Person:

Sunstein, Cass

In recent years, social scientists have been incorporating empirical findings about human behavior into economic models. These findings offer important insights for thinking about regulation and its likely consequences. They also offer some suggestions about the appropriate design of effective, low-cost, choice-preserving approaches to regulatory problems, including disclosure requirements, default rules, and simplification. A general lesson is that small, inexpensive policy initiatives can have large and highly beneficial effects. In the United States, a large number of recent practices and reforms reflect an appreciation of this lesson. They also reflect an understanding of the need to ensure that regulations have strong empirical foundations, both through careful analysis of costs and benefits in advance and through retrospective review of what works and what does not.

The concept of "irreversibility" plays a large role in many domains, including public health, medical practice, and environmental protection. Indeed, the concept is explicit in some statements of the Precautionary Principle. But the idea of irreversibility remains poorly defined. Because of the flow of time, any loss is, in a sense, irreversible. On one approach, irreversibility might be understood as a reference to the value associated with taking precautionary steps that maintain flexibility for an uncertain future ("option value"). On another approach, irreversibility might be understood to refer to the qualitatively distinctive and even unique nature of certain losses - a point that raises a claim about incommensurability. The two conceptions fit different problems. These ideas can be applied to a wide assortment of environmental and public health questions, including overuse of antibiotics, genetic modification of food, avian flu, and climate change.

Each government agency uses a uniform figure to measure the value of a statistical life. This is a serious mistake. The very theory that underlies current practice calls for far more individuation of the relevant values. According to that theory, the value of statistical lives should vary across risks. More controversially, the value of a statistical life should vary across individuals - even or especially if the result would be to produce a lower number for some people than for others. One practical implication is that a higher value should be given to programs that reduce cancer risks. Should government use a higher VSL for programs that disproportionately benefit the wealthy - and lower VSL for programs that disproportionately benefit the poor? A serious complication here is that sometimes the beneficiaries of regulation pay only a fraction or even none of its cost; when this is so, the appropriate VSL for poor people might be higher, on distributional grounds, than market evidence suggests. An understanding of this point has implications for foundational issues about government regulation, including valuation of persons in poor and wealthy nations.

Many regulators have concluded that cost-benefit analysis is the best available method for capturing the welfare effects of regulations. It is therefore understandable that in recent years, some people have been interested in requiring financial regulators to engage in careful cost-benefit analysis of their regulations, and to proceed only if the benefits justify the costs. Ideas of this sort have played a significant role in judicial review of agency action, especially in cases involving the Securities and Exchange Commission. But it is important to distinguish the question whether courts should require cost-benefit analyses, and review them for arbitrariness, from the separate question whether financial regulators should produce such analyses. It is also important to understand that in some cases, cost-benefit analysis presents serious challenges for financial regulators. When agencies lack relevant information, and cannot project benefits (or costs), they can invoke established techniques to discipline the question whether and how to proceed. In particular, breakeven analysis plays a valuable role. Of course it remains possible that in rare cases, agencies have so little information that they cannot even use breakeven analysis. In such cases, it is not helpful to refer to the precautionary principle or to “expert judgment.” In such rare cases, the best that agencies may be able to do is to rely on some version of maximin, while also seeking to fill informational gaps over time.

Technocratic judgments can have a “cooling function.” An insistent focus on the facts, and on the likely consequences of policies, might soften political divisions and produce consensus. Within the federal government, cost-benefit analysis is a prominent example of the cooling function of technocracy. But when undertaken prospectively, such analysis is sometimes speculative and can be error-prone; in addition, circumstances change, often in unanticipated ways. For this reason, retrospective analysis, designed to identify the actual rather than expected effects, has significant advantages. The “regulatory lookback,” first initiated in 2011 and undertaken within and throughout the executive branch, has considerable promise for simplifying the regulatory state, reducing cumulative burdens, and increasing net benefits. It deserves a prominent place in the next generation of regulatory practice. Recent history also suggests that it might well soften political divisions.