Complex Reduced Rank Models for Seasonally Cointegrated Time Series

Abstract

This paper introduces a new representation for seasonally cointegrated variables, namely the complex error correction model, which allows statistical inference to be performed by reduced rank regression. The suggested estimators and tests statistics are asymptotically equivalent to their maximum likelihood counterparts. Tables are provided for both asymptotic and finite sample critical values, and an empirical example is presented to illustrate the concepts and methods.