Generalized Method of Moments, Efficient Bootstrapping, and Improved Inference
提出一种基于经验似然分布重抽样的自助法用于广义矩方法，能在大样本下提升效率并改进推断，适合计量经济学研究者参考。
AbstractGeneralized method of moments (GMM) has been an important innovation in econometrics. Its usefulness has motivated a search for good inference procedures based on GMM. This article presents a novel method of bootstrapping for GMM based on resampling from the empirical likelihood distribution that imposes the moment restrictions. We show that this approach yields a large-sample improvement and is efficient, and give examples. We also discuss the development of GMM and other recent work on improved inference.KEY WORDS: BootstrappingEmpirical likelihoodPanel data