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This paper studies moderate deviation behaviors of the generalized method of moments and generalized empirical likelihood estimators for generalized estimating equations, where the number of equations can be larger than the number of unknown parameters. We consider two cases for the data...
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This paper studies large deviation properties of the generalized method of moments and generalized empirical likelihood estimators for moment restriction models. We consider two cases for the data generating probability measure: the model assumption and local deviations from the model...
Persistent link: https://www.econbiz.de/10013129886
A Simulated Maximum Likelihood (SML) estimator for the random coefficient logit model using aggregate data is found to be more efficient than the widely used Generalized Method of Moments estimator (GMM) of Berry-Levinsohn-Pakes (1995). In particular, the SML estimator is better than the GMM...
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