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	Provedor de dados AgEcon (5) Autor Brorsen, B. Wade (1) Heckelei, Thomas (1) Livanis, Grigorios T. (1) Lokshin, Michael (1) Moss, Charles B. (1) Salois, Matthew J. (1) Temel, Tugrul T. (1) Townsend, John P. (1) Wieck, Christine (1) Mais... Palavra-chave Nonparametric regression (5) C14 (2) C15 (2) Q12 (2) Research Methods/ Statistical Methods (2) C12 (1) C16 (1) C33 (1) C61 (1) Dairy production (1) Difference-based estimator (1) Forward contracting (1) Gaussian kernel (1) Hypothesis test (1) Livestock Production/Industries (1) Marginal costs (1) Marketing (1) Nonparametric derivatives (1) Omitted variables (1) Optimization techniques (1) Mais... Tipo do documento Conference Paper or Presentation (3) Journal Article (2) Ano 2009 (1) 2007 (1) 2006 (1) 2001 (1) 2000 (1) País United States (5) Idioma Inglês (5)		Ordenar por:  Relevância Autor Título Ano Registros recuperados: 5 Primeira ... 1 ... Última Parametric or Nonparametric Approaches to the Estimation of Marginal Cost in Dairy Production? A Comparison of Estimation Results AgEcon Wieck, Christine; Heckelei, Thomas. This paper compares various nonparametric models for the estimation of farm specific marginal costs function in the dairy sector. Specifically, locally weighted regression approaches using theory-consistent cost function frameworks as polynomials in the nonparametric approach are applied. A comparison of average marginal cost levels as well as marginal cost distributions across farms illustrates the different approaches. Tipo: Conference Paper or Presentation Palavras-chave: Dairy production; Marginal costs; Nonparametric regression; Livestock Production/Industries; C33; Q12; Q18. Ano: 2007 URL: http://purl.umn.edu/9829 COST OF FORWARD CONTRACTING HARD RED WINTER WHEAT AgEcon Townsend, John P.; Brorsen, B. Wade. Two methods were used to estimate the cost of forward contracting hard red winter wheat. One hundred days before delivery, the estimated cost of forward contracting ranged from six cents/bu. To eight cents/bu. Thus, further evidence is provided that the cost of forward contracting grain is not zero. Tipo: Journal Article Palavras-chave: Forward contracting; Nonparametric regression; Wheat; Marketing. Ano: 2000 URL: http://purl.umn.edu/15390 Difference-based semiparametric estimation of partial linear regression models AgEcon Lokshin, Michael. This article describes the plreg command, which implements the difference-based algorithm for fitting partial linear regression models. Tipo: Journal Article Palavras-chave: Plreg; Nonparametric regression; Difference-based estimator; Partial linear regression; Research Methods/ Statistical Methods. Ano: 2006 URL: http://purl.umn.edu/117587 A Nonparametric Kernel Representation of the Agricultural Production Function: Implications for Economic Measures of Technology AgEcon Livanis, Grigorios T.; Salois, Matthew J.; Moss, Charles B.. The issue of production function estimation has received recent attention, particularly in agricultural economics with the advent of precision farming. Yet, the evidence to date is far from unanimous on the proper form of the production function. This paper reexamines the use of the primal production function framework using nonparametric regression techniques. Specifically, the paper demonstrates how a nonparametric regression based on a kernel density estimator can be used to estimate a production function using data on corn production from Illinois and Indiana. Nonparametric results are compared to common parametric specifications using the Nadaraya-Watson kernel regression estimator. The parametric and nonparametric forms are also compared in terms of... Tipo: Conference Paper or Presentation Palavras-chave: Nonparametric regression; Nonparametric derivatives; Gaussian kernel; Optimization techniques; Production function; Production Economics; C14; C15; C16; C61; Q12. Ano: 2009 URL: http://purl.umn.edu/51063 A NONPARAMETRIC HYPOTHESIS TEST VIA THE BOOTSTRAP RESAMPLING AgEcon Temel, Tugrul T.. This paper adapts an already existing nonparametric hypothesis test to the bootstrap framework. The test utilizes the nonparametric kernel regression method to estimate a measure of distance between the models stated under the null hypothesis. The bootstraped version of the test allows to approximate errors involved in the asymptotic hypothesis test. Tipo: Conference Paper or Presentation Palavras-chave: Hypothesis test; The bootstrap; Nonparametric regression; Omitted variables; Research Methods/ Statistical Methods; C12; C14; C15. Ano: 2001 URL: http://purl.umn.edu/20600 Registros recuperados: 5 Primeira ... 1 ... Última

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