Home Itens selecionados Provedores de dados OAI Créditos Sobre Ajuda

			Busca avançada
	Provedor de dados AgEcon (4) Autor Cardell, N. Scott (4) Mittelhammer, Ronald C. (4) Fahs, Rafic (2) Judge, George G. (1) Marsh, Thomas L. (1) Miller, Douglas J. (1) Mais... Palavra-chave Demand and Price Analysis (2) Research Methods/ Statistical Methods (2) C10 (1) C2 (1) Conditional moment equations (1) Cressie-Read statistic (1) Finite sample bias and precision (1) Information theoretic methods (1) Nonparametric binary response models and estimators (1) Response variables (1) Squared error loss (1) Mais... Tipo do documento Conference Paper or Presentation (3) Working or Discussion Paper (1) Ano 2005 (1) 2001 (2) 1998 (1) País United States (4) Idioma Inglês (4)		Ordenar por:  Relevância Autor Título Ano Registros recuperados: 4 Primeira ... 1 ... Última Semiparametric Estimation and Inference in a System of Censored Demand Equations AgEcon Fahs, Rafic; Cardell, N. Scott; Mittelhammer, Ronald C.. The purpose of this paper is to utilize the generalized method of moments (GMM) approach for estimating a system of multivariate Tobit equations and propose a practical consistent estimator of model parameters. The GMM approach is based on a common set of general marginal and bivariate moment relations that hold between explanatory variables and model noise. Tipo: Conference Paper or Presentation Palavras-chave: Demand and Price Analysis. Ano: 2001 URL: http://purl.umn.edu/20482 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 Semiparametric Estimation and Inference in Multinomial Choice Models AgEcon Fahs, Rafic; Cardell, N. Scott; Mittelhammer, Ronald C.. The purpose of this paper is to incorporate semiparametric alternatives to maximum likelihood estimation and inference in the context of unordered multinomial response data when in practice there is often insufficient information to specify the parametric form of the function linking the observables to the unknown probabilities. We specify the function linking the observables to the unknown probabilities using a very general flexible class of functions belonging to the Pearson system of cumulative distribution equations. In this setting we consider the observations as arising from a multinomial distribution characterized by one of the CDFs in the Pearson system. Given this situation, it is possible to utilize the concept of unbiased estimating functions... Tipo: Conference Paper or Presentation Palavras-chave: Demand and Price Analysis. Ano: 2001 URL: http://purl.umn.edu/20742 A STRUCTURAL-EQUATION GME ESTIMATOR AgEcon Marsh, Thomas L.; Mittelhammer, Ronald C.; Cardell, N. Scott. A generalized maximum entropy estimator is developed for the linear simultaneous equations systems model. We provide results on large and small sample properties of the estimator. Empirical results illustrate efficiency advantages of the generalized maximum entropy estimator proposed in this study over traditional estimators (e.g., 2SLS and 3SLS). Tipo: Conference Paper or Presentation Palavras-chave: Research Methods/ Statistical Methods. Ano: 1998 URL: http://purl.umn.edu/20890 Registros recuperados: 4 Primeira ... 1 ... Última

Empresa Brasileira de Pesquisa Agropecuária - Embrapa Todos os direitos reservados, conforme Lei n° 9.610 Política de Privacidade Área restrita		Embrapa Parque Estação Biológica - PqEB s/n° Brasília, DF - Brasil - CEP 70770-901 Fone: (61) 3448-4433 - Fax: (61) 3448-4890 / 3448-4891 SAC: https://www.embrapa.br/fale-conosco