NONPARAMETRIC ANALYSIS OF RANDOM UTILITY MODELS: COMPUTATIONAL TOOLS FOR STATISTICAL TESTING

• 成果类型: Article
• 署名作者: Smeulders, Bart; Cherchye, Laurens; De Rock, Bram
• 署名单位: Eindhoven University of Technology; KU Leuven; Universite Libre de Bruxelles
• 刊物名称: ECONOMETRICA
• ISSN/ISSBN: 0012-9682
• DOI: 10.3982/ECTA17605
• 发表日期: 2021
• 页码: 437-455
• 关键词: SCORING RULES; INFORMATION; beliefs; probability; mechanism; incentives; prediction; CHOICE

摘要

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.