COUNT-DATA REGRESSION-MODELS OF THE TIME TO ADOPT NEW TECHNOLOGIES

This paper presents a framework for interpreting and using the count-d ata model for estimating the time of technology adoption. The Bernoull i trials of the negative binomial model are interpreted as the stages involved in a potential adopter learning and updating information rele vant to a new technology. Empirically, the paper estimates the Poisson , the generalized negative binomial, and the geometric models in order to identify the determinants of computer adoption on farms in Califor nia.