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Essays in Behavioral Economics and Game Theory

Citation

Fong, Meng-Jhang (2024) Essays in Behavioral Economics and Game Theory. Dissertation (Ph.D.), California Institute of Technology. doi:10.7907/5xh7-yw15. https://resolver.caltech.edu/CaltechTHESIS:09292023-062110859

Abstract

This thesis consists of three papers. Chapter 1 conducts experimental research on individual bounded rationality in games, Chapter 2 introduces a novel equilibrium solution concept in behavioral game theory, and Chapter 3 investigates confirmation bias within the framework of game theory.

In Chapter 1 (joint with Wei James Chen and Po-Hsuan Lin), we investigate individual strategic reasoning depths by matching human subjects with fully rational computer players in a lab, allowing for the isolation of limited reasoning ability from beliefs about opponent players and social preferences. Our findings reveal that when matched with robots, subjects demonstrate higher stability in their strategic thinking depths across games, in contrast to when matched with humans.

In Chapter 2 (joint with Po-Hsuan Lin and Thomas R. Palfrey), we investigate how players’ misunderstanding about the relationship between opponents’ private information and strategies influence their equilibrium behavior in dynamic environments. This theoretical study introduces a framework that extends the analysis of cursed equilibrium from the strategic form to multi-stage games and applies it to various applications in economics and political science.

In Chapter 3, I employ a game-theoretic framework to model how decision makers strategically interpret signals, particularly when they face a utility loss from holding beliefs that differ from their partners. The study reveals that the emergence of confirmation bias is positively associated with the strength of prior beliefs about a state, while the impact of signal accuracy remains ambiguous.

Item Type:Thesis (Dissertation (Ph.D.))
Subject Keywords:Ring Game, Guessing Game, Level-k, Higher-Order Rationality, Multi-Stage Games, Private Information, Cursed Equilibrium, Learning, Conformity, Confirmation Bias
Degree Grantor:California Institute of Technology
Division:Humanities and Social Sciences
Major Option:Social Science
Awards:John O. Ledyard Prize for Graduate Research in Social Science, 2020
Thesis Availability:Public (worldwide access)
Research Advisor(s):
  • Agranov, Marina
Thesis Committee:
  • Palfrey, Thomas R. (chair)
  • Pomatto, Luciano
  • Sprenger, Charles David
  • Agranov, Marina
Defense Date:27 September 2023
Funders:
Funding AgencyGrant Number
Ministry of Science and Technology of TaiwanMOST 109-2636-H-008-002
National Science FoundationSES-0617820
Gordon and Betty Moore Foundation1158
Record Number:CaltechTHESIS:09292023-062110859
Persistent URL:https://resolver.caltech.edu/CaltechTHESIS:09292023-062110859
DOI:10.7907/5xh7-yw15
Related URLs:
URLURL TypeDescription
https://arxiv.org/abs/2309.07427arXivArticle adapted for Chapter 1
https://arxiv.org/abs/2301.11971arXivArticle adapted for Chapter 2
ORCID:
AuthorORCID
Fong, Meng-Jhang0009-0008-8832-3985
Default Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:16198
Collection:CaltechTHESIS
Deposited By: Meng Jhang Fong
Deposited On:02 Oct 2023 21:48
Last Modified:02 Oct 2023 21:48

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