M-Estimator And Maximum Likelihood Estimator (MLE)

Myoung-jae Lee

Chapter Chapter 3 in Micro-Econometrics, 2008, pp 91-132 from Springer

Abstract: Abstract Least square estimator (LSE) minimizes an objective function, and the estimator itself is obtained in a closed form. There are many other estimators maximizing/minimizing some objective functions, but most of them are not written in closed forms; those estimators, called “Mestimators”, are reviewed here. Typically, the first-order conditions of M-estimators are moment conditions, and this links M-estimator to MOM estimator/test.

Keywords: Maximum Likelihood Estimator; Asymptotic Distribution; Nuisance Parameter; Asymptotic Variance; Little Square Estimator (search for similar items in EconPapers)
Date: 2008
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-0-387-68841-1_3

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DOI: 10.1007/b60971_3

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