Behavioral economics and happiness research have many important implications for the conduct of benefit-cost analysis as well as for policy design and implementation. By identifying ways in which we may act irrationally and providing new perspectives on the relationship between our circumstances and our sense of well-being, this research raises numerous questions regarding the evaluation of individual and societal welfare and the desirability of alternative policies. In this special issue, we present a series of articles that explore these concerns and provide significant new insights.

This paper discusses the ways in which behavioral economics challenges the premises of conventional welfare economics. It proposes revised premises that survive those challenges and sets forth a welfare framework derived from that foundation. It argues that the proposed framework is practical, in the sense that it lends itself to applications, as well as unifying, in the sense that it subsumes other approaches and illuminates the relationships between them.

Behavioral economists have identified certain biases in decision making that lead people to make decisions that harm themselves, but there is insufficient guidance for estimating benefits in the presence of such behavioral failures. This gap in principles and standards for benefit-cost analysis has led government agencies at times to adopt arbitrary and excessive benefit valuations. This article describes an approach to incorporating behavioral market failures into benefit estimation, first by advocating a behavioral transfer test to use before applying behavioral findings from narrow contexts to broader populations subject to regulation, and then by comparing the outcomes from the self-harming behavior to a policy reference point in which people are assumed to be fully informed and to act fully rationally in their own self-interest. This approach, which is grounded on systematic, well-documented, and context-specific findings of behavioral failings, would reduce instances of agencies assuming that behavioral findings in some contexts provide sufficient rationale for overriding consumer preferences in other contexts. It would also establish a consistent approach to government policy by, for example, creating symmetry between advancing policies that seek to discourage consumption of products for which consumers underestimate the health risks and fostering accurate risk beliefs to address erroneous individual choices based on risk overestimation.

In our opinion, the challenges of ongoing measurement, the ever-moving behavioral baseline, and strategic self-ignorance return us full-circle to a sensible point made by Peter Bohm–Benefit-Cost Analysis for environmental goods should use an interval method.

If policymakers could measure the actual welfare effects of regulations, and if they had a properly capacious sense of welfare, they would not need to resort to cost-benefit analysis, which gives undue weight to some values and insufficient weight to others. Surveys of self-reported well-being provide valuable information, but it is not yet possible to “map” regulatory consequences onto well-being scales. It follows that at the present time, self-reported well-being cannot be used to assess the welfare effects of regulations. Nonetheless, greatly improved understandings are inevitable, and current findings with respect to reported well-being – above all the serious adverse effects of unemployment – deserve to play a role in regulatory policymaking.

Individuals who are compromised in their ability to either believe in or plan for their future will make very different valuations of future benefits than will those who have more means and capabilities. These valuations could apply across a wide spectrum, from health care and insurance to investments in education to retirement savings. Data based on time trade-offs and other hypothetical questions will lead to large gaps in contingency valuations which, taken at face value, would lead to regressive outcomes. Individuals who discount the future are unlikely to be responsive to information intended to mitigate risk or to nudges designed to guide behavior away from risky choices. For example, these differential responses result in particular preventive policies having much less than the intended benefit values. Subjective well-being metrics can help circumvent the problem by comparing the reported well-being of individuals who are actually in different arrangements, such as those who have taken up health insurance or not, or in different work arrangements. Still, subjective well-being metrics are a compliment and not a substitute for the standard data that is used in BCA.

Air pollution makes us feel bad when we think about it – but do bad air days really affect our subjective well-being (SWB) when we are not thinking about them? And if so, do they affect the range of possible measures of SWB in similar ways? Using data from over 165,000 individuals in the UK, we model evaluative, experiential and eudemonic SWB as a function of demographic and local area characteristics including the background concentration of particulate matter. Our results indicate that air pollution adversely affects all of the positive measure of SWB included in our analysis; how satisfied people report being with their lives overall, how happy they report feeling on the previous day and how worthwhile they rate their activities as being, and that it does so over and above its effects on self-reported health. These effects can be monetized and may imply greater priority being afforded to pollution abatement programs than is currently warranted based on existing estimates of the health effects alone.

Two important developments in recent policy analysis are behavioral economics and subjective-well-being (SWB) surveys. What is the connection between them? Some have suggested that behavioral economics strengthens the case for SWB surveys as a central policy tool, e.g., in the form of SWB-based cost-benefit analysis. This article reaches a different conclusion. Behavioral economics shows that individuals in their day-to-day, “System 1” behavior are not expected utility (EU-) rational – that they often fail to comply with the norms of rationality set forth by EU theory. Consider now that the standard preference-based view of individual well-being looks to individuals’ rational preferences. If the findings of behavioral economics are correct, an individual’s answer to a question such as “How satisfied are you with your life?” is not going to tell us much about her rational (EU-compliant) preferences. Behavioral economics, by highlighting widespread failures of EU rationality, might actually argue for an objective-good (non-preference-based) view of well-being. However (except in the limiting case of an objective-good view positing a single mentalistic good, happiness), SWB surveys will not be strong evidence of well-being in the objective-good sense. In short, SWB surveys are no “magic cure” for the genuine difficulties in inferring rational preferences and measuring well-being underscored by behavioral economics.