This paper provides the first systematic analysis of migration to, within, and from Libya. The data used in the analysis are from the Displacement Tracking Matrix data set of the International Organization for Migration. The analysis uses this unique source of data, combining several techniques to analyze various dimensions of migration in Libya. First, the paper provides a detailed description of the demographic characteristics and national composition of the migrant populations in Libya. Next, it discusses the determinants of migration flow within Libya. The findings show that migration in Libya can be characterized as forced migration, because conflict intensity is the main determinant of the decision to relocate across provinces. Finally, the paper describes the direction, composition, and evolution of international migration flows passing through Libya and identifies the mechanisms of location selection by migrants within Libya by identifying hotspots and cluster provinces.
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This paper delves into the determinants of global migration flows by applying a social network methodology. In order to explicitly address the multidimensional aspects of this phenomenon, I employ data on bilateral flows between 169 countries from 1990 through 2010 in combination with information about language and colonial history of each population, and bilateral distance between countries. With respect to traditional approaches, the underlying mechanism characterizing the international migration network (IMN) is described using a data driven approach which takes into account both bilateral and multilateral resistances to migration. To enhance the understanding of the relationships occurring between countries, I analyze contextual effects at different granularity levels and use graph theory to explore the topological properties of the IMN. Overall, complementing existing literature, the results suggest that the IMN is characterized by a strongly persistent hierarchical architecture regardless the spatial granularity of the data. Few countries, both at the local and at the global level, control the whole connectivity of the network, with a prevalence of star-like structures. In terms of network analysis, this means that human international migration patterns can be described by a modular structure displaying high geographical clustering, where the preferential attachment mechanism is driven by cultural homophily (i.e. same language or colonial past) and economic disassortativity (e.g. migration, conditional on distance, take place between countries which differ in terms of GDP). The persistence of this topological structure over time is consistent with a well-established finding in literature, that is the presence of a self-reinforcing process on the intensive margin of the IMN. In conclusion, this paper demonstrates that the level of embeddedness of one country in the IMN is a powerful source of information to improve and further unfold the dynamics underlying migratory processes and its multilateral resistances. With this respect, SNA provides an appropriate theoretical framework of analysis that can be used to extend this study in many innovative ways.
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This paper delves into the effect of social networks on the economic attainment of immigrants. Using data from a survey on personal networks and daily activity spaces of Sri Lankan immigrants in Milan, Italy, our results confirm that access to distant and diverse social circles bear distinct positive effects on immigrants’ socioeconomic attainment. However, the highest benefits in terms of wage income are associated with either high levels of social network integration in the Italian society, or high levels of network segregation within the Sri Lankan community. Moving from having friends which are fully segregated in the Sri Lankan community to friends relatively more integrated is initially costly and becomes more beneficial only after a threshold is reached. This gives evidence to a rational for the persistence of ethnic niches in a decentralized local labour market.
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