Thin rationality review.

• Author: Gersen, Jacob
• Position: II. Prescription: Thin Rationality Review A. Negative Prescriptions d. "State Farm with Teeth" through Conclusion: The Baltimore Gas Era, with footnotes and appendices, p. 1383-1412

4. "State Farm with Teeth"

   Finally, there is an emergent idea in the commentary that tries to link a more intensive version of arbitrariness review with the performance of cost-benefit analysis by agencies. Professor Catherine Sharkey's proposed "State Farm with Teeth" argues for a more intensive elevated standard for judicial review of some independent agency decisions, particularly cost-benefit analysis not reviewed by OIRA. (147) The core idea is that courts should review agency decisions backed by high-quality cost-benefit analysis less intensively than they otherwise would. Judicial practice along these lines would not expressly require cost-benefit analysis, but would do so indirectly.

   To the extent that there is an implicit claim in Sharkey's proposal that courts should adopt a thin version of rationality review for agency decisions that have been subject to OIRA review, we certainly agree. But to the extent that she advocates a thicker version of review for agencies that have not engaged in rigorous cost-benefit analysis, the idea is neither an accurate description of existing judicial practice, nor in our view a desirable shift in doctrine. The proposal ignores the fundamental feature of agency decisionmaking under conditions of severe uncertainty. To illustrate, agencies addressing health risks from pollution rarely know the exact shape of the dose-response curve at low levels of exposure. (148) The challenge is to utilize other available information, for example effects of exposure at higher levels or effects of exposure on animals, to make a reasoned inference about the likely effects at low levels of exposure. (149) So too agencies regulating financial markets will rarely be able to precisely state the costs or benefits of a proposed rule because the actual effect will depend on a complex set of interdependent decisions by market participants. The problem to be solved is a lack of certainty about those effects. To require an agency to justify its decision using the exact information that is inevitably lacking is the very opposite of rationality. It is akin to requiring that all requests to learn an unknown foreign language be made in that language, or that all research be funded only if the results are already known.

   But we have now moved to the question of agency decisionmaking under uncertainty; let us take up that topic directly.

   3. Connecting Facts and Choices: Uncertainty, Rationality, and Arbitrariness

      In a frequently quoted passage, State Farm announced that an agency must "examine the relevant data and articulate a satisfactory explanation for its action including a 'rational connection between the facts found and the choice made.'" (150) This has become a basic principle of rationality review: agencies must explain their choices, in light of the facts. We will suggest, however, that there is much less to this requirement than meets the eye--both as a matter of the theory of rational decisionmaking, and under current law. The obligation to explain choices, given the facts, is far less demanding than lower courts sometimes assume--although the Court itself has usually understood the problem and followed the correct approach.

      The critical problem is that facts sometimes underdetermine agency choices. It is not necessarily the case, and perhaps not even usually the case, that given some state of the world, the agency will always have (let alone be able to give) reasons for choosing one policy over all competitors, or over any given alternative. Rather, it can be the case, and may often be the case, that agencies will face a situation in which (1) the agency is obligated to choose; (2) there exists more than one policy that can be justified, given the best evidence about the state of the world; and yet, (3) there is no decisive reason to choose one policy over another.

      Cases of this sort arise under genuine uncertainty, so-called Knightian uncertainty. (151) Knightian uncertainty arises when the decisionmaker has no respectable epistemic basis for attaching probabilities to possible outcomes. This is not to say that subjective probabilities cannot be elicited and then attached, by brute force, but those probabilities lack any credible epistemic warrant or foundation.

      From the fact that it is always possible to elicit these subjective probabilities, we should not conclude that one ought rationally to act upon them. One could certainly elicit from a political scientist the subjective probability that he attaches to the prediction that Norway in the year 3000 will be a democracy rather than a dictatorship, but would anyone even contemplate acting on the basis of this numerical magnitude? (152) Furthermore, it has been shown empirically that subjective probabilities are highly sensitive to the method used to elicit them, implying that they are artifactual. (153)

      Absent probabilities, what is the rational decisionmaker to do? The main issue is whether the decisionmaker should adopt a more or less optimistic or pessimistic approach. At the extreme of pessimism is "maximin," which indicates the choice with the best worst-case outcome; at the extreme of optimism is "maximax," which indicates the choice with the best best-case outcome; and indeed any weighted average of these extremes is also possible. (154) Importantly, any of these approaches is equally rational, given the circumstances; there is no general way to arbitrate among them, no further requirement of rationality that would knock out all but one approach.

      Sometimes, of course, law will impose further constraints, even if the theory of rational decisionmaking does not. Particular regulatory statutes might command a highly cautious or pessimistic ("precautionary") approach. But there is no general requirement to that effect; the law rejects any general preference for maximin over maximax. The Supreme Court has consistently overturned judges who attempt to impose on agencies a mandate to make "conservative" or "worst case" assumptions under uncertainty. (155) There is thus an element of irreducible discretion in agency choice under genuine uncertainty. The facts underdetermine the choice, and as far as the law and the theory of rational choice goes, the agency can simply choose how pessimistic or optimistic to be.

      In an important set of cases, then, agencies face a dilemma: although the agency does best by choosing one of the available options from within the feasible set, any choice of a particular option is necessarily arbitrary. The agency thus faces a "rationally arbitrary decision" (156): it is rational to act arbitrarily, in the sense of making a policy choice that cannot be justified relative to other available choices, but can be justified by the need to make some choice or other from within the feasible set. Rationality and arbitrariness are usually cast as strict antonyms, but this is a confusion. Agencies acting under uncertainty may have perfectly good second-order reasons to make one choice or another, within the feasible set, even if they lack any first-order reason to choose one option over another within the feasible set. In cases of this sort, agencies act based on reasons, even if they have no first-order reasons for their choices; they act arbitrarily, but have perfectly good reason to do so.

      As a recent illustration, the Secretary of the Interior was required by law to decide whether to list the southwestern flat-tailed horned lizard as a threatened species or not, yet there was no reliable data on the number of extant lizards; (157) "the administrative record did not support a finding that the lizard population was viable or nonviable." (158) In such circumstances, the agency has excellent second-order reasons--here, compliance with a legal mandate--to make a decision one way or another, even though no decision can be fully justified.

      Courts should recognize the existence of this sort of dilemma. The hallmark of such cases is mirror-image reversibility, the agency's choice of A over B is arbitrary, in the sense that the agency can give no valid first-order reason for the choice, but it is equally true that the agency can give no valid reason for the opposite choice either. The agency is constrained to choose, but any choice it makes would fail ordinary arbitrariness review. Recognizing this dilemma, the court should defer to the agency's choice.

      Any other judicial approach will create deadweight losses for the system. If the court itself picks arbitrarily, substituting its own decision for the agency's, there is by hypothesis no added benefit whatsoever, but there is the extra cost of the judicial proceeding itself, including not only the out-of-pocket costs but also the delay in reaching some choice or other. Furthermore, as we will discuss shortly under the rubric of tacit expertise, the agency's choice may actually be better than the court's in ways and on grounds that the agency cannot explain to the court; the agency may simply have better instincts, even in situations of severe uncertainty. If, on the other hand, the court demands first-order reasons for the agency's choice, then any of the agency's possible choices can be overturned as arbitrary. On that approach, one of two pathological results will occur. Either the agency will be trapped in an indefinite cycle of reversal, as the court overturns every new agency attempt to make a policy choice, or--more likely--agencies will have powerful incentives to engage in a charade, in which they offer the reviewing court bogus first-order reasons to prefer one alternative over the other. In such situations, it is pathological for courts to relentlessly demand that the agency supply first-order reasons that in the nature of things cannot be given. At the frontier of uncertainty, rationality simply runs out.

      Two doctrinal conclusions follow, one involving Section 706(2)(A) of the APA, the other involving State Farm and the rational connection test. The first...