Kitamura and Stoye (2018) recently proposed a nonparametric statistical test for random utility models of consumer behavior. The test is formulated in terms of linear inequality constraints and a quadratic objective function. While the nonparametric test is conceptually appealing, its practical implementation is computationally challenging. In this paper, we develop a column generation approach to operationalize the test. These novel computational tools generate considerable computational gains in practice, which substantially increases the empirical usefulness of Kitamura and Stoye's statistical test.

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随机效用模型的非参数分析：用于统计检验的计算工具

Kitamura和Stoye（2018）最近为消费者行为的随机效用模型提出了一种非参数统计检验。该检验是根据线性不等式约束和二次目标函数制定的。尽管非参数测试在概念上很有吸引力，但其实际实现在计算上却具有挑战性。在本文中，我们开发了一种色谱柱生成方法来进行测试操作。这些新颖的计算工具在实践中产生了可观的计算收益，从而大大提高了北村和斯托耶的统计检验的经验实用性。