Sequential Adoption of Package Technologies: The Dynamics of Stacked Trait Corn Adoption

Abstract

GM corn seed companies have innovated continuously with the introduction of new traits and, more recently, with the creation of stacked varieties, which combine more than one trait. This work develops a Bayesian model of adoption dynamics that demonstrates how uncertainty with a package technology with known risk can lead to a sequential adoption pattern in which farmers adopt a single component first. We then develop a semiparametric panel data model of adoption dynamics to measure the effects of experience with single trait (non-stacked) varieties 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, i.e., a sequential adoption process. There is also evidence that farmers with more human capital tend to learn faster from own experience and that as the GM corn-technology diffusion process deepens, the importance of early experience decreases.Crop Production/Industries,