We investigate the power and size performance of unit root tests when the true data generating process undergoes Markov regime-switching. All tests, including those robust to a single break in trend growth rate, have very low power against a process with a Markov-switching trend growth rate as...

Using Bayesian tests for a structural break at an unknown break date, we search for a volatility reduction within the post-war sample for the growth rates of U.S. aggregate and disaggregate real GDP. We find that the growth rate of aggregate real GDP has been less volatile since the early...

Several recent papers conclude that U.S. real GDP is trend stationary, implying that all shocks are transitory and the long run path is deterministic. These inferences fail to take into account two problems: the distortion of test size in finite samples due to data-based model selection and the...

Recent research has proposed the state space (88) framework for decomposition of GNP and other economic time series into trend and cycle components, using the Kalman filter. This paper reviews the empirical evidence and suggests that the resulting decomposition may be spurious, just as...

Estimates of the natural or full employment level of real GNP have usually been obtained by statistical detrending procedures which assume independence between trend and cycle. This paper presents an alternative approach which says that the natural level should be measured in the context of a...

Hall (1978) showed that the permanent income hypothesis implies that consumption (1) follows a random walk, and (2) cannot be predicted by past income. Reexamination of Hall's data results in rejection of the random walk hypothesis in favor of the alternative hypothesis of positively...

Regression of a trendless random walk on time produces R-squared values around .44 regardless of sample length. The residuals from the regression exhibit only about 14 percent as much variation as the original series even though the underlying process has no functional dependence on time. The...