Federated Learning (FL) presents a promising approach to machine learning (ML) by allowing multiple sources of data (devices or entities) to collaboratively train a shared model while keeping data decentralised. This approach mitigates privacy risks as raw data remains locally on the sources,...

Although reassignment of policy instruments among governments in many federations is a recurring event, there is no widely accepted, positive model of the phenomenon. This stands in contrast to the well established body of work on the normative theory of the efficient federal assignment. In this...