Calibrating Chevron for Preemption

Autor: Dickinson, Gregory M.
Rok vydání: 2023
Předmět:
Zdroj: 63 Admin. L. Rev. 667 (2011)
Druh dokumentu: Working Paper
Popis: Now almost three decades since its seminal Chevron decision, the Supreme Court has yet to articulate how that case's doctrine of deference to agency statutory interpretations relates to one of the most compelling federalism issues of our time: regulatory preemption of state law. Should courts defer to preemptive agency interpretations under Chevron, or do preemption's federalism implications demand a less deferential approach? Commentators have provided no shortage of possible solutions, but thus far the Court has resisted all of them. This Article makes two contributions to the debate. First, through a detailed analysis of the Court's recent agency-preemption decisions, I trace its hesitancy to adopt any of the various proposed rules to its high regard for congressional intent where areas of traditional state sovereignty are at risk. Recognizing that congressional intent to delegate preemptive authority varies from case to case, the Court has hesitated to adopt an across-the-board rule. Any such rule would constrain the Court and risk mismatch with congressional intent -- a risk it accepts under Chevron generally but which it finds particularly troublesome in the delicate area of federal preemption. Second, building on this previously underappreciated factor in the Court's analysis, I suggest a novel solution of variable deference that avoids the inflexibility inherent in an across-the-board rule while providing greater predictability than the Court's current haphazard approach. The proposed rule would grant full Chevron-style deference in those cases where congressional delegative intent is most likely -- where Congress has expressly preempted some state law and the agency interpretation merely resolves preemptive scope -- while withholding deference in those cases where Congress has remained completely silent as to preemption and delegative intent is least likely.
Databáze: arXiv