The First-Exposure Effect in Social Programs: Evidence Against a Welfare Trap

We develop a framework for estimating a first-exposure effect (FEE) in a social program, defined as the difference between observed use and the counterfactual use absent any learning from first exposure. In administrative data, those never exposed are unobserved, so the counterfactual distribution must be recovered structurally. Under (i) no state dependence in the counterfactual and (ii) behavioural change only at first use, the observed distribution is a one-altered version of the counterfactual. We derive FEE and marginal FEEs for common count processes, provide an R package fee for estimation, and illustrate with Ontario social assistance data. Results show a 12% reduction in unemployment spells due to first exposure, rejecting the welfare trap hypothesis.