FARGO, N.D. — June 16, 2026, The Agricultural Risk Policy Center (ARPC) at North Dakota State University has released a new technical report presenting a stochastic simulation framework for analyzing crop yield risk, price uncertainty, and agricultural policy outcomes.

The report, A Technical Manual for Stochastic Simulation of Crop Yield, Price, and Policy Outcomes, introduces a flexible modeling framework that combines historical crop yield data, market-based price information, copula methods, and crop insurance calibration to simulate agricultural outcomes under uncertainty.

The framework is designed to support policy evaluation by generating realistic joint distributions of crop yields and prices while preserving observed variability, downside risk, and dependence across crops and geographic regions. The model can be applied to evaluate crop insurance programs, farm safety net programs, and alternative policy scenarios at the national, state, county, and farm levels.

Using a nonparametric approach, the framework preserves real-world yield variability, downside risk, and county-specific production characteristics without relying on restrictive statistical assumptions. It also incorporates multiple sources of market information, including futures prices, implied volatility, Marketing Year Average (MYA) prices, FSA projections, and user-defined forecasts, to evaluate price uncertainty under a variety of market and policy scenarios.

To better reflect how agricultural risks interact, the model uses copula methods to capture the complex relationships between crop yields, commodity prices, and regional outcomes while maintaining realistic correlations across counties and production regions. Farm-level risk is further calibrated using USDA Risk Management Agency (RMA) Yield Protection data, linking county-level simulations to farm-level production risk and enabling more accurate assessments of crop insurance and farm safety net programs.

The modular design allows researchers to adapt individual components, including yield modeling, price simulation, dependence structures, farm-level calibration, and policy payment analysis, for different crops, regions, and policy applications, making the framework a flexible tool for agricultural risk and policy research.

"This report introduces a flexible stochastic simulation framework for jointly modeling crop yields, prices, and policy outcomes," said Dr. Sandro Steinbach, co-author and director of ARPC. "The framework provides researchers and policymakers with a practical tool for evaluating agricultural risk management programs under a wide range of production and market conditions."

The full report is available at:
https://www.dropbox.com/scl/fi/w27amhm7mogc8ng6ecsho/ARPC_Report_2026_03-JL-SA-SS.pdf?rlkey=rh3mngg5309gtx0oel6nt4prw&raw=1

Media Contact:
Agricultural Risk Policy Center (ARPC)
North Dakota State University
arpc@ndsu.edu
www.ndsu.edu/agriculture/arpc