On the Rigour of Some Misspecification Tests for Modelling Dynamic Relationships
通过模拟研究发现，在含滞后因变量的回归模型中，多种序列相关和预测失效检验在小样本下存在缺陷，只有特定自由度调整才能改善小样本表现。
For regression models alternative asymptotically equivalent misspecification tests may lead to conflicting inference in small samples. Effective misspecification tests should have correct significance levels irrespective of the true parameters and any redundant regressors in the model, and reasonable power against a wide class of alternative specifications. A simulation study of various tests for serial correlation and predictive failure in models with lagged dependent variables finds many tests defective in small samples. Only particular degrees of freedom adjustments to the test statistics yield improved small sample behaviour.