BAYESIAN RISK METHODOLOGY FOR CROP INSURANCE DECISIONS

A Bayesian risk methodology is outlined for making decisions under unc ertainty. A practical example is given for a crop insurance where the insurer decides how to take risks. The insurer's objective is formulat ed as a goal function whose expected value must equal zero. Risk to th e insurer arises from the uncertainty and variation in the input varia bles of a previously developed deterministic yield model. Monte Carlo simulation provides a cumulative frequency histogram of the goal funct ion from which risks are calculated. The methodology is general and ca n be used in many situations to determine the risk in a project from u ncertain inputs.