Generalized Method of Moments and Empirical Likelihood

@article{imbens:2002, abstract = {Generalized method of moments (GMM) estimation has become an important unifying framework for inference in econometrics in the last 20 years. It can be thought of as encompassing almost all of the common estimation methods, such as maximum likelihood, ordinary least squares, instrumental variables, and two-stage least squares, and nowadays is an important part of all advanced econometrics textbooks. The GMM approach links nicely to economic theory where orthogonality conditions that can serve as such moment functions often arise from optimizing behavior of agents. Much work has been done on these methods since the seminal article by Hansen, and much remains in progress. This article discusses some of the developments since Hansen\&\#039;s original work. In particular, it focuses on some of the recent work on empirical likelihood\&\#150;type estimators, which circumvent the need for a first step in which the optimal weight matrix is estimated and have attractive information theoretic interpretations.}, author = {Imbens, G. W. }, citeulike-article-id = {2968121}, issn = {0735-0015}, journal = {Journal of Business \&\#38; Economic Statistics}, keywords = {asymptotics, econometrics, econometric\_theory, empirical\_likelihood, gmm}, pages = {493--506}, posted-at = {2008-07-07 02:08:56}, priority = {2}, publisher = {American Statistical Association}, title = {Generalized Method of Moments and Empirical Likelihood}, url = {http://www.ingentaconnect.com/content/asa/jbes/2002/00000020/00000004/art00008} }

TY - JOUR ID - imbens:2002 L3 - citeulike-article-id:2968121 TI - Generalized Method of Moments and Empirical Likelihood JF - Journal of Business & Economic Statistics SP - 493 EP - 506 PB - American Statistical Association SN - 0735-0015 N2 - Generalized method of moments (GMM) estimation has become an important unifying framework for inference in econometrics in the last 20 years. It can be thought of as encompassing almost all of the common estimation methods, such as maximum likelihood, ordinary least squares, instrumental variables, and two-stage least squares, and nowadays is an important part of all advanced econometrics textbooks. The GMM approach links nicely to economic theory where orthogonality conditions that can serve as such moment functions often arise from optimizing behavior of agents. Much work has been done on these methods since the seminal article by Hansen, and much remains in progress. This article discusses some of the developments since Hansen's original work. In particular, it focuses on some of the recent work on empirical likelihood–type estimators, which circumvent the need for a first step in which the optimal weight matrix is estimated and have attractive information theoretic interpretations. KW - asymptotics KW - econometrics KW - econometric_theory KW - empirical_likelihood KW - gmm AU - Imbens, GW UR - http://www.ingentaconnect.com/content/asa/jbes/2002/00000020/00000004/art00008 ER -