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A Systematic Test of the Independence Axiom Near Certainty

Jain, Ritesh and Nielsen, Kirby (2020) A Systematic Test of the Independence Axiom Near Certainty. . (Unpublished) https://resolver.caltech.edu/CaltechAUTHORS:20201210-101529259

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Abstract

A large literature has documented violations of expected utility consistent with a preference for certainty (the “certainty effect”). We design a laboratory experiment to investigate the role of the certainty effect in explaining violations of the independence axiom. We use lotteries spanning over the entire probability simplex to detect violations systematically. We find that violations of independence consistent with the reverse certainty effect are much more common than violations consistent with the certainty effect. Results hold as we test robustness along two dimensions: varying the mixing lottery and moving slightly away from certainty.


Item Type:Report or Paper (Working Paper)
Related URLs:
URLURL TypeDescription
https://ideas.repec.org/p/sin/wpaper/20-a001.htmlOrganizationWorking Paper
Additional Information:We want to thank Yaron Azrieli, Doug Bernheim, Anujit Chakraborty, Paul J. Healy, Collin Raymond, John Rehbeck, Colin Sullivan, and the participants of the experimental reading group at the Ohio State University for providing helpful feedback on this project. All errors remain our own. Research support was provided by the Decision Science Collaborative of the Ohio State University. This study was approved by the Institutional Review Boards at Academia Sinica and Stanford University.
Subject Keywords:independence axiom; expected utility theory; certainty effect; Allais Paradox
Other Numbering System:
Other Numbering System NameOther Numbering System ID
Institute of Economics, Academia Sinica (IEAS)20-A001
Classification Code:JEL: C79, D82
Record Number:CaltechAUTHORS:20201210-101529259
Persistent URL:https://resolver.caltech.edu/CaltechAUTHORS:20201210-101529259
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:107009
Collection:CaltechAUTHORS
Deposited By: Tony Diaz
Deposited On:10 Dec 2020 19:35
Last Modified:10 Dec 2020 19:35

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