Designing Dynamic Reassignment Mechanisms: Evidence from GP Allocation

Many centralized assignment systems seek to not only provide good matches for participants’ current needs, but also to accommodate changes in preferences and circumstances. We study the problem of designing a dynamic reassignment mechanism in the context of Norway’s system for allocating patients to general practitioners (GPs). We provide direct evidence of misallocation under the current system––patients sitting on waitlists for each others’ GPs, but who cannot trade––and analyze an alternative mechanism that adapts the Top-Trading Cycles (TTC) algorithm to a dynamic environment. In contrast to the static case, dynamic TTC may leave some agents worse off relative to a status quo where trades are not permitted, introducing novel concerns about fairness. We empirically evaluate how this mechanism would perform by estimating a structural model of switching behavior and GP choice. While introducing TTC would on average reduce waiting times and increase patient welfare––with especially large benefits for female patients and recent movers––patients endowed with undesirable GPs would be harmed. Adjustments to the priority system can avoid harming this group while preserving most of the gains from TTC.