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	Provedor de dados AgEcon (23) Autor Judge, George G. (23) Grendar, Marian (7) Mittelhammer, Ronald C. (7) Cho, Wendy K. (3) Miller, Douglas J. (3) Golan, Amos (2) Lee, Joanne (2) Perloff, Jeffrey M. (2) Cardell, N. Scott (1) Marsh, Thomas L. (1) Niven, R.K. (1) Schoenberg, Ron (1) Swanson, E.R. (1) Mais... Palavra-chave Research Methods/ Statistical Methods (18) C10 (4) C24 (4) Empirical likelihood (3) Information theoretic methods (3) Squared error loss (3) Conditional moment equations (2) Cressie-Read statistic (2) Environmental Economics and Policy (2) Estimating equations (2) Finite sample bias and precision (2) Marketing (2) Maximum entropy (2) Quadratic loss (2) Research and Development/Tech Change/Emerging Technologies (2) Semiparametric estimation and inference (2) Statistics (2) Agribusiness (1) Asymptotic and finite sample risk (1) Asymptotic and finite sample risk. (1) Mais... Tipo do documento Working or Discussion Paper (18) Conference Paper or Presentation (2) Book (1) Journal Article (1) Working Paper (1) Ano 2012 (1) 2010 (2) 2009 (2) 2008 (3) 2007 (2) 2006 (1) 2005 (1) 2004 (2) 2003 (4) 2001 (1) 1995 (2) 1977 (1) 1962 (1) Mais... País United States (23) Idioma Inglês (23)		Registro completo Provedor de dados:  AgEcon País:  United States Título:  A Minimum Power Divergence Class of CDFs and Estimators for Binary Choice Models Autores:  Mittelhammer, Ronald C. Judge, George G. Data:  2008-07-08 Ano:  2008 Palavras-chave:  Binary choice models and estimators Conditional moment equations Squared error loss Cressie-Read statistic Information theoretic methods Minimum power divergence Research Methods/ Statistical Methods Resumo:  The Cressie-Read (CR) family of power divergence measures is used to identify a new class of statistical models and estimators for competing explanations of the data in binary choice models. A large flexible class of cumulative distribution functions and associated probability density functions emerge that subsumes the conventional logit model, and forms the basis for a large set of estimation alternatives to traditional logit and probit methods. Asymptotic properties of estimators are identified, and sampling experiments are used to provide a basis for gauging the finite sample performance of the estimators in this new class of statistical models. Tipo:  Working or Discussion Paper Idioma:  Inglês Identificador:  http://purl.umn.edu/37759 Relação:  University of California, Berkeley>Department of Agricultural and Resource Economics>CUDARE Working Papers CUDARE Working Papers 1059 Formato:  31 Fechar

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