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	Provedor de dados AgEcon (2) Autor Judge, George G. (2) Mittelhammer, Ronald C. (2) Cardell, N. Scott (1) Miller, Douglas J. (1) Schoenberg, Ron (1) Palavra-chave C10 (2) Finite sample bias and precision (2) Research Methods/ Statistical Methods (2) Squared error loss (2) C2 (1) C24 (1) Conditional estimating equations (1) Conditional moment equations (1) Cressie-Read statistic (1) Empirical exponential likelihood (1) Empirical likelihood (1) Information theoretic methods (1) Instrumental conditioning variables (1) Nonparametric binary response models and estimators (1) Response variables (1) Semiparametric models (1) Unbiased moment based estimation and inference (1) Mais... Tipo do documento Working or Discussion Paper (2) Ano 2005 (1) 2003 (1) País United States (2) Idioma Inglês (2)		Ordenar por:  Relevância Autor Título Ano Registros recuperados: 2 Primeira ... 1 ... Última Empirical Evidence Concerning the Finite Sample Performance of EL-Type Structural Equation Estimation and Inference Methods AgEcon Mittelhammer, Ronald C.; Judge, George G.; Schoenberg, Ron. This paper presents empirical evidence concerning the finite sample performance of conventional and generalized empirical likelihood-type estimators that utilize instruments in the context of linear structural models characterized by endogenous explanatory variables. There are suggestions in the literature that traditional and non-traditional asymptotically efficient estimators based on moment equations may, for the relatively small sample sizes usually encountered in econometric practice, have relatively large biases and/or variances and provide an inadequate basis for estimation and inference. Given this uncertainty we use a range of data sampling processes and Monte Carlo sampling procedures to accumulate finite sample empirical evidence concerning... Tipo: Working or Discussion Paper Palavras-chave: Unbiased moment based estimation and inference; Empirical likelihood; Empirical exponential likelihood; Semiparametric models; Conditional estimating equations; Finite sample bias and precision; Squared error loss; Instrumental conditioning variables; Research Methods/ Statistical Methods; C10; C24. Ano: 2003 URL: http://purl.umn.edu/25090 Minimum Divergence Moment Based Binary Response Models: Estimation and Inference AgEcon Mittelhammer, Ronald C.; Judge, George G.; Miller, Douglas J.; Cardell, N. Scott. This paper introduces a new class of estimators based on minimization of the Cressie-Read (CR) power divergence measure for binary choice models, where neither a parameterized distribution nor a parameterization of the mean is specified explicitly in the statistical model. By incorporating sample information in the form of conditional moment conditions and estimating choice probabilities by optimizing a member of the set of divergence measures in the CR family, a new class of nonparametric estimators evolves that requires less a priori model structure than conventional parametric estimators such as probit or logit. Asymptotic properties are derived under general regularity conditions and finite sampling properties are illustrated by Monte Carlo sampling... Tipo: Working or Discussion Paper Palavras-chave: Nonparametric binary response models and estimators; Conditional moment equations; Finite sample bias and precision; Squared error loss; Response variables; Cressie-Read statistic; Information theoretic methods; Research Methods/ Statistical Methods; C10; C2. Ano: 2005 URL: http://purl.umn.edu/25020 Registros recuperados: 2 Primeira ... 1 ... Última

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