A Comparison of Unit-Root Test Criteria
The ordinary least squares estimator has been widely used for testing the unit-root hypothesis in autoregressive processes. Recently, several new criteria, based on maximum likelihood and weighted symmetric estimators, have been proposed. In this article, the authors describe several different test criteria. Results from Monte Carlo studies that compare the power of the different test criteria indicate that the new tests are more powerful against the stationary alternative. Of the procedures studied, the weighted symmetric estimator and the unconditional maximum likelihood estimator provide the most powerful tests against the stationary alternative. The weekly series of one-month treasury bill rates is analyzed.
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Volume (Year): 12 (1994)
Issue (Month): 4 (October)
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