Literature DB >> 27247395

Interlocking directorates in Irish companies using a latent space model for bipartite networks.

Nial Friel1, Riccardo Rastelli1, Jason Wyse2, Adrian E Raftery3.   

Abstract

We analyze the temporal bipartite network of the leading Irish companies and their directors from 2003 to 2013, encompassing the end of the Celtic Tiger boom and the ensuing financial crisis in 2008. We focus on the evolution of company interlocks, whereby a company director simultaneously sits on two or more boards. We develop a statistical model for this dataset by embedding the positions of companies and directors in a latent space. The temporal evolution of the network is modeled through three levels of Markovian dependence: one on the model parameters, one on the companies' latent positions, and one on the edges themselves. The model is estimated using Bayesian inference. Our analysis reveals that the level of interlocking, as measured by a contraction of the latent space, increased before and during the crisis, reaching a peak in 2009, and has generally stabilized since then.

Entities:  

Keywords:  Bayesian estimation; Ireland; Markov chain Monte Carlo; corporate governance; social network analysis

Mesh:

Year:  2016        PMID: 27247395      PMCID: PMC4914205          DOI: 10.1073/pnas.1606295113

Source DB:  PubMed          Journal:  Proc Natl Acad Sci U S A        ISSN: 0027-8424            Impact factor:   11.205


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4.  Modelling the evolution of a bi-partite network Peer referral in interlocking directorates.

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  5 in total

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Journal:  J Am Stat Assoc       Date:  2018-01-26       Impact factor: 5.033

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Review 5.  Recent Integrations of Latent Variable Network Modeling With Psychometric Models.

Authors:  Selena Wang
Journal:  Front Psychol       Date:  2021-12-09
  5 in total

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