Abstract
A more powerful version of the augmented Dickey–Fuller test and a test that has trend stationarity as the null are applied to U.S. gross national product. Simulated critical values generated from plausible trend- and difference-stationary models are used to minimize possible finite-sample biases. The discriminatory power of the two tests is evaluated using alternative-specific rejection frequencies. For postwar quarterly data, these two tests do not provide a definite conclusion. When analyzing annual data over the 1869–1986 period, however, the unit-root null is rejected, but the trend-stationary null is not.
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