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A Comparison of Unit-Root Test Criteria
Sastry G. Pantula, Graclela Gonzalez-Farias and Wayne A. Fuller
Journal of Business & Economic Statistics
Vol. 12, No. 4 (Oct., 1994), pp. 449-459
Stable URL: http://www.jstor.org/stable/1392213
Page Count: 11
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During the past 15 years, the ordinary least squares estimator and the corresponding pivotal statistic have been widely used for testing the unit-root hypothesis in autoregressive processes. Recently, several new criteria, based on maximum likelihood estimators and weighted symmetric estimators, have been proposed. In this article, we describe several different test criteria. Results from a Monte Carlo study that compares the power of the different 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. As an illustration, the weekly series of one-month treasury-bill rates is analyzed.
Journal of Business & Economic Statistics © 1994 American Statistical Association