Estimating the Economic Effects of Gmos : The Importance of Policy Choices and Preferences

The new agricultural biotechnologies that are generating transgenic or genetically modified organisms (GMOs) are attracting an exceptionally large degree of opposition to their production and trade. Both environmental and food safety concerns have been raised by opponents to the development of transgenic crops. The vast majority of opponents want at least to have labels on products that may contain GMOs, while the most extreme of them (particularly in Western Europe) want to see GM crops totally excluded from production and consumption in their country. This extreme view contrasts with the more relaxed attitude towards the use of GMOs in pharmaceuticals, and swamps discussions of the positive attributes of the new technology. Also associated with that view is the idea that we should not try to measure the economic and other effects of GMOs because there is too much uncertainty surrounding the technology. We beg to differ with the latter sentiment, believing that without attempts to quantify the economic effects of GMOs, opinion formation and policy making would be even less well informed because it would have to depend even more on guesswork. To illustrate the usefulness of quantitative models for informing GMO debates, the present paper draws on three recent studies by the authors that use existing empirical models of the global economy to examine what the effects of widespread adoption of genetically modified crop varieties in some (non-European) countries might be in light of different policy and consumer preference responses. Specifically, the effects of an assumed degree of GMO-induced productivity growth in selected countries for cotton, rice, and maize plus soybean are explored. In the latter case those results are compared with what they would be if (a) Western Europe chose to ban consumption and hence imports of those products from countries adopting GM technology or (b) some Western European consumers and intermediate users responded by boycotting imported GM crops. Then another global CGE model is introduced which distinguishes GM-inclusive from GM-free maize and soybean. It is used to explore the impact of increased preferences for GM-free food. The final section discusses areas where future empirical work of this sort might focus