Diffusion-for-Privilege: A Quid Pro Quo Approach to Mitigating Competitive Distortions in Regulatory Sandboxes

Regulatory sandboxes are designed to balance innovation incentives with regulatory risk control, yet their structural features of selective entry and differential treatment often transform admission into an institutional competitive advantage, thereby inducing non-productive rent-seeking, resource misallocation, and competitive distortions. Employing a law and economics framework based on a social welfare function, this paper integrates innovation benefits, regulatory learning, and competitive distortion losses into a unified assessment. By incorporating regulatory capacity constraints, it identifies the static and dynamic mechanisms of sandbox failure. Statically, a low entry cost–high privilege benefit pricing failure incentivizes over-application and weakens screening at the entry stage, allowing low-quality rent-seekers to pool with genuinely innovative applicants. At the same time, competitive distortion losses operate as negative externalities and remain uninternalized by firms. Dynamically, scarcity driven by capacity caps amplifies the signaling effect of admission, forcing firms into defensive competition and resulting in a dynamic welfare divergence where public benefits plateau while distortion losses accumulate. To address this, the paper proposes a Diffusion-for-Privilege mechanism. Rather than eliminating privilege, it reconstructs privilege as a conditional institutional exchange, requiring firms to produce verifiable, reusable public knowledge as a quid pro quo. By proportionally binding the diffusion obligation to the intensity of privilege, this mechanism creates a negative feedback loop that raises rent-seeking costs and dilutes first-mover advantages through knowledge spillovers, thereby mitigating competitive distortions. This paper articulates the theoretical logic for shifting sandbox governance from privilege allocation to conditional exchange, offering a framework for reconciling innovation incentives with competitive order.