2003

April, 2003

By: McNew, Kevin; Smith, Vincent H.
The introduction of genetically modified grain and oilseed products at the farm level and resistance for these products by consumer groups have led to segmentation in grain markets. This study explores the implications for market price behavior for a segregated soybean market for genetically modified (GM) and non-GM varieties. A stochastic dynamic simulation model of production and storage is solved, and Monte Carlo simulation procedures are used to examine price behavior between GM and non-GM soybeans. The results suggest important differences in price behavior between GM and non-GM soybeans. The results obtained in the model simulations are compared with evidence from the Tokyo Grain Exchange, where non-GM and GM soybean futures contracts have traded simultaneously since May 2000. The evidence from the Tokyo Grain Exchange contracts is largely consistent with the results of the simulation model. Price correlations between the Tokyo Grain Exchange non-GM and GM soybean contracts tended to be similar in magnitude to those found in the simulations.

April, 2003

By: Hennessy, David A.; Saak, Alexander E.
Suppose a farmer had to apply a herbicide pre-emergence or not at all. The advent of a herbicide-tolerance trait innovation then provides the option to wait for more information before making a state-contingent post-emergence application. This option to wait can increase or decrease average herbicide use. For heterogeneous acre types, trait royalties increase with the level of uncertainty about the extent of weed damage. Royalties are largest when acre infestation susceptibility types are bunched around the type indifferent to applying the herbicide in the absence of the trait. The trait complements (substitutes for) information technologies that facilitate informed post-emergence (pre-emergence) decisions.

April, 2003

By: Park, Timothy A.; Florkowski, Wojciech J.
Timely adoption of new varieties is critical to profitable peach production, and peach quality is a primary factor driving adoption. An adoption model for peach varieties is estimated, incorporating grower evaluations of peach quality. The model identifies the impact of farm characteristics such as the farmer's quality preferences, on-farm agronomic and orchard conditions, as well as geographic effects in Georgia peach-growing regions. The relative impact of the key external and internal peach quality attributes on adoption is assessed. Decisions on new varieties are influenced by the age distribution of the orchard, information which can be used in targeting new varieties to growers.