Futures prices when combined with a basis forecast provide a reliable way to forecast cashprices. The most popular method of forecasting basis is historical moving averages. Given therecent failure of longer moving averages proposed by previous studies, this research reassessespast...

A Cox test with parametric bootstrap is developed to select between the linearized version of the First-Difference Almost Ideal Demand System (FDAIDS) and the Rotterdam model. A Cox test with parametric bootstrap has been shown to be more powerful than encompassing tests like those used in past...

This study instructs an artificial price competition market to examine the impact of capacity constraints on the behavior of packers. Results show when there are cattle left for the lowest bidder after all other packers finishing their procurement, the capacity constraints make the price lower...

Training a neural network is a difficult optimization problem because of numerous local minimums. Many global search algorithms have been used to train neural networks. However, local search algorithms are more efficient with computational resources, and therefore numerous random restarts with a...

A method of estimating a linear response stochastic plateau function is developed and used to determine optimal levels of nitrogen fertilization for wheat. Under the stochastic plateau model, optimizing behavior implies different nitrogen levels than the linear plateau model, depending on the...

Improved software now makes Bayesian estimation a strong alternative to nonlinear maximum likelihood. Bayesian methods were used to estimate a linear response stochastic plateau for cotton and were shown to provide estimates similar to maximum likelihood. Optimal levels of nitrogen were lower...

A new stochastic process is introduced where permanent changes occur following a Poisson jump process and temporary changes occur following a normal distribution. The model is estimated using hard wheat basis data and is used to explain why the optimal length of moving average to forecast basis...