Regulatory Impact Modeling for Emerging Digital Technologies

Abstract

Regulatory impact modelling (RIM) for emerging digital technologies requires methodologies that can quantify the costs and benefits of regulation across multiple dimensions -- compliance burden, innovation effects, consumer welfare, market structure, and societal outcomes -- under conditions of deep uncertainty about technology trajectories, market responses, and second-order social effects. This paper proposes the Regulatory Impact Modelling Framework for Digital Technologies (RIMFDT), a systematic methodology combining econometric estimation, computational simulation, and expert elicitation to quantify regulatory impacts across four emerging digital technology regulation domains: generative AI (EU AI Act), data governance (EU Data Act), digital platform competition (DMA), and cybersecurity (NIS2). RIMFDT extends and refines CRISF (Horvath, 2025) by integrating empirical econometric calibration with simulation dynamics and providing a structured impact decomposition methodology. Key results: EU AI Act produces net positive welfare impact (EUR +8.4 billion/year EU-27 by 2030) driven by trust and safety benefits exceeding compliance costs; EU Data Act consumer benefits exceed industry costs by 2.4x at current implementation parameters; DMA full compliance reduces consumer welfare loss from digital platform market power by EUR 12.4 billion/year. The framework provides impact modelling methodology and empirical calibration for digital technology regulators.