Document Type

Article

Publication Date

2004

Keywords

quality-adjusted life years, QALY's, welfare, risk assessment, regulatory agencies, risk, welfare setbacks

Abstract

Risk assessment is now a common feature of regulatory practice, but fear assessment is not. In particular, environmental, health and safety agencies such as EPA, FDA, OSHA, NHTSA, and CPSC, commonly count death, illness and injury as costs for purposes of cost-benefit analysis, but almost never incorporate fear, anxiety or other welfare-reducing mental states into the analysis. This is puzzling, since fear and anxiety are welfare setbacks, and since the very hazards regulated by these agencies - air or water pollutants, toxic waste dumps, food additives and contaminants, workplace toxins and safety threats, automobiles, dangerous consumer products, radiation, and so on - are often the focus of popular fears. Even more puzzling is the virtual absence of economics scholarship on the pricing of fear and anxiety, by contrast with the vast literature in environmental economics on pricing other intangible benefits such as the existence of species, wilderness preservation, the enjoyment of hunters and fishermen, and good visibility, and the large literature in health economics on pricing health states.

This Article makes the case for fear assessment, and explains in detail how fear and anxiety should be quantified and monetized as part of a formal, regulatory cost-benefit analysis. I propose, concretely, that the methodology currently used to quantify and monetize light physical morbidities, such as headaches, coughs, sneezes, nausea, or shortness of breath, should be extended to fear. The change in total fear-days resulting from regulatory intervention to remove or mitigate some hazard - like the change in total headache-days, cough-days, etc. - should be predicted and then monetized at a standard dollar cost per fear-day determined using contingent-valuation interviews.

Part I of the Article rebuts various objections to fear assessment. Deliberation costs are a worry, but this is not unique to fear, and can be handled through threshold rules specifying when the expected benefits of fear assessment appear to outweigh the incremental deliberation costs of quantifying and monetizing fear. Other objections reduce to the deliberation-cost objection, or are misconceived: irrational as well as rational fears are real harms for those who experience them; fear can be quantified; worries about uncertainty and causality reduce to deliberation costs; the possibility of reducing fear through information rather than prescription means that agencies should look at a wider range of policy options, not that they should evaluate options without considering fear costs; the concern that the very practice of fear assessment will on balance, increase fear by creating stronger incentives for fear entrepreneurs seems overblown; and fear is a welfare setback, whether or not it flows from political views.

Part II argues for what I call the unbundled valuation of fear. A given hazard may cause a package of harms for each individual exposed to it: the fear of the hazard, an incremental risk of death, and perhaps other harms. Why not, then, price the harms as a package? In particular, why not predict the deaths caused by a given hazard and avoided by regulatory intervention, and multiply those deaths by a value of statistical life (VOSL) number designed to incorporate a fear premium? For reasons explored in Part II, the bundled valuation of fear and death, through fear premia attached to VOSLs or in other ways, is misguided. Rather, these two kinds of harms should be separately quantified and monetized.

Parts III and IV consider how agencies should monetize fear states. How should the price of a fear-day be determined? Part III argues that contingent-valuation techniques are more appropriate, here, than revealed-preference techniques. Part IV discusses the design of contingent-valuation interviews for pricing fear. The instrumental as well as intrinsic costs of fear may need to be accounted for; the respondents to these interviews should, optimally, be calm rather than fearful; and interviews designed to secure a QALY valuation of fear can also be useful, but only if the QALY scale is understood as a welfare scale and calibrated in an inclusive way.

In arguing for fear assessment as a component of cost-benefit analysis, this Article contributes to the literature on cost-benefit analysis and also stakes out a novel position in scholarly debates about risk regulation. One standard view (call it the simple technocratic view) argues that popular fear should play no role in determining regulatory choice; instead, regulators should focus on minimizing or achieving technologically feasible or cost-justified reductions in death, illness and injury. A standard opposing view (call it the populist view) is that popular perceptions of the riskiness of hazards, in turn substantially influenced by how feared or dreaded the hazards are, should be determinative. The account presented in this Article is technocratic, not populist; risk regulators should seek to maximize social welfare, and cost-benefit analysis is a technocratic tool for doing just that. Yet technocratic risk regulation need not focus narrowly on mortality and morbidity. It should focus (prima facie) on all constituents of welfare, including fear and anxiety. Although popularly perceived risk should not determine risk regulation, since the fear and anxiety that drives popular risk perception is simply one welfare impact among the multitude of costs and benefits flowing from hazards, neither should risk regulation reduce to counting deaths or injuries - to a crude minimization of physical impacts or a simplistic balancing in which death- and injury-reduction are the sole regulatory benefits that are seen to counterbalance compliance costs.

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