Real-time ultrasound information taken on beef heifers prior to backgrounding is used to develop a logit model to aid heifer retention decisions. The value of ultrasound data is calculated as the difference in certainty equivalents between a decision rule incorporating ultrasound information and one using only visual cues. The value of ultrasound data is found to be around $10 per head but is influenced by heifer value and backgrounding costs.

Binary logit analysis was used to identify the factors influencing adoption of Global Positioning System (GPS) guidance systems by cotton farmers in 11 Mid-south and Southeastern states. Results indicate that adoption was more likely by those who had already adopted other precision-farming practices and had used computers for farm management. In addition, younger and more affluent farmers were more likely to adopt. Farmers with larger farms and with relatively high yields were also more likely to adopt. Education was not a significant factor in a farmer's decision to adopt GPS guidance systems.

This study uses a bivariate probit model with partial observability to examine Louisiana beef producers' awareness of the Environmental Quality Incentives Program (EQIP) and how awareness translates to application to the program. Results indicate that awareness of and application to the EQIP depend on portion of income derived from off-farm sources, extent of previous best management practice adoption at one's own expense, household income, farmed land that is highly erodible, contact with Natural Resource Conservation Service and extension service personnel, and producer age.

Crawfish processors' ex ante adoption rates of three hypothetical crawfish peeling machines are assessed using a polychotomous-choice elicitation format. Adoption rates would likely range from 23% to 70%, depending upon which machine was offered and whether it was purchased or leased. Processors most likely to adopt are determined using ordered probit analysis. Likely adopters would be larger, more diversified processors with greater resources and longer planning horizons.

There is comparatively little empirical evidence regarding the accuracy of regional housing sector forecasts. Much of the recent analysis conducted for this topic is developed for housing starts and indicates a relatively poor track record. This study examines residential real estate forecasts previously published for El Paso, TX using a structural econometric model. Model coverage is much broader than just starts. Similar to earlier studies, the previously published econometric predictions frequently do not fare very well against the selected random walk benchmarks utilized for the various series under consideration.