Abstract
Empirical likelihood (EL) is a method for estimation and inference without making distributional assumptions. Viewed as a nonparametric maximum likelihood estimation procedure (NPMLE), it approximates the unknown distribution function with a discrete distribution, then applies the ML estimation method. Alternatively, EL can be regarded as a minimum divergence estimation procedure. EL works well for estimating moment condition models, though it applies to other models as well. The large deviation principle (LDP) and other techniques show that EL has many optimality properties.KeywordsBlockwise empirical likelihoodEmpirical likelihoodEmpirical likelihood ratioGeneralized empirical likelihoodGeneralized method of momentsKernel regression techniqueLagrange multiplierLarge deviation principleMaximum likelihoodNonparametric maximum likelihood estimationSemiparametric estimationVector autoregressionsJEL ClassificationsC14
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