An out-of-sample prediction of Kansas farmers' responses to five surveyed questions involving risk is used to compare ordered multinomial logistic regression models with feedforward backpropagation neural network models. Although the logistic models often predict more accurately than the neural...

Out-of-sample forecasting of annual U.S. per capita food consumption, applying data from 1923 to 1992, is used as a basis for model selection among the absolute price Rotterdam model, a first-differenced linear approximate almost ideal demand system (FDLA/ALIDS) model, and a first-differenced...

Recent evidence suggests that cyclical cattle inventories are driven by exogenous shocks. This article examines a second possible contributing factor to the cattle cycle: a market timing effect that arises from individual attempts to maintain countercyclical inventories. The model uncovers an...

This article proposes a fully integrated and interactive elicitation-optimization procedure for portfolio management. A soft computing approach based on fuzzy logic is developed as an alternative to the traditional mean variance model and compromise programming approach. The models are applied...

Current crop insurance rating procedures consider only performance for the individual crop in question. Recent farm legislation has given producers considerable planting flexibility and, as a result, many have shifted to new crops. Producers without a production history for the new crop may be...

The reliability of several statisitcal software packages was examined using the National Institute of Standards and Technology linear and nonlinear least squares datasets and models. Software tested include Excel 2007, GAMS 23.4, GAUSS 9.0, LIMDEP 8.0, Mathematica 7.0, MATLAB 7.5, R 2.10, SAS...