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Abstract
Advances in the genetic modification of agricultural seeds have allowed a range of new
opportunities for manipulating seed traits according to production, market and environmental
concerns. As seed varieties continue to become increasingly differentiated, preferences for
specific seed traits may be expected to impart significant effects on farmer demand for new
seeds. This paper proposes a model of technology adoption that integrates demand for traits of
new technologies with the potential for heterogeneity based on farm and farmer characteristics.
The model is applied to recent GM corn adoption data from Minnesota and Wisconsin farmers,
and uses conditional logit and mixed multinomial logit econometric models to estimate the
effects of traits and farm and farmer characteristics on adoption outcomes.