Economists have recognized the possibility that a time series may change structure from trend-stationarity to difference-stationarity, or vice versa. Taking difference-stationarity as the null hypothesis, we develop tests for this possibility, where neither the location nor direction of any...

We analyse the case where a unit-root test is based on a Dickey-Fuller regression the only deterministic term of which is a fixed intercept. Suppose, however, as could well be the case, that the actual data-generating process includes a broken linear trend. It is shown theoretically, and...

Unit root tests, seeking mean or trend reversion, are frequently applied to panel data. We show that more powerful variants of commonly applied tests are readily available. Moreover, power gains persist when the modifications are applied to bootstrap procedures that may be employed when...

Although the t-ratio variant of the Dickey-Fuller test is the most commonly applied unit-root test in practical applications, it has been known for some time that readily implementable, more powerful modifications are available. We explore the large-sample properties of five of these modified...

Using standardized cumulative sums of squared sub-sample residuals, we propose a new ratio-based test of the null hypothesis that a time series exhibits no change in its persistence structure [specifically that it displays constant I(1) behaviour] against the alternative of a change in...

This paper considers the problem of testing for and dating changes (at unknown points) in the order of integration of a time series between different trend-stationary and difference-stationary regimes. While existing procedures in the literature are designed for processes displaying only a...

Many structural models have attempted to explain the behaviour of exchange rates under the floating rate regime. Meese and Rogoff (1983) found that a random walk model performs at least as well as various structural and time series models for exchange rates in terms of out-of-sample forecast....