Adaptive Regulatory Impact Assessment: Beyond the Foresight-Hindsight Divide

Impact Assessment (IA) has evolved to become a multidisciplinary tool aimed at increasing political accountability and promoting better policy decisions. Among other IA tools, Regulatory Impact Assessment (RIA) has gained prominence with its strategic and broad scope (covering agency regulations and all kinds of significant impacts) and structured method. Growing consensus on evidence-based policies as a requirement of good governance and the Better Regulation agenda have also helped propel the diffusion of RIA. A recent trend in RIA systems has been the adoption of an ex post RIA counterpart to the traditional ex ante RIA. In other words, RIA has started to look back. This dissertation examines this recent evolutionary step of IA and argues that while adopting the ex post complement is a step in the right direction, it is ultimately a step that falls short of truly fulfilling RIA normative goals. The foresighthindsight divide between ex ante and ex post RIA exposes the system to the risk of missing the correct timing for policy adjustments, therefore failing to avoid unwanted welfare losses. Also, policy learning is limited. To overcome these problems, the dissertation proposes the idea of Adaptive Regulatory Impact Assessment (ARIA). The dissertation examines the benefits of ARIA, the limitations on ARIA posed by the fragmentation of IA tools, and the literature on the quality of ex ante and ex post RIA. Furthermore, it provides an overview of the techniques and tools that can make ARIA both feasible and promising