Analyzing the Homeland Security of the U.S.‐Mexico Border
Analyzing the Homeland Security of the U.S.‐Mexico Border
复制标题
分析美墨边境的国土安全
作者：
L. Wein;Yifan Liu;Arik Motskin
我们在国土安全和移民的交叉点开发了一个数学优化模型，该模型选择各种移民执法决策变量，以最大限度地减少恐怖分子通过美墨边境成功进入美国的概率。其中包括一个离散选择模型，用于计算潜在的外国人越境者试图越过美墨边境的概率，包括成功的可能性和美国非法工人的工资，一个空间模型，用于计算逮捕概率作为越境者数量的函数，边境巡逻人员的数量，以及边境上的监视技术数量，一个拘留模式，确定被逮捕的外国人将被拘留和驱逐的概率，作为拘留床位数量的函数，以及一个平衡工作供求并纳入工地执法影响的非法工资均衡模式。我们的主要结果是，拘留床位是当前系统的瓶颈（即使在最近通过加快搬迁大幅减少拘留时间之后），如果不大幅增加拘留能力，增加边境巡逻人员或监视技术将不会带来任何改善。我们的模型还预测，监控技术比边境巡逻人员更具成本效益，而边境巡逻人员又比工地检查员更具成本效益，但由于难以从现有数据预测人类行为，这些结果并不稳健。总的来说，恐怖分子成功进入美国的概率非常高，要大幅降低这种概率，成本非常高，也非常困难。我们还研究了另一个目标函数，即最小化非法外国人穿越美墨边境的流动，并获得了定性相似的结果。
We develop a mathematical optimization model at the intersection of homeland security and immigration, that chooses various immigration enforcement decision variables to minimize the probability that a terrorist can successfully enter the United States across the U.S.‐Mexico border. Included are a discrete choice model for the probability that a potential alien crosser will attempt to cross the U.S.‐Mexico border in terms of the likelihood of success and the U.S. wage for illegal workers, a spatial model that calculates the apprehension probability as a function of the number of crossers, the number of border patrol agents, and the amount of surveillance technology on the border, a queueing model that determines the probability that an apprehended alien will be detained and removed as a function of the number of detention beds, and an equilibrium model for the illegal wage that balances the supply and demand for work and incorporates the impact of worksite enforcement. Our main result is that detention beds are the current system bottleneck (even after the large reduction in detention residence times recently achieved by expedited removal), and increases in border patrol staffing or surveillance technology would not provide any improvements without a large increase in detention capacity. Our model also predicts that surveillance technology is more cost effective than border patrol agents, which in turn are more cost effective than worksite inspectors, but these results are not robust due to the difficulty of predicting human behavior from existing data. Overall, the probability that a terrorist can successfully enter the United States is very high, and it would be extremely costly and difficult to significantly reduce it. We also investigate the alternative objective function of minimizing the flow of illegal aliens across the U.S.‐Mexico border, and obtain qualitatively similar results.