Statistical Properties of the Two-Stage Least Squares Estimator Under Cointegration
推导了动态联立模型中变量非平稳且协整时，两阶段最小二乘估计量的极限性质，并讨论了对假设检验的影响。结论是结构方程估计中只需关注识别和估计等经典问题，非平稳性和协整不会影响传统渐近协方差公式和Wald检验统计量的有效性。
We derive the limiting properties of the two-stage least squares estimator of an equation in a dynamic simultaneous model when variables are nonstationary and cointegrated. The implication on hypothesis testing is also discussed. It is shown that in a structural equation approach what one needs to worry about are the classical issues of identification and estimation, not nonstationarity and cointegration. Conventional formulae for computing the asymptotic covariance of the 2SLS estimator and the Wald-type test statistics remain good approximations despite the fact that variables may be integrated.