Size and power properties of powerful unit root tests in the presence of variance breaks

Abstract

The standard Dickey–Fuller (DF) test is routinely employed to analyse the integrated nature of economic and financial time series. However, recent research has shown the test to suffer severe size distortion in the presence of breaks in innovation variance under the unit root null hypothesis. In this paper, the properties of alternative, more powerful unit root tests are examined in such circumstances. Simulation experiments are undertaken to permit a comparison of the behaviour of the alternative tests and a recently proposed ‘variance break robust’ unit root test. The results derived across a range of breakpoints and break sizes show a marked difference in the size and power properties of the rival tests. It is found that over a range of breaks and sample sizes, weighted symmetric or recursively mean-adjusted unit root tests are to be preferred to both the standard DF test and the robust test.