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A STRUCTURAL ECONOMETRIC ANALYSIS OF
NETWORK AND SOCIAL INTERACTION MODELS
by
Shuyang Sheng
A Dissertation Presented to the
FACULTY OF THE USC GRADUATE SCHOOL
UNIVERSITY OF SOUTHERN CALIFORNIA
In Partial Ful llment of the
Requirements for the Degree
DOCTOR OF PHILOSOPHY
(ECONOMICS)
August 2013
Copyright 2013 Shuyang Sheng
Object Description
| Title | A structural econometric analysis of network and social interaction models |
| Author | Sheng, Shuyang |
| Author email | ssheng@usc.edu;shengshuyang@gmail.com |
| Degree | Doctor of Philosophy |
| Document type | Dissertation |
| Degree program | Economics |
| School | College of Letters, Arts And Sciences |
| Date defended/completed | 2013-04-25 |
| Date submitted | 2013-08-07 |
| Date approved | 2013-08-07 |
| Restricted until | 2013-08-07 |
| Date published | 2013-08-07 |
| Advisor (committee chair) | Ridder, Geert |
| Advisor (committee member) |
Strauss, John A. Moon, Hyungsik Roger Yang, Sha |
| Abstract | Social and economic networks play an important role in shaping individuals' behaviors. In this dissertation, we provide a structural econometric analysis of network-related models, including network formation models and social interaction models. In the analysis of network formation models, the goal is to identify and estimate the underlying utility parameters using observed data on network structure, i.e., who is linked with whom. We consider a game-theoretic model of network formation and use pairwise stability, introduced by Jackson and Wolinsky (1996) as the equilibrium condition. The parameters are not point identified when there are only multiple equilibria. We leave the equilibrium selection completely unrestricted and use partial identification. Following Ciliberto and Tamer (2009), we derive bounds on the probability of observing a network. These bounds, however, are computationally infeasible if networks are large. To overcome this computational problem, we propose a novel method based on subnetworks. A subnetwork is the restriction of a network to a subset of the individuals. We derive bounds on the probability of observing a subnetwork, considering only the pairwise stability of the subnetwork rather than the entire network. Under mild assumptions, these subnetwork bounds are computationally feasible as long as we consider only small subnetworks. ❧ As for the social interaction models, we focus on a special case where individuals interact because they can learn from their neighbors about a new technology. We follow the literature on nonparametric identification and provide conditions under which the structural functions and average learning effects in this model can be nonparametrically identified. |
| Keyword | network formation; pairwise stability; multiple equilibria; partial identification; subnetworks; simulation; social interactions; Bayesian learning; nonparametric identification; nonadditive index models |
| Language | English |
| Format (imt) | application/pdf |
| Part of collection | University of Southern California dissertations and theses |
| Publisher (of the original version) | University of Southern California |
| Place of publication (of the original version) | Los Angeles, California |
| Publisher (of the digital version) | University of Southern California. Libraries |
| Provenance | Electronically uploaded by the author |
| Type | texts |
| Legacy record ID | usctheses-m |
| Contributing entity | University of Southern California |
| Rights | Sheng, Shuyang |
| Physical access | The author retains rights to his/her dissertation, thesis or other graduate work according to U.S. copyright law. Electronic access is being provided by the USC Libraries in agreement with the author, as the original true and official version of the work, but does not grant the reader permission to use the work if the desired use is covered by copyright. It is the author, as rights holder, who must provide use permission if such use is covered by copyright. The original signature page accompanying the original submission of the work to the USC Libraries is retained by the USC Libraries and a copy of it may be obtained by authorized requesters contacting the repository e-mail address given. |
| Repository name | University of Southern California Digital Library |
| Repository address | USC Digital Library, University of Southern California, University Park Campus MC 7002, 106 University Village, Los Angeles, California 90089-7002, USA |
| Repository email | cisadmin@lib.usc.edu |
| Filename | etd-ShengShuya-1990.pdf |
| Archival file | uscthesesreloadpub_Volume7/etd-ShengShuya-1990.pdf |
Description
| Title | Page 1 |
| Contributing entity | University of Southern California |
| Repository email | cisadmin@lib.usc.edu |
| Full text | A STRUCTURAL ECONOMETRIC ANALYSIS OF NETWORK AND SOCIAL INTERACTION MODELS by Shuyang Sheng A Dissertation Presented to the FACULTY OF THE USC GRADUATE SCHOOL UNIVERSITY OF SOUTHERN CALIFORNIA In Partial Ful llment of the Requirements for the Degree DOCTOR OF PHILOSOPHY (ECONOMICS) August 2013 Copyright 2013 Shuyang Sheng |
