The Risk Analysis in the Agricultural Enterprises using Earnings at Risk Method

The paper examines the potential of stochastic simulation methods and Earnings at Risk method in risk analysis of farming business. The results revealed a different nature of yield and price risks in agriculture. The natural yields are low spatially correlated and the rate of yield risk depends on the climate and weather features, soil properties, technology of production and other predominantly natural variables. Estimates of yield probability distribution require the most individualized data. Price risk has higher spatial correlation. The case study illustrates that the Monte Carlo simulation and Earnings at Risk method are suitable tools for risk analysis in econometric models at the farm level as well as at the aggregate level.