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	Provedor de dados AgEcon (2) Autor Lien, Gudbrand D. (2) Richardson, James W. (2) Eltun, Ragnar (1) Flaten, Ola (1) Hardaker, J. Brian (1) Korsaeth, Audun (1) Schumann, Keith D. (1) Mais... Palavra-chave Multivariate kernel estimator (2) Q12 (2) Stochastic simulation (2) C44 (1) C8 (1) Crop Production/Industries (1) Integrated and conventional crop farming (1) Organic (1) Parzen (1) Research Methods/ Statistical Methods (1) Risk and Uncertainty (1) Risk aversion (1) Smoothing (1) Stochastic efficiency with respect to a function (1) Mais... Tipo do documento Conference Paper or Presentation (2) Ano 2006 (1) 2005 (1) País United States (2) Idioma Inglês (2)		Ordenar por:  Relevância Autor Título Ano Registros recuperados: 2 Primeira ... 1 ... Última Simulating Multivariate Distributions with Sparse Data: A Kernal Density Smoothing Procedure AgEcon Lien, Gudbrand D.; Hardaker, J. Brian; Richardson, James W.. Often analysts must conduct risk analysis based on a small number of observations. This paper describes and illustrates the use of a kernel density estimation procedure to smooth out irregularities in such a sparse data set for simulating univariate and multivariate probability distributions. Tipo: Conference Paper or Presentation Palavras-chave: Stochastic simulation; Smoothing; Multivariate kernel estimator; Parzen; Research Methods/ Statistical Methods; Q12; C8. Ano: 2006 URL: http://purl.umn.edu/25449 Comparison of Risk Between Cropping Systems in Eastern Norway AgEcon Lien, Gudbrand D.; Flaten, Ola; Schumann, Keith D.; Richardson, James W.; Korsaeth, Audun; Eltun, Ragnar. The aim of this study was to compare production and policy risk of organic, integrated and conventional cropping systems in Norway. Experimental cropping system data (1991-1999) from eastern Norway were combined with budgeted data. Empirical distributions of total farm income for different cropping systems were estimated with a simulation model that uses a multivariate kernel density function to smooth the limited experimental data. Stochastic efficiency with respect to a function (SERF) was used to rank the cropping systems for farmers with various risk aversion levels. The results show that the organic system had the greatest net farm income variability, but the existing payment system and organic price premiums makes it the most economically viable... Tipo: Conference Paper or Presentation Palavras-chave: Organic; Integrated and conventional crop farming; Stochastic simulation; Multivariate kernel estimator; Risk aversion; Stochastic efficiency with respect to a function; Crop Production/Industries; Risk and Uncertainty; Q12; C44. Ano: 2005 URL: http://purl.umn.edu/24663 Registros recuperados: 2 Primeira ... 1 ... Última

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