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The Internal Dynamic of International Migration Systems

Authors: B Waldorf;

The Internal Dynamic of International Migration Systems

Abstract

In this paper I provide a conceptualization of international migration networks, which can be used to identify and integrate the internal components of migration systems, and formalize the relationships in an analytic model of the internal network dynamic. With the use of the operationalized model, and microlevel and macrolevel data for guestworkers in Germany during the period 1970 to 1989, we can empirically test the relative influence of internal network variables versus external forces on the attraction of immigrants over time. The empirical results suggest that—as the system matures—network variables have an increasing impact on the attraction of immigrants, while the impact of economic factors declines. The research is concluded with a series of simulations that further highlight the internal dynamic of international migration systems.

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Keywords

Transients and Migrants, Economics, Developed Countries, Research, Population, Population Dynamics, Emigration and Immigration, Models, Theoretical, Europe, Germany, Demography

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    popularity
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    influence
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
12
Average
Top 10%
Average
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