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

Copyright Owner and License

Authors

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