Optimal invariant tests for the autocorrelation coefficient in linear regressions with stationary or nonstationary AR(1) errors

Jean Marie Dufour, Maxwell L. King

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82 Citations (Scopus)


Inference on the autocorrelation coefficient ρ{variant} of a linear regression model with first-order autoregressive normal disturbances is studied. Both stationary and nonstationary processes are considered. Locally best and point-optimal invariant tests for any given value of ρ{variant} are derived. Special cases of these tests include tests for independence and tests for unit-root hypotheses. The powers of alternative tests are compared numerically for a number of selected testing problems and for a range of design matrices. The results suggest that point-optimal tests are usually preferable to locally best tests, especially for testing values of ρ{variant} greater than or equal to one.

Original languageEnglish
Pages (from-to)115-143
Number of pages29
JournalJournal of Econometrics
Issue number1
Publication statusPublished - Jan 1991

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