Incorporating Stochasticity into Enterprise Budgeting: A Monte Carlo Simulation Approach
ISSN 2158-9429
Volume 18, Issue 2 - December 2025
Editor: Bindu Poudel-Ward
Abstract
This study incorporates stochastic elements into a deterministic enterprise budget framework to evaluate economic risk in cherry tomato production. Drawing on data from two Iowa farms, Johnson and Roller/Schintler, the analysis models four key economic indicators: marketable harvest, gross revenue, total cost, and net income. These indicators are represented using triangular probability distributions, parameterized through expert-informed estimates. In the absence of historical time-series data, this approach applies a ±10% range around observed values to facilitate probabilistic risk assessment via the Monte Carlo method. Simulations comprising 50,000 iterations per variable were executed in Excel, illustrating the utility of stochastic modeling in enhancing financial planning and decision-making under uncertainty, particularly for beginning farmers and ranchers.
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