Persistent Link:
http://hdl.handle.net/10150/243966
Title:
Estimating Models of Social Network Formation
Author:
Hom, Matthew Oliver
Issue Date:
May-2012
Publisher:
The University of Arizona.
Rights:
Copyright © is held by the author. Digital access to this material is made possible by the University Libraries, University of Arizona. Further transmission, reproduction or presentation (such as public display or performance) of protected items is prohibited except with permission of the author.
Abstract:
We study a dynamic model of network formation introduced by Matthew Jackson and Brian Rogers in the paper "Meeting Strangers and Friends of Friends: How Random Are Social Networks?" The model is unique, because nodes are allowed to form multiple links at the same time through random and network-based meetings. We produce MATLAB code which simulates the dynamic network formation process, and then develop likelihood free Markov Chain Monte Carlo (MCMC) techniques to estimate and extend the Jackson-Rogers model. By using simulation techniques, we are able to avoid having to use mean-field approximations to estimate the parameters of the model. In addition, we circumvent the need for explicit evaluation of the likelihood function, and are able to match more features of the model to the data.
Type:
text; Electronic Thesis
Degree Name:
B.S.B.A.
Degree Level:
bachelors
Degree Program:
Honors College; Economics
Degree Grantor:
University of Arizona

Full metadata record

DC FieldValue Language
dc.language.isoenen_US
dc.titleEstimating Models of Social Network Formationen_US
dc.creatorHom, Matthew Oliveren_US
dc.contributor.authorHom, Matthew Oliveren_US
dc.date.issued2012-05-
dc.publisherThe University of Arizona.en_US
dc.rightsCopyright © is held by the author. Digital access to this material is made possible by the University Libraries, University of Arizona. Further transmission, reproduction or presentation (such as public display or performance) of protected items is prohibited except with permission of the author.en_US
dc.description.abstractWe study a dynamic model of network formation introduced by Matthew Jackson and Brian Rogers in the paper "Meeting Strangers and Friends of Friends: How Random Are Social Networks?" The model is unique, because nodes are allowed to form multiple links at the same time through random and network-based meetings. We produce MATLAB code which simulates the dynamic network formation process, and then develop likelihood free Markov Chain Monte Carlo (MCMC) techniques to estimate and extend the Jackson-Rogers model. By using simulation techniques, we are able to avoid having to use mean-field approximations to estimate the parameters of the model. In addition, we circumvent the need for explicit evaluation of the likelihood function, and are able to match more features of the model to the data.en_US
dc.typetexten_US
dc.typeElectronic Thesisen_US
thesis.degree.nameB.S.B.A.en_US
thesis.degree.levelbachelorsen_US
thesis.degree.disciplineHonors Collegeen_US
thesis.degree.disciplineEconomicsen_US
thesis.degree.grantorUniversity of Arizonaen_US
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