International Migration Institute

THEMIS: Migration system dynamics: evidence from global data


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Hein de Haas presents his paper 'Migration system dynamics: evidence from global data' co-authored by Mathias Czaika in Parallel session III(D) of the conference Examining Migration Dynamics: Networks and Beyond held in Oxford from 24-26 Sept 2013 This paper provides a critical assessment of migration systems theory based on an analysis of global migration patterns between 1960 and 2000. Migration systems theory pioneered by Mabogunje (1970), predicts that migration that one form of exchange between countries or places, such as trade, is likely to engender other forms of exchange such as people, in both directions. This echoes earlier arguments by Ravenstein (1885; 1889) and Lee (1966) that migration in one direction is likely to engender a counterflow in the opposite direction. In this functionalist perspective, migrant networks fulfil a vital role in the process of ‘migration diffusion' and in facilitating return migration and counter-migration (of natives of the destination country to the origin), and this can be seen as part of a wider process of social, cultural and political entangling and increasing equilibrium (decreasing skewed-ness) between ‘origins' and ‘destinations'. From a historical-structural perspective, the hypothesis that migration reciprocity increases as migration systems mature can be criticized for its ignorance of structurally embedded power inequalities, the discriminatory role of immigration restrictions and the exclusionary dimensions of ‘negative social capital' in migrant networks. However, these hypotheses have remained strikingly untested, and this paper aims to fill this gap. Based on Global Migrant Stock database, it assess the extent to which bilateral migration corridors become more balances as migration systems mature, and which factors may explain difference in such migration system dynamics (i.e., when does such increasing equilibrium occur).
[The research leading to these results is part of the DEMIG project and has received funding from the European Research Council under the European Community's Seventh Framework Programme (FP7/2007-2013) / ERC Grant Agreement 240940.]
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