A Comparison of Unit-Root Test Criteria
比较了多种单位根检验准则，蒙特卡洛研究表明基于加权对称估计量和无条件最大似然估计量的新检验比传统OLS检验更有效。
During the past fifteen 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 criteriia, based on the 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 indicates 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, we analyze the quarterly change in busine;ss investories.