We introduce a new approach for the estimation of high-dimensional factor models with regime-switching factor loadings by extending the linear three-pass regression filter to settings where parameters can vary according to Markov processes. The new method, denoted as Markov-switching three-pass...

The paper is a keynote lecture from the Tilburg-Madrid Conference on Hypothesis Tests: Foundations and Applications at the Universidad Nacional de Educación a Distancia (UNED) Madrid, Spain, 15-16 December 2011. It addresses the role of tests of statistical hypotheses (specification tests) in...

Bayesian predictive synthesis is a flexible method of combining density predictions. The flexibility comes from the ability to choose an arbitrary synthesis function to combine predictions. I study the choice of synthesis function when combining large numbers of predictions-a common occurrence...

Bayesian predictive synthesis (BPS) is a method of combining predictive distributions based on agent opinion analysis theory, which encompasses many common approaches to combining density forecasts. The key ingredient in BPS is a synthesis function. This is typically specified parametrically as...