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Valuing Transgenic Cotton Technologies Using a Risk/Return Framework

Published online by Cambridge University Press:  26 January 2015

Kelly J. Bryant ,
Jeanne M. Reeves ,
Robert L. Nichols ,
Jeremy K. Greene ,
Christopher H. Tingle ,
Glenn E. Studebaker ,
Fred M. Bourland ,
Charles D. Capps Jr.  and
Frank E. Groves
Kelly J. Bryant
Affiliation:
Southeast Research and Extension Center, University of Arkansas Division of Agriculture, Monticello, AR
Jeanne M. Reeves
Affiliation:
Cotton Incorporated, Cary, NC
Robert L. Nichols
Affiliation:
Cotton Incorporated, Cary, NC
Jeremy K. Greene
Affiliation:
Edisto Research and Education Center, Clemson University, Blackville, SC
Christopher H. Tingle
Affiliation:
Syngenta Crop Protection, Vero Beach Research Center, Vero Beach, FL
Glenn E. Studebaker
Affiliation:
Northeast Research and Extension Center, University of Arkansas Division of Agriculture, Keiser, AR
Fred M. Bourland
Affiliation:
Northeast Research and Extension Center, University of Arkansas Division of Agriculture, Keiser, AR
Charles D. Capps Jr.
Affiliation:
University of Arkansas Division of Agriculture, Monticello, AR
Frank E. Groves
Affiliation:
Southeast Research and Extension Center, University of Arkansas Division of Agriculture, Monticello, AR
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Abstract

Stochastic Efficiency with Respect to a Function (SERF) is used to rank transgenic cotton technology groups and place an upper and lower bound on their value. Yield and production data from replicated plot experiments are used to build cumulative distribution functions of returns for nontransgenic, Roundup Ready, Bollgard, and stacked gene cotton cultivars. Analysis of Arkansas data indicated that the stacked gene and Roundup Ready technologies would be preferred by a large number of risk neutral and risk averse producers as long as the costs of the technology and seed are below the lower bounds calculated in this manuscript.

Keywords

cottonfinancial riskmarket valueSERFtransgenicQ12Q16
Type
Research Article
Information
Journal of Agricultural and Applied Economics , Volume 40 , Issue 3 , December 2008 , pp. 767 - 775
Copyright
Copyright © Southern Agricultural Economics Association 2008

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