2 research outputs found

    Gene editing and agrifood systems

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    Gene-editing technologies represent a promising new tool for plant and animal breeding in low- and middle-income countries. They enhance precision and efficiency over current breeding methods and could lead to rapid development of improved plant varieties and animal breeds. However, as for any new technology, they have their merits and demerits. There is, as yet, no international consensus regarding if and how gene-edited organisms should be regulated, and whether their release would fall under the regulatory framework of the Cartagena Protocol on Biosafety to the Convention on Biological Diversity. This science- and evidence-based Issue Paper on gene editing and agrifood systems presents a balanced discussion of the most pertinent aspects of gene editing, including the consequences for human hunger, human health, food safety, effects on the environment, animal welfare, socioeconomic impact and distribution of benefits. Intrinsic ethical concerns and issues of governance and regulation are addressed, and the roles of the public and private sectors, alone and in partnership, are summarized. Various scenarios are also presented for how gene editing might be used in the future to help transform agrifood systems

    Monopolistic pricing power for transgenic crops when technology adopters face irreversible benefits and costs

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    Pricing of biotechnology innovation under a patent grant is reconsidered in a model with uncertain returns and irreversible costs and benefits. Past results on restricted monopoly pricing in the presence of competing technologies showed that pricing power is reduced. The timing of adoption of an innovation is delayed and the pricing power of the restricted monopolist is further reduced when uncertainty and irreversibility is considered. The presence of irreversible benefits results in increased willingness-to-pay for the innovation, accelerating adoption, and increasing the innovator's restricted monopolist pricing power. Using Monte-Carlo simulation, the quantitative effects were approximated by a linear function through the hyper-plane.
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