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Chapman University

Motive Selection and Lying Aversion in a Coin Flip Game: An Experimental Approach to Preference Switching

Abstract

dc:description.abstract

<p>This paper studies how people behave when honesty, fairness, equality, and self-interest intersect. In a series of coin-flip reporting tasks, participants can misreport a privately observed outcome to change payoffs for themselves and an anonymous partner. Building on prior work on lying aversion and lying-dictator games, the test varies to elicit the discrepancy between lying aversion and equality. Allocations to each player’s material payoff, introduces of equal or unequal treatment and involved and indifferent treatments. Using a simple nonparametric mixture model, there is evidence of cheating in all four tasks, with implied cheating rates of roughly 13 to 25 percent, including in conditions where lying does not increase one’s own earnings but can benefit the partner or alter relative standing. Differences in implied cheating rates across most tasks are consistent with the idea that willingness to lie is sensitive to the structure of incentives, but they do not provide conclusive evidence of systematic “preference switching” between honesty and equality.</p>

Degree

thesis:*
Name thesis:degree_name
Master of Science (MS)
Level thesis:degree_level
Thesis
Discipline thesis:degree_discipline
Behavioral and Computational Economics
Year dc:date.available
2026

Author and committee

dc:creator, dc:contributor.*
Author dc:creator
  • Lin, Morgan S
Contributors dc:contributor
  • Steven Rassenti
  • David Porter

Subjects

dc:subject × 7

Identifiers

dc:identifier.*
OAI identifier oai:identifier
oai:digitalcommons.chapman.edu:behavioral_and_computational_economics_theses-1008

Chain of custody

source
Harvested from
Chapman University
Base URL
digitalcommons.chapman.edu/do/oai/
Last updated
2026-07-24
Source record
OAI-PMH GetRecord
citation

Lin, Morgan S. Motive Selection and Lying Aversion in a Coin Flip Game: An Experimental Approach to Preference Switching. Thesis thesis, 2026. https://digitalcommons.chapman.edu/behavioral_and_computational_economics_theses/9