Complex reduced rank models for seasonally cointegrated time series

This paper introduces a new representation for seasonally cointegrated vari ables, namely the complex error correction model, which allows statistical inference to be performed by reduced rank regression. The suggested estimat ors and tests statistics are asymptotically equivalent to their maximum lik elihood counterparts. The small sample properties are evaluated by a Monte Carlo study and an empirical example is presented to illustrate the concept s and methods.