A test to determine whether a time series is stationary or, specifically, whether the prediction intervals are almost constant. The point forecasts of a DS series are constant as the horizon is increased (like naive no-change forecasts), other things being equal, while the prediction intervals widen rapidly. There is a vast literature on unit roots. The expression "unit root test$" ($ indicates a wildcard) generated 281 hits in the Econolit database of OVID (as of mid-December, 1999), although when it was combined with “forecast$,” the number fell to 12. Despite this literature, we can say little about the usefulness of a unit-root test, such as the Dickey-Fuller test, as part of a testing strategy to improve forecasting accuracy. Meese and Geweke (1984) examined 150 quarterly and monthly macroeconomic series and found that forecasts from detrended data (i.e., assuming TS) were more accurate than forecasts from differenced data. Campbell and Perron (1991) conducted a forecasting model. Maddala and Kim (1998) provide a helpful summary.