Introduction to Network Modeling Using Exponential Random Graph Models (ERGM): Theory and an Application Using R-Project

Johannes van der Pol*

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

Abstract

Exponential family random graph models (ERGM) are increasingly used in the study of social networks. These models are build to explain the global structure of a network while allowing inference on tie prediction on a micro level. The number of papers within economics is however limited. Possible applications for economics are however abundant. The aim of this document is to provide an explanation of the basic mechanics behind the models and provide a sample code (using R and the packages statnet and ERGM) to operationalize and interpret results and analyse goodness of fit. After reading this paper the reader should be able to start their own analysis.

Original languageEnglish
Pages (from-to)845-875
Number of pages31
JournalComputational Economics
Volume54
Issue number3
DOIs
Publication statusPublished - Oct 2019
Externally publishedYes

Keywords

  • Exponential random graph model (ERGM)
  • Innovation networks
  • Networks
  • p-Star (p*)
  • Statnet
  • Tie formation

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