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Abstract

Simulation-optimization techniques are employed to analyze changes in farmland control arrangements as a result of using different constructs of intertemporal risk behavior. Risk behavior based on constant absolute risk aversion (CARA) and constant relative risk aversion (CRRA) mean-standard deviation functions are used to achieve this objective. Specfically, a multi-period programming framework for a representative grain farm is developed to explore farmland control decisions under these two behavioral assumptions. Our results suggest that the use of a CRRA behavioral construct in analyzing farmland control decisions produce predictions that are more consistent with observed farm behavior.

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