STOCHASTIC-DOMINANCE ON UNIDIMENSIONAL GRIDS

Special stochastic-dominance relations for probability distributions o n a finite grid of evenly-spaced points are considered. The relations depend solely on iterated partial sums of grid-point probabilities and are very computer efficient. Their corresponding classes of utility f unctions for expected-utility comparisons consist of functions defined on the grid that mimic in the large the traditional continuous functi ons whose derivatives alternate in sign. The first-degree and second-d egree relations are identical to their traditional counterparts define d from iterated integrals of cumulative distribution functions. The hi gher-degree relations differ from the traditional relations in interes ting and sometimes subtle ways. The paper explores aspects of the part ial-sums relations, including effects of grid refinements and extensio ns, and describes their relationships to the traditional relations.