Tests for stochastic dominance are important tools for the comparison of distributions between pairs of random variables. In finance, dominance criteria can potentially provide an unambiguous ranking of the desirability of different assets while placing only general restrictions on the preferences of investors. In welfare economics, dominance concepts allow for the ranking of income distributions using generally accepted welfare criteria. Existing dominance test procedures suffer from a number of weaknesses. One weakness concerns restrictions on the class of distribution functions that may be used as a basis for testing. While early literature in this area typically ignored sampling errors, this issue has been addressed in more recent literature, but only at the cost of restricting the class of parametric distributions discussed; see e.g. Stein and Pfaffenberger (1986). Since dominance criteria are attractive primarily because they allow for a ranking of returns on risky assets or income distributions, while placing only weak restrictions on preferences, it is important that dominance tests retain a degree of generality, and hence remain nonparametric in nature. Another weakness of existing dominance tests is that these often specify the null hypothesis improperly; see e.g. Bishop et al. (1989). For example, most test procedures make use of the null hypothesis that two distribution or quantile functions are identical. The hypothesis of dominance may be viewed as an hypothesis of inequality in a particular direction between two distribution or quantile functions. If such an hypothesis is rejected, then dominance cannot be sustained, a result that may or may not be caused by the equality of the two distribution or quantile functions. On the other hand, if the null hypothesis of equality is rejected, then the two distributions cannot be said to be equal, but the cause may or may not be that one dominates the other. Thus the null hypothesis of equality is not very helpful in providing information about dominance; see Levy (1992, p. 574).