 On finite sample properties of alternative estimators of coefficients in a structural equation with many instrumentsT.W. Anderson, Naoto Kunitomo and Yukitoshi Matsushita Journal of Econometrics, 2011, vol. 165, issue 1, 58-69 Abstract: We compare four different estimation methods for the coefficients 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 empirical likelihood (MEL) estimator and the generalized method of moments (GMM) (or the estimating equation) estimator. Tables and figures of the distribution functions of four estimators are given for enough values of the parameters to cover most linear models of interest and we include some heteroscedastic cases and nonlinear cases. We have found that the LIML estimator has good performance in terms of the bounded loss functions and probabilities when the number of instruments is large, that is, the micro-econometric models with “many instruments” in the terminology of recent econometric literature. Keywords: Finite sample properties; Empirical likelihood; GMM; Simultaneous equations with many instruments; Limited information maximum likelihood; Nonlinear LIML (search for similar items in EconPapers) Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:eee:econom:v:165:y:2011:i:1:p:58-69 DOI: 10.1016/j.jeconom.2011.05.006 Access Statistics for this article Journal of Econometrics is currently edited by T. Amemiya, A. R. Gallant, J. F. Geweke, C. Hsiao and P. M. Robinson More articles in Journal of Econometrics from Elsevier |
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