IV‐BASED COINTEGRATION TESTING IN DEPENDENT PANELS WITH TIME‐VARYING VARIANCE
针对创新方差时变且面板单元间存在依赖的情况，将非线性工具变量法推广到误差修正框架，提出稳健的协整检验，证明检验统计量渐近正态且单元间渐近独立，有限样本表现良好。
The distributions of cointegration tests are affected when the innovation variance varies over time. In panels, one must also pay attention to dependence among units. To obtain a panel cointegration test robust to both heteroskedasticity and dependence, we adapt the nonlinear instruments method proposed for the Dickey–Fuller test by Chang (2002, J Econometrics 110, 261–292) to an error‐correction framework. We show that IV‐based testing of the no error‐correction null in individual equations yields standard normal test statistics when computed with heteroskedasticity‐robust standard errors. The result holds under endogenous regressors, irrespective of the number of integrated covariates and for any variance profile. A non‐cointegration test combining single‐equation tests retains these nice properties. In panels of fixed cross‐sectional dimension, such test statistics from individual units are shown to be asymptotically independent even under dependence, leading to panel tests robust to dependence and heteroskedasticity. The tests perform well in finite panels.