Publikation: Finite Sample Properties of One-step, Two-step and Bootstrap Empirical Likelihood Approaches to Efficient GMM Estimation
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2000
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Inkmann, Joachim
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This paper compares conventional GMM estimators to empirical likelihood based GMM estimators which employ a semiparametric efficient estimate of the unknown distribution function of the data. One-step, two-step and bootstrap empirical likelihood and conventional GMM estimators are considered which are efficient for a given set of moment conditions. The estimators are subject to a Monte Carlo investigation using a specification which exploits sequeantial conditional moment restrictions for binary panel data with multiplicative latent effects. Among other findings the experiments show that the one-step and two-step estimators yield coverage rates of confidence intervals below their nominal coverage probabilities. The bootstrap methods improve upon this result.
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330 Wirtschaft
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GMM, empirical likelihood, bootstrap, sequential moment restrictions
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INKMANN, Joachim, 2000. Finite Sample Properties of One-step, Two-step and Bootstrap Empirical Likelihood Approaches to Efficient GMM EstimationBibTex
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year={2000},
series={CoFE-Diskussionspapiere / Zentrum für Finanzen und Ökonometrie},
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number={2000/03},
author={Inkmann, Joachim}
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