The sequential adoption of package technologies : the dynamics of stacked trait corn adoption

Genetically modified corn seed companies have innovated continuously with the introduction of new traits and, more recently, with the creation of stacked varieties. Thiswork develops a Bayesian model of adoption that demonstrates how uncertainty with a package technology can lead to a sequential adoption pattern in which farmers move from single trait to stacked varieties. We then develop a semi-parametric panel data model of adoption to measure the effects of experience on the adoption of stacked varieties. The results underscore the importance of early experience with the non-stacked technology in the subsequent adoption of stacked varieties. There is also evidence that farmers with more human capital tend to learn faster from own experience and that as time evolves, the importance of early experience decreases.