Parameter Constancy in Cointegrating Regressions.

This paper proposes an approach to testing for coefficient stability in cointegrating regressions in time series models. The test statistic considered is the one-sided version of the Lagrange Multiplier (LM) test. Its limit distribution is non-standard but is nuisance parameter free and can be represented in terms of a stochastic bridge process which is tied down like a Brownian bridge but relies on a random rather than a deterministic fraction do so. The approach provides a test of the null hypothesis of cointegration against specific directions of departure from the null; subset coefficient stability tests are also available. A small simulation studies the size and power properties of these tests and an empirical illustration to Australian data on consumption, disposable income, inflation and money is provided.