To answer this question, we develop new testing methods for identifying superior forecasting skills in settings with arbitrarily many forecasters, outcome variables, and time periods. Our methods allow us to address if any economists had superior forecasting skills for any variables or at any...

We develop a Bayesian approach that performs variable selection in panel regression models that are subject to breaks. Our variable selection approach enables deactivation of pervasive regressors and activation of weak regressors for short periods. Allowing the coefficients on individual...

This paper develops new methods for testing equal predictive accuracy in panels of forecasts that exploit information in the time series and cross-sectional dimensions of the data. Using a common factor setup, we establish conditions on cross-sectional dependencies in forecast errors which allow...