Essays on Using Experimental Agronomic Data to Solve Practical Cropping Decision Problems

Abstract

Across the United States, agronomic research is being conducted that provides agricultural producers with new cropping options; however, without having insight into the profitability or risk associated with the options, producers may not make the optimal decision for their operation. This dissertation consists of three essays in applied agricultural economics utilizing experimental agronomic data to solve practical cropping decision problems. The first chapter examines the impact of row spacing, tillage, and seed traits on cotton profitability in Alabama, and estimates profits using an application of a single equation and a multi-equation approach. Overall, estimating a single equation profit function and constructing profit from multi-equation response functions produced similar results. Non-transgenic seed planted with standard and narrow spacing utilizing both conservation and conventional tillage were in the top five most profitable production options regardless of rainfall amount and estimation method. The second chapter determines the optimal crop rotation for a peanut and cotton producer in Alabama under alternative land tenure arrangements considering previous land use and Markovian prices. The decision to adopt a rotation instead of monoculture is heavily influenced by expected yield, production costs, and expected prices. The land ownership scenario has the lowest annualized net returns, and cash rent flexed on yield scenario has the highest annualized net returns based on the model assumptions. The third chapter incorporates a safety-first constraint into the dynamic programming model developed in Chapter 2 to determine the optimal crop rotation for a peanut and cotton producer in Alabama under alternative land tenure arrangements assuming a producer can choose to leave land fallow. Adopting a peanut/cotton crop rotation with the option of fallowing with consideration given to the type of land tenure arrangement may be an appropriate risk management option for producers.