Sabiia Seb
PortuguêsEspañolEnglish
Embrapa
        Busca avançada

Botão Atualizar


Botão Atualizar

Ordenar por: RelevânciaAutorTítuloAnoImprime registros no formato resumido
Registros recuperados: 11
Primeira ... 1 ... Última
Imagem não selecionada

Imprime registro no formato completo
Correction of Measurement Error in Monthly USDA Pig Crop: Generating Alternative Data Series AgEcon
Kim, In Seck; Plain, Ronald L.; Bullock, J. Bruce; Jei, Sang Young.
The imputed pig death loss contained in the reported monthly U.S. Department of Agriculture (USDA) pig crop data over the December 1995–June 2006 period ranged from 24.93% to 12.75%. Clearly, there are substantial measurement errors in the USDA monthly pig crop data. In this paper, we present alternative monthly U.S. pig crop data using the biological production process, which is compatible with prior knowledge of the U.S. hog industry. Alternative pig crop data are applied to a slaughter hog model and tested comparatively to USDA pig crop. Test results reject the validity of USDA pig crop data in favor of the alternative data.
Tipo: Journal Article Palavras-chave: Biological production process; Measurement error; Monthly USDA pig crop data; Pig death loss; Agribusiness; Farm Management; Livestock Production/Industries; Q11; Q13; C12.
Ano: 2008 URL: http://purl.umn.edu/47208
Imagem não selecionada

Imprime registro no formato completo
Does Duality Theory Hold in Practice? A Monte Carlo Analysis for U.S. Agriculture AgEcon
Rosas, Francisco; Lence, Sergio H..
The Neoclassical theory of production establishes a dual relationship between the profit value function of a competitive firm and its underlying production technology. This relationship, usually referred to as the duality theory, has been widely used in empirical work to estimate production parameters without the requirement of explicitly specifying the technology. We analyze the ability of this approach to recover the underlying production parameters and its effects on estimated elasticities and scale economies measurements, when data available for estimation features typical realistic problems. We design alternative scenarios and compute the data generating process by Monte Carlo simulations, so as to know the true technology parameters as well as to...
Tipo: Conference Paper or Presentation Palavras-chave: Duality theory; Firm’s heterogeneity; Measurement error; Data aggregation; Omitted variables; Endogeneity; Uncertainty; Monte Carlo simulations.; Crop Production/Industries; Production Economics; Risk and Uncertainty; Q12; D22; D81.
Ano: 2011 URL: http://purl.umn.edu/103911
Imagem não selecionada

Imprime registro no formato completo
Does Measurement Error Explain a Paradox About Household Size and Food Demand? Evidence from Variation in Household Survey Methods AgEcon
Gibson, John.
Several recent papers report a puzzling pattern of food demand falling as household size rises at constant per capita expenditure, especially in poorer countries. This pattern is contrary to a widely used model of scale economics. This paper exploits within-country differences in household survey methods and interviewer practices to provide a measurement error interpretation of this puzzle. A comparison of household surveys in Cambodia and Indonesia with the results from Monte Carlo experiments suggest that food expenditure estimates from shorter, less detailed recall surveys have measurement errors that are correlated with household size. These correlated measurement errors contribute to the negative effect of household size on food demand and cause...
Tipo: Conference Paper or Presentation Palavras-chave: Food demand; Economies of scale; Household surveys; Measurement error; Consumer/Household Economics; Demand and Price Analysis.
Ano: 2003 URL: http://purl.umn.edu/22198
Imagem não selecionada

Imprime registro no formato completo
Farm Level Nonparametric Analysis of Profit Maximization Behavior with Measurement Error AgEcon
Zereyesus, Yacob Abrehe; Featherstone, Allen M.; Langemeier, Michael R..
This paper tests the farm level profit maximization hypothesis using a nonparametric production analysis approach allowing for measurement error in the input and output variables. All farms violated Varian’s deterministic Weak Axiom of Profit Maximization (WAPM). The magnitude of minimum critical standard errors required for consistency with profit maximization, convex technology production was smaller after allowing technological change during the sample period. Results indicate strong support for the presence of technological change during the sample period.
Tipo: Conference Paper or Presentation Palavras-chave: Nonparametric analysis; Profit maximization; Measurement error; Technological change; Production Economics; D24.
Ano: 2009 URL: http://purl.umn.edu/46829
Imagem não selecionada

Imprime registro no formato completo
Instrumental variables, bootstrapping, and generalized linear models AgEcon
Hardin, James W.; Schmiediche, Henrik; Carroll, Raymond J..
This paper discusses and illustrates the qvf command for fitting generalized linear models. The differences between this new command and Stata’s glm command are highlighted. One of the most notable features of the qvf command is its ability to include instrumental variables. This functionality was added specifically to address measurement error but may be utilized by the user for other purposes. The qvf command was developed in the C-language using Stata’s new plugin features and executes much faster than the glm ado-file.
Tipo: Journal Article Palavras-chave: Measurement error; Instrumental variables; Murphy–Topel; Bootstrap; Generalized linear models; Research Methods/ Statistical Methods.
Ano: 2003 URL: http://purl.umn.edu/116178
Imagem não selecionada

Imprime registro no formato completo
Measurement error, GLMs, and notational conventions AgEcon
Hardin, James W.; Carroll, Raymond J..
This paper introduces additive measurement error in a generalized linear-model context. We discuss the types of measurement error along with their effects on fitted models. In addition, we present the notational conventions to be used in this and the accompanying papers.
Tipo: Journal Article Palavras-chave: Generalized linear models; Transportability; Measurement error; Research Methods/ Statistical Methods.
Ano: 2003 URL: http://purl.umn.edu/116175
Imagem não selecionada

Imprime registro no formato completo
Quantifying Obesity in Economic Research: How Misleading is the Body Mass Index? AgEcon
Parks, Joanna C.; Smith, Aaron D.; Alston, Julian M..
Replaced with revised version of paper 07/19/10.
Tipo: Conference Paper or Presentation Palavras-chave: Obesity; Percent body fat (PBF); Body mass index (BMI); Economic costs; Measurement error; Health Economics and Policy; Research and Development/Tech Change/Emerging Technologies; C52; I10.
Ano: 2010 URL: http://purl.umn.edu/61841
Imagem não selecionada

Imprime registro no formato completo
The Impact of Measurement Error on Estimates of the Price Reaction to USDA Crop Reports AgEcon
Aulerich, Nicole M.; Irwin, Scott H.; Nelson, Carl H..
This paper investigates the impact of USDA crop production reports in corn and soybean futures markets. The analysis is based on all corn and soybean production reports released over 1970-2006. The empirical analysis compares the typical OLS event study approach to the new Identification by Censoring (ITC) technique. Corn and soybean production reports are analyzed both separately and together for impact in corn and soybean futures prices. ITC proves to be the more useful method because it avoids the pitfalls of errors in variables that cause downward bias in OLS coefficients. Price reaction coefficients estimated via ITC are one to four times larger than OLS estimates for a one price and one event analysis. In the two price, two event case, ITC estimates...
Tipo: Conference Paper or Presentation Palavras-chave: Event study; USDA Crop Production reports; Measurement error; Identification Through Censoring.
Ano: 2007 URL: http://purl.umn.edu/37579
Imagem não selecionada

Imprime registro no formato completo
The regression-calibration method for fitting generalized linear models with additive measurement error AgEcon
Hardin, James W.; Schmiediche, Henrik; Carroll, Raymond J..
This paper discusses and illustrates the method of regression calibration. This is a straightforward technique for fitting models with additive measurement error. We present this discussion in terms of generalized linear models (GLMs) following the notation defined in Hardin and Carroll (2003). Discussion will include specified measurement error, measurement error estimated by replicate error-prone proxies, and measurement error estimated by instrumental variables. The discussion focuses on software developed as part of a small business innovation research (SBIR) grant from the National Institutes of Health (NIH).
Tipo: Journal Article Palavras-chave: Regression calibration; Measurement error; Instrumental variables; Replicate measures; Generalized linear models; Research Methods/ Statistical Methods.
Ano: 2003 URL: http://purl.umn.edu/116180
Imagem não selecionada

Imprime registro no formato completo
The simulation extrapolation method for fitting generalized linear models with additive measurement error AgEcon
Hardin, James W.; Schmiediche, Henrik; Carroll, Raymond J..
We discuss and illustrate the method of simulation extrapolation for fitting models with additive measurement error. We present this discussion in terms of generalized linear models (GLMs) following the notation defined in Hardin and Carroll (2003). As in Hardin, Schmiediche, and Carroll (2003), our discussion includes specified measurement error and measurement error estimated by replicate error-prone proxies. In addition, we discuss and illustrate three extrapolant functions.
Tipo: Journal Article Palavras-chave: Simulation extrapolation; Measurement error; Instrumental variables; Replicate measures; Generalized linear models; Research Methods/ Statistical Methods.
Ano: 2003 URL: http://purl.umn.edu/116184
Imagem não selecionada

Imprime registro no formato completo
Variance estimation for the instrumental variables approach to measurement error in generalized linear models AgEcon
Hardin, James W.; Carroll, Raymond J..
This paper derives and gives explicit formulas for a derived sandwich variance estimate. This variance estimate is appropriate for generalized linear additive measurement error models fitted using instrumental variables. We also generalize the known results for linear regression. As such, this article explains the theoretical justification for the sandwich estimate of variance utilized in the software for measurement error developed under the Small Business Innovation Research Grant (SBIR) by StataCorp. The results admit estimation of variance matrices for measurement error models where there is an instrument for the unknown covariate.
Tipo: Journal Article Palavras-chave: Sandwich estimate of variance; Measurement error; White's estimator; Robust variance; Generalized linear models; Instrumental variables; Research Methods/ Statistical Methods.
Ano: 2003 URL: http://purl.umn.edu/116177
Registros recuperados: 11
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

Valid HTML 4.01 Transitional