Coarse revealed preference

Gaoji Hu (), Jiangtao Li (), John K.-H. Quah () and Rui Tang ()
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Gaoji Hu: School of Economics and Dishui Lake Advanced Finance Institute, Shanghai University of Finance and Economics
Jiangtao Li: School of Economics, Singapore Management University
John K.-H. Quah: Department of Economics, National University of Singapore
Rui Tang: Department of Economics, The Hong Kong University of Science and Technology

Theoretical Economics, Forthcoming

Abstract: 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.

Keywords: Coarse dataset; rationalization; revealed preference; Afriat's theorem; perturbation index; price misperception index (search for similar items in EconPapers)
JEL-codes: C6 D0 D1 (search for similar items in EconPapers)
Date: 2025-12-16
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