Anticipating State Action: Risk Perceptions and Consumption under Immigration Enforcement

Immigration enforcement affects millions of individuals who make daily economic decisions under uncertainty about state action. Using data from 2014 to 2018, we study how households learn about and respond to enforcement risk by combining daily bank account transaction data with arrest-level records of Immigration and Customs Enforcement (ICE) operations. We document that enforcement follows predictable weekday patterns and that communities with large immigrant populations have learned them: Consumption is depressed not only on days when enforcement occurs, but also on the same weekday of other weeks—when no enforcement occurs—and rebounds in between, indicating that behavior tracks beliefs about enforcement risk, not just realized enforcement. Instrumenting for beliefs using the learnable structure of enforcement, we find that a 10 percentage point increase in perceived enforcement probability reduces Hispanic foreign-born consumption by approximately 5 percent. A structural model with Bayesian learning and pent-up demand reveals that roughly half of the immediate consumption decline is recovered through subsequent rebound; the rest is permanently foregone. Eliminating enforcement risk entirely would increase Hispanic foreign-born consumption by 3.6 percent, but when enforcement ceases, only 42 percent of these gains materialize within the first year —the remaining losses reflect learning frictions: even after state action ceases, beliefs must still adjust.