Essays in Networks and Experimental Economics
type: CreativeWork
description: The thesis focuses on networks and experimental economics. The first chapter theoretically studies network coordination games under adaptive learning agents. The second and third chapters conduct experiments on strategic interactions in networks and on network formation, respectively. The fourth chapter examines the behaviour of Generative Pre-trained Transformers (GPT) in classic game experiments. The first chapter theoretically examines how agents' behavioural traits influence long-term coordination outcomes in networks. Agents conduct experience-weighted attraction (EWA) learning, a model that captures various aspects of behavioural characteristics. I demonstrate that the range of possible long-term outcomes depends significantly on these behavioural traits, ranging from a unique outcome where all agents favour the risk-dominant option to a broader set of possibilities than that of Nash equilibria. Additionally, I show that the importance of each agent's initial preference to the network’s coordinated outcome can be summarised by the principal left eigenvector of a Jacobian matrix, which incorporates both the properties of the network structure and the distribution of individual behavioural traits. In the second chapter, coauthored with Syngjoo Choi, Sanjeev Goyal, and Frederic Moisan, we conduct an experiment to study games on networks involving strategic complements and strategic substitutes between connected individuals. Economic theory predicts that equilibrium actions are proportional to (Bonacich) centrality. Our data offer broad qualitative support for this prediction, but the relationship between actions and centrality is weaker than predicted by theory. We also identify effects of the strategic structure (strategic complements vs. strategic substitutes) and the complexity of networks on action levels. These patterns cannot be explained using standard behavioural models – such as other-regarding preferences, k-level reasoning, and quantal response equilib…
abstract: The thesis focuses on networks and experimental economics. The first chapter theoretically studies network coordination games under adaptive learning agents. The second and third chapters conduct experiments on strategic interactions in networks and on network formation, respectively. The fourth chapter examines the behaviour of Generative Pre-trained Transformers (GPT) in classic game experiments. The first chapter theoretically examines how agents' behavioural traits influence long-term coordination outcomes in networks. Agents conduct experience-weighted attraction (EWA) learning, a model that captures various aspects of behavioural characteristics. I demonstrate that the range of possible long-term outcomes depends significantly on these behavioural traits, ranging from a unique outcome where all agents favour the risk-dominant option to a broader set of possibilities than that of Nash equilibria. Additionally, I show that the importance of each agent's initial preference to the network’s coordinated outcome can be summarised by the principal left eigenvector of a Jacobian matrix, which incorporates both the properties of the network structure and the distribution of individual behavioural traits. In the second chapter, coauthored with Syngjoo Choi, Sanjeev Goyal, and Frederic Moisan, we conduct an experiment to study games on networks involving strategic complements and strategic substitutes between connected individuals. Economic theory predicts that equilibrium actions are proportional to (Bonacich) centrality. Our data offer broad qualitative support for this prediction, but the relationship between actions and centrality is weaker than predicted by theory. We also identify effects of the strategic structure (strategic complements vs. strategic substitutes) and the complexity of networks on action levels. These patterns cannot be explained using standard behavioural models – such as other-regarding preferences, k-level reasoning, and quantal response equilib…
author: Guo, Fulin
keywords: Networks, Experimental Economics
license: https://apollo8-f-pro.lib.cam.ac.uk/bitstreams/298779af-9002-4a76-bc9a-f91210257d00/download
license: http://purl.org/NET/rdflicense/allrightsreserved
date published: 2025-04-17
date modified: 2026-07-22T22:24:24Z
provider: Cambridge University
publisher: Networked Digital Library of Theses and Dissertations
type: WebPage
source organization: University of Cambridge

PropertyValue
property ID: DOI
value: 10.17863/CAM.119806