经鸿之粟 | 虎高计常任副教授合作论文在经济学国际一类期刊在线发表

We propose a novel concept of rationalization, called coarse rationalization, tailored for the analysis of datasets where an agent’s choices are imperfectly observed. We characterize those datasets which are rationalizable in this sense and present an efficient algorithm to verify the characterizing condition. We then demonstrate how our results can be applied through a duality approach to test the rationalizability of datasets with perfectly observed choices but imprecisely observed linear budget sets. For datasets that consist of both perfectly observed feasible sets and choices but are inconsistent with perfect rationality, our results could be used to measure the extent to which choices or prices have to be perturbed to recover rationality.

虎高计，上海财经大学经济学院常任副教授。研究领域为匹配理论、机制设计、信息设计、显示偏好理论等。研究成果发表于American Economic Journal: Microeconomics、Games and Economic Behavior、International Economic Review、Theoretical Economics 等学术期刊。科研项目包括国家自然科学基金青年项目、面上项目、重大项目(参与），以及上海市曙光计划、浦江人才计划等。学术兼职包括Journal of Mathematical Economics副主编等。