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Introduction to network modeling using Exponential Random Graph models (ERGM)

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  • Johannes van Der Pol

    (GREThA - Groupe de Recherche en Economie Théorique et Appliquée - UB - Université de Bordeaux - CNRS - Centre National de la Recherche Scientifique)

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 paper within economics is however limited. 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 analyze goodness of fit. After reading this paper the reader should be able to launch their own analysis.

Suggested Citation

  • Johannes van Der Pol, 2017. "Introduction to network modeling using Exponential Random Graph models (ERGM)," Working Papers hal-01284994, HAL.
    • Handle: RePEc:hal:wpaper:hal-01284994
    Note: View the original document on HAL open archive server: https://hal.science/hal-01284994v2
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    References listed on IDEAS

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    Keywords

    ERGM; Social and economic networks; Exponential Random Graph Model; P-star; Innovation networks;
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