Testing for a Unit Root in Time Series with Pretest Data-Based Model Selection
The author examines the impact of data based lag length estimation on the behavior of the augmented Dickey-Fuller (ADF) test for a unit root. He derives conditions under which the augmented Dickey-Fuller test converges to the Dickey-Fuller distribution and verify that these conditions are satisfied by many popular lag selection strategies. Simulation evidence indicates that the performance of the augmented Dickey-Fuller test is considerably improved when the lag length is selected from the data. An application to inventory series illustrates that inference about a unit root can be very sensitive to the method of lag-length selection.
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Volume (Year): 12 (1994)
Issue (Month): 4 (October)
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