Testing for Serial Correlation by Variable Addition in Dynamic Models Estimated by Instrumental Variables
提出在工具变量估计的动态模型中，通过将初始估计的滞后残差加入回归变量和工具变量集来检验序列相关，蒙特卡洛证据表明该方法能改善有限样本表现。
Instrumental variable tests for serial correlation can be carried out by adding lagged residuals from initial estimation to the regressors of the model under scrutiny and then checking their joint significance. It is shown that asymptotically valid tests are obtained if the lagged residuals are also added to the initial instrument set. Monte Carlo evidence suggests that useful improvements in finite sample behavior under null and alternative hypotheses can be produced when the instrument set is extended to include the relevant lagged residuals. Links with other tests are discussed and a modification allowing for conditional heteroskedasticity is described. Copyright 1994 by MIT Press.