We utilize an agricultural model that uses crop/weather relationships at the county resolution and fits robust distributions that take into account the impact that weather has on crop production. Once the crop insurance policy conditions and prices are applied to the modeled county yield...

Many studies have done econometric estimates of how climate alters crop yields and or land rents in an effort to gain information on potential effects of climate change. However, an important related factor, the atmospheric carbon dioxide (CO2) concentration, and in fact a driver of climate...

Using an extensive household-level data set collected in Tanzania, this paper investigates the determinants of the technological adoption of rice cultivation and of paddy yield. We especially focus on the impact of credit and training on the adoption of modern technologies. Based on empirical...

We used survey data collected from cotton producers in eleven U.S. states to address the issues of correlated events and individual heterogeneity in multiple precision technologies adoption. Results from a conditional frailty model indicated that younger, better educated cotton producer adopted...

Technology and innovation play an increasingly important role in the economic development of both developed and developing countries. We investigate how policy and market factors influence firms’ (or other potential innovators’) decisions on innovation or imitation by developing a conceptual...

Recent studies in the literature examining impact of government seed price intervention on adoption of Bt cotton get different results depending on the specifics of the situation analyzed. According to one study, reduction in seed prices enables farmers to buy seeds at lower prices and this can...

A nested logit model was used to analyze the 2009 Southern Cotton Precision Farming Survey to study the impact of farmer and farm characteristics on the adoption of Variability Detection Technologies (VDT) and the adoption of Variability Rate application Technology (VRT) conditioned on the type...

We used the 2009 Southern Cotton Precision Farming Survey data collected from farmers in twelve U.S. states (Alabama, Arkansas, Florida, Georgia, Louisiana, Missouri, Mississippi, North Carolina, South Carolina, Tennessee, Texas, and Virginia) to understand why farmers do not adopt seemingly...

Agricultural technology adoption is often a sequential process. Farmers may adopt a new technology in part of their land first and then adjust in later years based on what they learn from the earlier partial adoption. This paper presents a dynamic adoption model with Bayesian learning, in which...

Prior research identifies a direct positive link between the stock of public scientific knowledge and agricultural productivity; however, an indirect contribution to agricultural productivity is also possible when this stock facilitates private sector invention. This study examines how...