Hypothesis Testing for Cointegration Vectors: with Application to the Demand for Money in Denmark and Finland

The purpose of this paper is to give a systematic account of the maximum likelihood inference concerning cointegration vectors in non-stationary vector value autoregressive time series with Gaussian errors. The hypothesis of r cointegration vectors is given a simple parametric formulation in terms of cointegration vectors and their weights. We then estimate and test linear hypotheses about these. We find that the asymptotic inference for the linear hypotheses can be performed by applying the usual ² test. We also give some very simple Wald test and their asymptotic properties. The methids are illustrated by data from the Danish and the Finnish economy on the demand for money.