Diffusion index model specification and estimation using mixed frequency datasets

Abstract

In this chapter, we discuss the use of mixed frequency models and diffusion index approximation methods in the context of prediction. In particular, recent specification and estimation methods are outlined, and an empirical illustration is provided wherein U.S. unemployment forecasts are constructed using both classical principal components-based diffusion indexes and a combination of diffusion indexes and factors formed using small mixed frequency datasets. Preliminary evidence that mixed frequency-based forecasting models yield improvements over standard fixed frequency models is presented.