A conceptual link among mean-variance (EV), stochastic dominance (SD), and mean-risk (ET), and Gini mean difference (EG) is established for determining risk efficient decision sets. The theoretical relations among the various efficiency criteria are then empirically demonstrated with a soybean and wheat double-crop simulation model. Empirical results associated with extended Gini mean difference (EEG) and extended mean-absolute Gini (EET) for risk analysis are encouraging.