| Summary: | With many genetic traits discovered and many more in progress, it is imperative to the industry that firms (biotechnology companies) decide on the trait valuation and pricing. This includes more than one trait (also referred to as stacked traits) in a single variety of crop; the risk and uncertainty of expected returns associated with the development and release of a variety increases even more in case of stacked traits. The purpose of this thesis is to develop a model that can be used for the valuing and pricing of genetically modified (GM) traits that are random, sporadic, and non-persistent (e.g. drought tolerance, heat/cold stress) using the real option approach. The efficiency gain in case of occurrence of random event and expression of GM traits will be measured and used as a decision factor in determining the value of GM trait(s) at different phases of development. === Agribusiness and Applied Economics === Agribusiness and Applied Economics === College of Agriculture, Food Systems and Natural Resources
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