Showing papers by "T. W. Anderson published in 2006"
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TL;DR: In this article, the authors compared four different estimation methods for a coefficient of a linear structural equation with instrumental variables, and proved several theorems on the asymptotic optimality of the LIML estimator when the number of instruments is large.
Abstract: We compare four dffierent estimation methods for a coefficient of a linear structural equation with instrumental variables. As the classical methods we consider the limited information maximum likelihood (LIML) estimator and the two-stage least squares (TSLS) estimator, and as the semi-parametric estimation methods we consider the maximum emirical likelihood (MEL) estimator and the generalized method of moments (GMM) (or the estimating equation) estimator. We prove several theorems on the asymptotic optimality of the LIML estimator when the number of instruments is large, which are new as well as old, and we relate them to the results in some recent studies. Tables and figures of the distribution functions of four estimators are given for enough values of the parameters to cover most of interest. We have found that the LIML estimator has good performance when the number of instruments is large, that is, the micro-econometric models with many instruments in the terminology of recent econometric literature.
12 citations
TL;DR: In this article, it was shown that the maximum likelihood estimator of the restrictions can be approximated by a function of the effect matrix alone, which is a generalization of the limited information maximum likelihood and two-stage least squares estimators.
4 citations