Empirical Likelihood Methods in Econometrics: Theory and Practice

Yuichi Kitamura ()
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Yuichi Kitamura: Cowles Foundation, Yale University, https://economics.yale.edu/people/faculty/yuichi-kitamura

No 1569, Cowles Foundation Discussion Papers from Cowles Foundation for Research in Economics, Yale University

Abstract: Recent developments in empirical likelihood (EL) methods are reviewed. First, to put the method in perspective, two interpretations of empirical likelihood are presented, one as a nonparametric maximum likelihood estimation method (NPMLE) and the other as a generalized minimum contrast estimator (GMC). The latter interpretation provides a clear connection between EL, GMM, GEL and other related estimators. Second, EL is shown to have various advantages over other methods. The theory of large deviations demonstrates that EL emerges naturally in achieving asymptotic optimality both for estimation and testing. Interestingly, higher order asymptotic analysis also suggests that EL is generally a preferred method. Third, extensions of EL are discussed in various settings, including estimation of conditional moment restriction models, nonparametric specification testing and time series models. Finally, practical issues in applying EL to real data, such as computational algorithms for EL, are discussed. Numerical examples to illustrate the efficacy of the method are presented.

Keywords: Convex analysis; Empirical distribution; GNP-optimality; Large deviation principle; Moment restriction models; Nonparametric test; NPMLE; Semiparametric efficiency; Weak dependence (search for similar items in EconPapers)
JEL-codes: C14 (search for similar items in EconPapers)
Pages: 66 pages
Date: 2006-06
New Economics Papers: this item is included in nep-ecm
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (24)

Published in Richard Blundell, W.K. Newey, and T. Persson, eds., Advances in Economics and Econometrics: Theory and Applications, Ninth World Congress, vol. 3, Cambridge University Press, 2007, Ch. 7

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