We propose a theoretical framework for assessing whether a forecast model estimated over one period can provide good forecasts over a subsequent period. We formalize this idea by defining a forecast breakdown as a situation in which the out-of-sample performance of the model, judged by some loss...

We propose a theoretical framework for assessing whether a forecast model estimated over one period can provide good forecasts over a subsequent period. We formalize this idea by defining a forecast breakdown as a situation in which the out-of-sample performance of the model, judged by some loss...

We propose a new Information Criterion for Impulse Response Function Matching estimators of the structural parameters of macroeconomic models. The main advantage of our procedure is that it allows the researcher to select the impulse responses that are most informative about the deep parameters,...

This paper investigates whether oil price shocks have a reliable and stable out-of-sample relationship with the Canadian/U.S Dollar nominal exchange rate. Despite state-of-the-art methodologies and clean data, we …find paradoxically little systematic relation between oil prices and the exchange...

This paper proposes forecast optimality tests that can be used in unstable environments. They include tests for forecast unbiasedness, efficiency, encompassing, serial uncorrelation, and, in general, regression-based tests of forecasting ability. The proposed tests are applied to evaluate the...

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...