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On the asymptotic optimality of the LIML estimator with possibly many instruments
Authors:TW Anderson  Naoto Kunitomo  Yukitoshi Matsushita
Institution:1. Department of Statistics, Stanford University, United States;2. Department of Economics, Stanford University, United States;3. Graduate School of Economics, University of Tokyo, Bunkyo-ku, Hongo 7-3-1 Tokyo, Japan
Abstract:We consider the estimation of the coefficients of a linear structural equation in a simultaneous equation system when there are many instrumental variables. We derive some asymptotic properties of the limited information maximum likelihood (LIML) estimator when the number of instruments is large; some of these results are new as well as old, and we relate them to results in some recent studies. We have found that the variance of the limiting distribution of the LIML estimator and its modifications often attain the asymptotic lower bound when the number of instruments is large and the disturbance terms are not necessarily normally distributed, that is, for the micro-econometric models of some cases recently called many instruments and many weak instruments.
Keywords:C13  C30
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