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
textElectronic Thesis
Degree Name
B.S.B.A.Degree Level
bachelorsDegree Program
Honors CollegeEconomics