The Discretionary Function Exception to the Federal Tort Claims Act: A Proposal for a Workable Analysis

Article excerpt


In 1946 Congress enacted the Federal Tort Claims Act (FTCA), which provides that the federal government can be held liable in tort "in the same manner and to the same extent as a private individual under like circumstances."1 In enacting the FTCA, Congress also provided thirteen exceptions to this baseline rule.2 The most litigated,3 and one of the broadest4 of these statutory exceptions, is the discretionary function exception.5 The Supreme Court created the current test for the applicability of the discretionary function exception in 1991 in United States v. Gaubert.6 The Gaubert Court's test created a "strong presumption" that the discretionary function exception applies where the governmental official has discretion to act and the action is "susceptible to policy analysis."7 Although the Gaubert presumption has remained the law for seventeen years, it has been consistently decried by commentators as applying the discretionary function exception too broadly and in effect swallowing the purpose of the FTCA.8 Accordingly, various commentators have proffered a number of proposals on how to refine and narrow the application of the exception.9 Similarly, several recent Ninth Circuit decisions reveal judicial attempts to chip away at the Gaubert "presumption" and thus narrow the exception's applicability.10

This Comment will discuss and compare the Ninth Circuit's recent approach to the discretionary function exception with both a stricter application of the Supreme Court's test in Gaubert and alternatives advocated by commentators. In so doing, this analysis will illustrate that in addition to applying the discretionary function exception too broadly, the Court's current approach under Gaubert also creates an undesirable incentive for governmental agencies to establish ineffective regulations in order to avoid FTCA liability. Further, this Comment shows that neither the Ninth Circuit's approach nor proposed scholarly alternatives present solutions that are both workable for courts and able to remove the incentive for agencies to regulate ineffectively.

Identifying the problems created by both the Court's current approach and other alternative approaches, this Comment proposes a novel analytical approach based upon recognition of the incentives the discretionary function exception creates for agencies in drafting policies. In applying this proposed "incentive recognition" approach, a court would undergo a two-step analysis. First, the court would determine whether the discretionary decision was made through a legislative or administrative process. If so, the exception applies; if not, the court would move to the second step to determine whether: (1) the official taking the action was affirmatively delegated the authority to use discretion in considering specific policy factors; (2) before taking the action, the official had received training such that she was aware of the policy factors she was to consider; and (3) at the time of the action, the official had access to information to make such a policy-based decision. If the government can show that these three criteria are met under the second step, there is a rebuttable presumption that the discretionary function exception applies. This proposed "incentive recognition" approach would narrow the scope of the discretionary function exception and avoid encouraging agency policymakers to enact inefficient policies and regulations to avoid liability exposure. The result is a discretionary function analysis that is more attuned to Congress's purpose in enacting the discretionary function exception and the FTCA as a whole.

Part II provides an overview of the context surrounding the passage of the FTCA, Congress's intent in enacting the discretionary function exception, and the Supreme Court decisions dealing with the exception prior to Gaubert. Part III provides a general overview of the Gaubert decision and reactions to Gaubert by scholarly commentators. …


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