Testing for Autocorrelation in Dynamic Random Effects Models
针对面板数据的动态随机效应模型，在三阶段最小二乘估计后开发协方差约束检验，推导非正态下协方差矩阵估计的渐近分布，并展示如何通过广义线性回归计算最小卡方检验，同时利用GLS估计实现渐近效率。
This article develops, tests of covariance restrictions after estimating by three-stage least squares a dynamic random effects model from panel data. The asymptotic distribution of covariance matrix estimates under non-normality is obtained. It is shown how minimum chi-square tests for interesting covariance restrictions can be calculated from a generalised linear regression involving the sample autocovariances and dummy variables. Asymptotic efficiency exploiting covariance restrictions can also be attained using a GLS estimator.