ADOPTION OF EMERGING TECHNOLOGIES UNDER OUTPUT UNCERTAINTY

A model of divisible technology adoption under incomplete information dissemination and output uncertainty is developed. We identify economic and subjective factors affecting technology adoption and its intensity. Empirical estimation employs a mixed dichotomous-continuous framework with nonrandom sample selection. Producers' adoption intensity is conditional on their knowing about and deciding to adopt the new technology. Using survey data on bST (bovine somatotropin) adoption among Texas dairy producers, we find that larger and more educated operators are likely to adopt more intensively. Traditional dichotomous adoption models without sample selection significantly overestimate the adoption rate.