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A Dynamic Decision Model of Technology Adoption under Uncertainty: Case of Herbicide-Resistant Rice

Published online by Cambridge University Press:  28 April 2005

Mamane M. Annou ,
Eric J. Wailes  and
Michael R. Thomsen
Mamane M. Annou
Affiliation:
Department of Agricultural Economics and Agribusiness, Division of Agriculture, University of Arkansas, Fayetteville, AR
Eric J. Wailes
Affiliation:
Department of Agricultural Economics and Agribusiness, Division of Agriculture, University of Arkansas, Fayetteville, AR
Michael R. Thomsen
Affiliation:
Department of Agricultural Economics and Agribusiness, Division of Agriculture, University of Arkansas, Fayetteville, AR
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Abstract

Herbicide-resistant (HR) rice technology is a potential tool for control of red rice in commercial rice production. Using an ex ante mathematical programming framework, this research presents an empirical analysis of HR rice technology adoption under uncertainty. The analysis accounts for stochastic germination of red rice and sheath blight to model a profit maximization problem of crop rotation among HR rice, regular rice, and soybeans. The results demonstrate that risk attitudes and technology efficiency determine adoption rates and optimal rotation patterns.

Keywords

biotechnologyherbicide resistancemathematical programmingprofit maximizationriceriskrotationtechnology adoptionQ16Q18O33C61
Type
Articles
Information
Journal of Agricultural and Applied Economics , Volume 37 , Issue 1 , April 2005 , pp. 161 - 172
Copyright
Copyright © Southern Agricultural Economics Association 2005

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