A multiway cluster-robust test for stochastic dominance
提出一种新的Kolmogorov-Smirnov检验，用于多向聚类抽样下的随机占优假设检验，能有效控制检验规模并保持稳健性，应用于收入数据发现男性收入在有子女的工人中随机占优女性。
Accounting for multiway clustering is essential for valid statistical inference. This paper develops a new Kolmogorov–Smirnov test for stochastic dominance that accommodates multiway clustered sampling, where separate exchangeability holds and non-overlapping cells are independent. The proposed test controls the size well asymptotically and is consistent against fixed alternatives. More importantly, our test remains valid whether or not clustering is present, and if so, irrespective of its form. Simulation results support the theoretical findings in that the proposed test maintains excellent size control and has good power under multiway clustering across various settings, while remaining conservative in degenerate and i.i.d. cases. Applied to income distribution data, the results are consistent with the hypothesis that male income stochastically dominates female income among workers with children, while no clear dominance relationship is observed among childless workers. Moreover, the evidence provides support for the dominance of fathers’ income distribution over that of childless men, whereas no such relationship is supported among female workers.