Near Observational Equivalence and Theoretical size Problems with Unit Root Tests
指出在非常一般的模型设定下，单位根检验的实际检验水平会趋近于1而非名义水平，并提出了通过缩小模型空间来解决渐近检验水平问题的方法，为改进有限样本检验表现提供了建议。
Said and Dickey (1984, Biometrika 71, 599–608) and Phillips and Perron (1988, Biometrika 75, 335–346) have derived unit root tests that have asymptotic distributions free of nuisance parameters under very general maintained models. Under models as general as those assumed by these authors, the size of the unit root test procedures will converge to one, not the size under the asymptotic distribution. Solving this problem requires restricting attention to a model that is small, in a topological sense, relative to the original. Sufficient conditions for solving the asymptotic size problem yield some suggestions for improving finite-sample size performance of standard tests.