There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.
Abstract
<p class="first" id="P1">We analyze China’s rural-urban migration and endogenous social
network structures
using agent-based modeling. The agents from census micro data are located in their
rural origin with an empirical-estimated prior propensity to move. The population-scale
social network is a hybrid one, combining observed family ties and locations of the
origin with a parameter space calibrated from census, survey and aggregate data and
sampled using a stepwise Latin Hypercube Sampling method. At monthly intervals, some
agents migrate and these migratory acts change the social network by turning within-nonmigrant
connections to between-migrant-nonmigrant connections, turning local connections to
nonlocal connections, and adding among-migrant connections. In turn, the changing
social network structure updates migratory propensities of those well-connected nonmigrants
who become more likely to move. These two processes iterate over time. Using a core-periphery
method developed from the
<i>k</i>-core decomposition method, we identify and quantify the network structural
changes
and map these changes with the migration acceleration patterns. We conclude that network
structural changes are essential for explaining migration acceleration observed in
China during the 1995–2000 period.
</p>