This paper proposes new iterative reduced-rank regression procedures for seasonal cointegration analysis. The suggested methods are motivated by the idea that modelling the cointegration restrictions jointly at different frequencies may increase efficiency in finite samples. Monte Carlo...

This paper proposes a reduced rank regression framework for constructing coincident and leading indexes. Based on a formal definition that requires that the first differences of the leading index are the best linear predictor of the first differences of the coincident index, it is shown that the...

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...