and Lee (2008) and Higdon and colleagues (2008), one can use Bayesian inferences to set credible regions on model outputs.

The advantages of agent-based models for inferring immigration flow are that the method is relatively easy to program, relatively easy to validate, and allows decision makers to flexibly explore “what if” scenarios. The disadvantages are that the methods for formal statistical inference are still under development and that building and fitting such a model requires expertise that DHS has yet to acquire. As discussed in Chapter 5, DHS would be able to cheaply and effectively “outsource” this analysis to the scholarly community if it were to make the administrative data from its enforcement database more widely available.

In the context of immigration modeling, the Secure Border Initiative (MITRE Corporation, 2008) attempted to produce a simulation model for cross-border traffic that is essentially an agent-based model. That model has been criticized for making ad hoc assumptions, and to the best of our knowledge it has not been retrospectively validated against historical data (Chang et al., 2012). Nonetheless, if DHS decides to pursue an agent-based model as a strategy for producing flow estimates, the Secure Border Initiative model is a natural starting point.


Existing surveys and administrative data sources do not suffice to estimate some important aspects of the migration process; two fundamental data gaps include the proportion of undocumented migrants who cross the border undetected and the proportion of migrants who were successfully deterred after one or more apprehensions. The use of modeling approaches informed by survey data and administrative data is therefore necessary for estimating the flows of unauthorized migrants across the U.S.–Mexico border. Any modeling approach, and the assumptions underlying it, will need to keep track of mechanisms of change and be continually validated against historical trends and data. Since all modeling approaches will have their limitations, there is also much that could be learned by comparing estimates from multiple methods.

Without access to DHS administrative data, the panel was unable to assess the strengths and weaknesses of each modeling approach in the context of estimating the components of illegal migration flows along the U.S.–Mexico border. If the panel had had access to these data, it might have been able to make some basic comparisons between the different approaches and gain some insight into the accuracy of the information obtained from surveys. As a specific example, consider the analysis carried out using EMIF-N data in Chapter 5. The panel found that several probability models appeared to fit the re-apprehension estimates from EMIF-N quite

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