The conditional beta distribution as a stochastic production function

The conditional beta distribution is proposed as a parametric model of the probability distribution of agricultural output. A two-stage maximum likelihood estimation procedure is shown to produce consistent, asymptotically efficient and normal estimates of maximum output and the parameters of the co...

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Bibliographic Details
Published in:American journal of agricultural economics 1989-05, Vol.71 (2), p.370-378
Main Authors: Nelson, Carl H., Preckel, Paul V.
Format: Article
Language:English
Subjects:
ANALISIS DE INSUMO-PRODUCTO
ANALISIS ESTADISTICO
ANALYSE INPUT OUTPUT
ANALYSE STATISTIQUE
APLICACION DE FERTILIZANTES
beta distribution
Coefficients
Consistent estimators
Corn
Crops
ESTADISTICA
FERTILISATION
FONCTION DE PRODUCTION
FUNCIONES DE LA PRODUCCION
IOWA
Mathematical moments
Maximum likelihood estimation
Maximum likelihood estimators
MODELE
MODELOS
Nitrogen
PREVISION DE RENDEMENT
PRODUCCION
PRODUCTION
PROGRAMACION
PROGRAMMATION
PRONOSTICO DEL RENDIMIENTO
RENDEMENT
RENDEMENT DES CULTURES
RENDIMIENTO
RENDIMIENTO DE CULTIVOS
RIESGO
RISQUE
Skewed distribution
skewness
Statistical variance
STATISTIQUE
stochastic production
two-stage maximum likelihood estimation
yield distributions
ZEA MAYS
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Description
Summary:The conditional beta distribution is proposed as a parametric model of the probability distribution of agricultural output. A two-stage maximum likelihood estimation procedure is shown to produce consistent, asymptotically efficient and normal estimates of maximum output and the parameters of the conditional distribution. Application of the procedure to data on corn yield response to fertilizers shows that fertilizers have a significant impact on each of the first three moments of the distribution of corn yield. Corn yield distributions are found to be negatively skewed, implying that above average yields are more probable than below average yields.
ISSN:0002-9092
1467-8276
DOI:10.2307/1241595