Identification without assuming mean stationarity: quasi–maximum likelihood estimation of dynamic panel models with endogenous regressors
无需均值平稳假设的识别:含内生解释变量动态面板模型的拟极大似然估计
Summary Linear generalised method of moments (GMM) estimators for dynamic panel models with predetermined or endogenous regressors suffer from a weak instruments problem when the data are highly persistent. In this paper, we propose new random- and fixed-effects limited-information quasi–maximum likelihood estimators (LIQMLEs) for such models. We also discuss LIQMLEs for models that contain time-varying individual effects. Unlike system GMM estimators, the LIQMLEs do not…