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Determining Optimal Levels of Nitrogen Fertilizer Using Random Parameter Models

Published online by Cambridge University Press:  26 January 2015

Emmanuel Tumusiime ,
Brorsen B. Wade ,
Jagadeesh Mosali ,
Jim Johnson ,
James Locke  and
Jon T. Biermacher
Brorsen B. Wade
Affiliation:
Department of Agricultural Economics at Oklahoma State University
Jon T. Biermacher
Affiliation:
Agricultural Division of The Samuel Roberts Noble Foundation, Inc.
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Abstract

The parameters of yield response functions can vary by year. Past studies usually assume yield functions are nonstochastic or “limited” stochastic. In this study, we estimate rye–ryegrass yield functions in which all parameters are random. The three functional forms considered are the linear response plateau, the quadratic, and the Spillman-Mitscherlich. Nonstochastic yield models are rejected in favor of stochastic parameter models. Quadratic functional forms fit the data poorly. Optimal nitrogen application recommendations are calculated for the linear response plateau and Spillman-Mitscherlich. The stochastic models lead to smaller recommended levels of nitrogen, but the economic benefits of using fully stochastic crop yield functions are small because expected profit functions are relatively flat for the stochastic yield functions. Stochastic crop yield functions provide a way of incorporating production, uncertainty into input decisions.

Keywords

cereal rye—ryegrassMonte Carlonitrogenrandom parametersstochastic plateauQ10C12D24
Type
Research Article
Information
Journal of Agricultural and Applied Economics , Volume 43 , Issue 4 , November 2011 , pp. 541 - 552
Copyright
Copyright © Southern Agricultural Economics Association 2011

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