We describe the main features of empirical likelihood and discuss recent developments,
including Bartlett correction and location adjustment. Algorithms are provided for …

The overall objectives of this review and synthesis are to study the basics of information-
theoretic methods in econometrics, to examine the connecting theme among these methods …

We study statistical inference and distributionally robust solution methods for stochastic
optimization problems, focusing on confidence intervals for optimal values and solutions that …

Weak instruments arise when the instruments in linear instrumental variables (IV) regression
are weakly correlated with the included endogenous variables. In generalized method of …

This revised book provides a thorough explanation of the foundation of robust methods,
incorporating the latest updates on R and S-Plus, robust ANOVA (Analysis of Variance) and …

For some time, so-called empirical likelihoods have been used heuristically for purposes of
nonparametric estimation. Owen showed that empirical likelihood ratio statistics for various …

Empirical likelihood provides inferences whose validity does not depend on specifying a
parametric model for the data. Because it uses a likelihood, the method has certain inherent …

Empirical likelihood is a nonparametric method of inference. It has sampling properties
similar to the bootstrap, but where the bootstrap uses resampling, it profiles a multinomial …

This paper studies the method of empirical likelihood in models with weakly dependent
processes. In such cases, if the likelihood function is formulated as if the data process were …

One-step efficient GMM estimation has been developed in the recent papers of Back and
Brown (1990), Imbens (1993) and Qin and Lawless (1994). These papers emphasized …