Social network theory (SNT) holds that, once a critical number of migrants have settled in a destination, migration adopts a self-perpetuating character whereby movement tends to follow the `beaten track.' At this point, the migratory flow between two countries will no longer be strongly correlated to macro-level variables such as immigration policy. This implies that migrants from a given origin will continue to concentrate in the same destination even if other destinations offer easier possibilities for entry. The concentration of immigrants from one origin, predicted by SNT, is widely documented. However, we also see evidence of migrant flows reorienting away from locations where co-ethnics have historically settled. I develop an abstract, theory-driven agent-based model to help reconcile the existence of two apparently mutually exclusive outcomes under the framework of SNT. This model, which considers network-driven labor migration from Mexico to the USA from 1990 to 2013, demonstrates that network theory can explain the emergence of both path dependent migration systems as well as systems that shift in reaction to immigration policy, when return migration is taken into account. Return, a severely understudied aspect of migration, can help migration flows adapt to changes in immigration policy and follow the path of least resistance towards a new destination.

中文翻译：

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路径依赖与适应：政策对移民系统的影响

社会网络理论（SNT）认为，一旦有一定数量的移民定居在某个目的地，移民便会表现出自我永存的性格，从而使运动趋向于遵循“人迹罕至的轨道”。在这一点上，两国之间的移民流动将不再与诸如移民政策之类的宏观变量紧密相关。这意味着，即使其他目的地提供了更容易入境的机会，来自给定来源的移民也将继续集中在同一目的地。SNT预测，来自一个来源的移民的集中度已被广泛记录。但是，我们还看到有证据表明，移民潮从同族定居的地方重新定向。我写了一个摘要，理论驱动的基于主体的模型，可帮助协调SNT框架下两个表面上互斥的结果的存在。该模型考虑了1990年至2013年从墨西哥到美国的网络驱动的劳动力迁移，证明了网络理论既可以解释路径依赖的迁移系统的出现，也可以解释当返乡迁移时对移民政策做出反应的系统的迁移。考虑在内。返乡是人们对移民问题的严重研究，它可以帮助移民适应移民政策的变化，并沿着阻力最小的途径前往新目的地。证明了网络理论可以解释路径依赖的移民系统的出现，以及考虑到回程移民而对移民政策做出反应的系统的变化。返乡是人们对移民问题的严重研究，它可以帮助移民适应移民政策的变化，并沿着阻力最小的途径前往新目的地。证明了网络理论可以解释路径依赖的移民系统的出现，以及考虑到回程移民而对移民政策做出反应的系统的变化。返乡是严重被忽视的移民问题，它可以帮助移民流适应移民政策的变化，并沿着对新目的地的阻力最小的道路走。