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ABSTRACTConventional unit root tests are biased towards non‐rejection of the null when applied to variables characterized by a one‐time change in their mean. Suggested modifications allowing for a break point require identification of an exogenous change initiated at the time of the break and not subsequently reversed. This paper suggests that modified tests are particularly useful in dealing with legislative changes. Two UK examples are given; the abolition of exchange controls in 1979 and the changes in monetary policy in 1980. Results suggest that allowing for a break changes the apparent order of integration of portfolio shares and real interest rates.

A counter‐example from chaos theory is used to challenge the augmented Dickey‐Fuller (ADF) test and common prewhitening techniques. The ADF test is applied to data constructed from a fully deterministic nonlinear (chaotic) process. The null hypothesis, that a unit root is present, cannot be rejected; "stationarity" is achieved by prewhitening. The largest Lyapunov exponent and the correlation dimension are estimated for the original and conditioned series in efforts to detect the nonlinearity and ascertain information regarding its specification. This is repeated in the presence of additive white noise. In no case is the procedure successful, nor is misspecification avoided. Along the way, the tests for nonlinearity provide evidence in support of the results of Nelson and Plosser (1982), that the removal of deterministic trends from time series that appear to be unit root processes can lead to spurious results.