Semester of Graduation

Fall 2021

Degree

Master of Science (MS)

Department

AGEC

Document Type

Thesis

Abstract

A grower’s crop enterprise selection plays a substantial role in determining the operational profitability in areas that are capable of growing diverse crops, such as the northern and central regions of Louisiana. Each crop enterprise selection is subject to variation in risk as market conditions, weather, and production costs can all be critical factors that could potentially impact the level of per-acre net returns to the grower. Variations or volatility in one or more of these risk categories can result in growers electing to plant alternative enterprises on their farms. Simulation modeling allows farm managers the ability to calculate mean net return values (per-acre) for each crop enterprise based on the construction of representative farms that emulate production conditions for a particular region. For the purposes of this research project, three representative farms are modeled for the northwestern, northeastern, and central regions of Louisiana. Stochastic efficiency with respect to a function (SERF) will be utilized to rank the alternative cotton, corn, and soybeans enterprises based on certainty equivalents (CE) that are defined by the grower’s share of net returns above variable costs per acre across a range of absolute risk aversion coefficients. The result of this research will provide ordinal and cardinal rankings of which farm management enterprise decision within cotton, corn, and soybeans cropping options will provide growers with maximum net returns across varying levels of risk aversion that suits an individual’s risk preference.

Committee Chair

Deliberto, Michael A.

DOI

10.31390/gradschool_theses.5438

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