The Role of Common Cyclical Features for Coincident and Leading Indexes Building

In this paper we propose a new methodology to build composite coincident and leading indexes. Based on a formal definition which requires that the first difference of the leading index is the best linear predictor of the first difference of the coincident index, we show that the notion of polynomial serial correlation common features can be used to build these composite variables. Concepts and methods are illustrated by an empirical investigation of the US business cycle movements.