Literature DB >> 33503023

How inter-state amity and animosity complement migration networks to drive refugee flows: A multi-layer network analysis, 1991-2016.

Justin Schon1, Jeffrey C Johnson2.   

Abstract

What drives the formation and evolution of the global refugee flow network over time? Refugee flows in particular are widely explained as the result of pursuits for physical security, with recent research adding geopolitical considerations for why states accept refugees. We refine these arguments and classify them into explanations of people following existing migration networks and networks of inter-state amity and animosity. We also observe that structural network interdependencies may bias models of migration flows generally and refugee flows specifically. To account for these dependencies, we use a dyadic hypothesis testing method-Multiple Regression- Quadratic Assignment Procedure (MR-QAP). We estimate MR-QAP models for each year during the 1991-2016 time period. K-means clustering analysis with visualization supported by multi-dimensional scaling allows us to identify categories of variables and years. We find support for the categorization of drivers of refugee flows into migration networks and inter-state amity and animosity. This includes key nuance that, while contiguity has maintained a positive influence on refugee flows, the magnitude of that influence has declined over time. Strategic rivalry also has a positive influence on refugee flows via dyad-level correlations and its effect on the structure of the global refugee flow network. In addition, we find clear support for the global refugee flow network shifting after the Arab Spring in 2011, and drivers of refugee flows shifting after 2012. Our findings contribute to the study of refugee flows, international migration, alliance and rivalry relationships, and the application of social network analysis to international relations.

Entities:  

Year:  2021        PMID: 33503023      PMCID: PMC7840044          DOI: 10.1371/journal.pone.0245712

Source DB:  PubMed          Journal:  PLoS One        ISSN: 1932-6203            Impact factor:   3.240


  5 in total

1.  Kantian fractionalization predicts the conflict propensity of the international system.

Authors:  Skyler J Cranmer; Elizabeth J Menninga; Peter J Mucha
Journal:  Proc Natl Acad Sci U S A       Date:  2015-09-03       Impact factor: 11.205

2.  statnet: Software Tools for the Representation, Visualization, Analysis and Simulation of Network Data.

Authors:  Mark S Handcock; David R Hunter; Carter T Butts; Steven M Goodreau; Martina Morris
Journal:  J Stat Softw       Date:  2008       Impact factor: 6.440

3.  Climate as a risk factor for armed conflict.

Authors:  Katharine J Mach; Caroline M Kraan; W Neil Adger; Halvard Buhaug; Marshall Burke; James D Fearon; Christopher B Field; Cullen S Hendrix; Jean-Francois Maystadt; John O'Loughlin; Philip Roessler; Jürgen Scheffran; Kenneth A Schultz; Nina von Uexkull
Journal:  Nature       Date:  2019-06-12       Impact factor: 49.962

4.  Sensitivity of MRQAP Tests to Collinearity and Autocorrelation Conditions.

Authors:  David Dekker; David Krackhardt; Tom A B Snijders
Journal:  Psychometrika       Date:  2007-08-07       Impact factor: 2.500

5.  Does human migration affect international trade? A complex-network perspective.

Authors:  Giorgio Fagiolo; Marina Mastrorillo
Journal:  PLoS One       Date:  2014-05-14       Impact factor: 3.240

  5 in total

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