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Notes -
I'm going to strongly caution about taking any CATO publication at face value, and against using a citation that CATO provides without examining it, in this particular field. They're not the single most dishonest actor, but that's damning with faint praise. Massey 2016 has a ton of bizarre modeling choices, but the most relevant one is that another study he cited and was recent at the time of his publication took the same underlying metrics and used a similar model to separate Border Patrol funding, and came to a drastically different conclusion for the exact same time frame.
Massey's approach only works by relying on survey data to find the most dedicated illegal immigrants, being surprised when they eventually got through, and then declaring enforcement has a null effect on inflows period. Of course reductions in outflows outweigh the impact on inflows once you assume enforcement has no impact on inflows, but that's a much more serious claim, and it's one that's only barely supportable at all, and then only by conflating times where Border Patrol funding wasn't even trying to reduce border inflows with those where it did.
I can't guarantee the counterfactual world without increased border enforcement would have also connected to vastly increased inflows under Massey's metrics, but given that we have the test case of the entire Biden administration, I think it's pretty clear that's a problem with Massey's metrics, rather than the difficulty of modeling the matter.
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