This paper proposes a new method to estimate the welfare impact of conflicts and remedy common data constraints in conflict-affected environments. The method first estimates how agents regard spatial welfare differentials by voting with their feet, using pre-conflict data. Then, it infers a lower-bound estimate for the conflict-driven welfare shock from partially observed post-conflict migration patterns. Results for the conflict in Eastern Ukraine between 2014 and 2019 show a large lower-bound welfare loss for Donetsk residents equivalent to 8–32 percent of lifetime income depending on agents’ time preference and risk aversion parameters.