This article examines the factors that account for agricultural biotechnology patenting success among universities using a dynamic count data model. It builds a theoretical and econometric model to capture the inherently dynamic and nonlinear process of technological innovation, wherein a...

This article proposes a model of technology adoption that integrates demand for individual traits of new technologies with the potential for heterogeneity based on farm and farmer characteristics. The model is applied to recent genetically modified corn adoption data from Minnesota and Wisconsin...

This article exploits panel data from Wisconsin dairy farmers to examine the dynamics of recombinant bovine somatotropin (rBST) adoption and to identify the characteristics that distinguish among nonadopters, disadopters, and early and late adopters. Panel methods are used to control for omitted...

Trends and determinants in the adoption of recombinant bovine somatotropin are examined using data from across the United States. The core findings are: (a) moderate adoption rates and relatively small impacts on national milk production; (b) substantial disadoption, farmers who have tried the...

This work analyzes the evolution of time allocation for agricultural and life science faculty in Tier 1 US research universities from 1975 to 2005. Specifically, it explores the trends with respect to time spent on research versus administrative activities, and shows about a 20% decline in the...

Genetically modified corn seed companies have recently created stacked varieties which combine more than one trait. This work develops a Bayesian model that demonstrates how uncertainty with a package technology can lead to an adoption pattern in which farmers move from single trait to stacked...