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	Provedor de dados AgEcon (29) Autor Jayne, Thomas S. (3) Baum, Christopher F. (2) Chen, Min (2) Fisher, Monica G. (2) Koo, Won W. (2) Kumbhakar, Subal C. (2) Mishra, Ashok K. (2) Poi, Brian P. (2) Ricker-Gilbert, Jacob (2) Schaffer, Mark E. (2) Stillman, Steven (2) Ainembabazi, John Herbert (1) Angelsen, Arild (1) Bailly, Denis (1) Boncoeur, Jean (1) Brown, A. Blake (1) Chapoto, Antony (1) Chavas, Jean-Paul (1) Cheney, Laura Martin (1) Crepinsek, Mary Kay (1) Mais... Palavra-chave Endogeneity (29) Q12 (6) Instrumental variables (5) Production Economics (5) Research Methods/ Statistical Methods (5) Consumer/Household Economics (4) Farm Management (4) Food Security and Poverty (4) Agribusiness (3) C24 (3) Crop Production/Industries (3) Demand and Price Analysis (3) Food Consumption/Nutrition/Food Safety (3) Panel data (3) Q18 (3) Agricultural and Food Policy (2) C10 (2) C34 (2) Environmental Economics and Policy (2) Facilities (2) Mais... Tipo do documento Conference Paper or Presentation (12) Journal Article (6) Working or Discussion Paper (6) Presentation (2) Article (1) Report (1) Thesis or Dissertation (1) Mais... Ano 2012 (2) 2011 (4) 2010 (3) 2009 (5) 2007 (3) 2006 (1) 2005 (3) 2004 (3) 2002 (3) 2001 (1) 2000 (1) Mais... País United States (29) Idioma Inglês (29)		Registro completo Provedor de dados:  AgEcon País:  United States Título:  Estimating the Link Function in Multinomial Response Models under Endogeneity and Quadratic Loss Autores:  Judge, George G. Mittelhammer, Ronald C. Data:  2006-02-06 Ano:  2004 Palavras-chave:  Multinomial Process Endogeneity Empirical likelihood procedures Quadratic loss Semiparametric estimation and inference Data dependent shrinkage Asymptotic and finite sample risk Research Methods/ Statistical Methods C10 C24 Resumo:  This paper considers estimation and inference for the multinomial response model in the case where endogenous variables are arguments of the unknown link function. Semiparametric estimators are proposed that avoid the parametric assumptions underlying the likelihood approach as well as the loss of precision when using nonparametric estimation. A data based shrinkage estimator that seeks an optimal combination of estimators and results in superior risk performance under quadratic loss is also developed. Tipo:  Working or Discussion Paper Idioma:  Inglês Identificador:  19783 http://purl.umn.edu/25095 Editor:  AgEcon Search Relação:  University of California, Berkeley>Department of Agricultural and Resource Economics>CUDARE Working Papers CUDARE Working Paper 970 Formato:  26 application/pdf Fechar

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