Stochastic Dominance Tests for Decreasing Absolute Risk Aversion. I. Discrete Random Variables

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Abstract
Stochastic dominance (SD) theory is concerned with orderings of random variables by classes of utility functions characterized solely in terms of general properties. This paper discusses a type of stochastic dominance, called DSD, which is denned by the utility functions having decreasing absolute risk-aversion. Necessary and sufficient conditions for DSD are presented for discrete random variables which, after the possible addition of points of zero probability, are concentrated on finitely many equally-spaced points. The problem is cast as a nonlinear program, which is solved through an efficient dynamic programming routine. Examples are presented to illustrate the increased effectiveness of DSD relative to previous types of stochastic dominance.

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