The Properties of Cointegration Tests in Models with Structural Change

In this paper we examine, by means of Monte Carlo simulation, the properties of several cointegration tests when long run parameters are subject to structural changes. We allow for different types of stochastic and deterministic regime shifts, more specifically, changes governed by Markov chains, martingale parameter variation, sudden multiple breaks and gradual changes. Our Monte Carlo analysis reveals that tests with cointegration as the null hypothesis perform badly, while tests with the null of no cointegration retain much of their usefulness in this context.