Recent Developments in Empirical Likelihood and Related Methods
综述了基于矩条件模型的估计与推断方法的最新进展，重点介绍广义经验似然类估计量作为广义矩方法的替代，并讨论了计算问题、高阶性质及弱依赖数据的适应性。
This article reviews a number of recent contributions to estimation and inference for models defined by moment condition restrictions. The particular emphasis is on the generalized empirical likelihood class of estimators as an alternative to the generalized method of moments. Estimation methods for parameters defined through moment restrictions and their properties are described with tests of overidentifying moment restrictions and parametric hypotheses. Computational issues are discussed together with some proposals for their amelioration. Higher-order and other properties are also addressed in some detail. Models specified by conditional moment restriction models are considered, and the adaptation of these methods to weakly dependent data is discussed.