We argue that the current framework for predictive ability testing (e.g., West, 1996) is not necessarily useful for real-time forecast selection, i.e., for assessing which of two competing forecasting methods will perform better in the future. We propose an alternative framework for...

We provide an extensive evaluation of the predictive performance of the U.S. yield curve for U.S. GDP growth by using a new test for forecast breakdown as well as a variety of in-sample and out-of-sample testing procedures. Empirical research over the past decades uncovered a strong predictive...

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...

We propose a framework for out-of-sample predictive ability testing and forecast selection designed for use in the realistic situation in which the forecasting model is possibly misspecified, due to unmodeled dynamics, unmodeled heterogeneity, incorrect functional form, or any combination of...

We provide an extensive evaluation of the predictive performance of the US yield curve for US gross domestic product growth by using new tests for forecast breakdown, in addition to a variety of in-sample and out-of-sample evaluation procedures. Empirical research over the past decades has...

We propose a test for comparing the out-of-sample accuracy of competing density forecasts of a variable. The test is valid under general conditions: the data can be heterogeneous and the forecasts can be based on (nested or non-nested) parametric models or produced by semi- parametric,...

We explore convenient analytic properties of distributions constructed as mixtures of scaled and shifted t-distributions. Particularly desirable for econometric applications are closed-form expressions for antiderivatives (e.g., the cumulative density function). We illustrate the usefulness of...