Willful ignorance in legal contexts: A mechanism design approach - Xiaoge Dong (Bielefeld University, Center for Mathematical Economics (IMW), 2025)
We study "willful ignorance" - choosing not to learn whether a task is illegal - in a lawmaker-principal-agent game and characterize the penalty policies that implement welfare-maximizing behavior. The model delivers an implementability frontier : which equilibrium behaviors can exist and be selected by penalties. With perfect inquiry, this frontier is aligned with the welfare ordering, so the lawmaker can make the welfare-maximizing behavior both exist and be preferred by all parties. With imperfect inquiry, noise breaks that alignment and produces two failures: inquiry that is socially desirable may be infeasible at any penalty, and inquiry that is socially undesirable may persist because it cannot be switched off. We compare harm-based, compliance-based, and dual-penalty rules: harm-based rules preserve control but tightens feasibility; compliance-based rules relax feasibility but sacrifices control; dual penalty rules recover both levers subject to simple bounds. The framework yields practical guidance for calibrating penalties to harm, inquiry accuracy, and inquiry costs. It also implies that ignorance cannot serve as a shield: the absence of knowing crime in equilibrium is driven by incentives rather than morality, making non-inquiry the true strategic margin of liability design.
urn:nbn:de:0070-pub-30070577
Keywords: K14; K42; D82; D86; H23; 330; willful ignorance; ostrich instruction; law and economics; asymmetric information