Publication Type
Working Paper
Version
publishedVersion
Publication Date
7-2024
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
Discipline
Economic Theory
Research Areas
Economic Theory
First Page
1
Last Page
35
Citation
HU, Gaoji; LI, Jiangtao; QUAH, John K-H; and TANG, Rui.
Coarse revealed preference. (2024). 1-35.
Available at: https://ink.library.smu.edu.sg/soe_research/2767
Copyright Owner and License
Authors
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.