Behavioural economics research has pointed to the importance of market inefficiencies, framing, heuristics and hyperbolic discounting. Empirically, behavioural economics has been shown to predict patterns of consumer behaviour, exercise patterns and substance addiction. In this article, I discuss the ways in which our growing understanding of behavioural economics has shaped the development of public policies. I conclude with six pieces of advice for behavioural policymakers.

We study individuals' incentives to make investment decisions. Using data from a large pension system in Chile we find that individuals who are active in managing their investments have, on average, poor performance. We provide robust evidence suggesting that learning plays an important part in this phenomenon. Indeed, individuals who have made successful investment decisions in the past go on to trade more frequently. However, this result holds when using a naive definition for successful decisions. Also, average performance is negatively related to the number of investment decisions, casting doubt on the existence of market timing skills.

Under dynamic efficiency, a pay-as-you-go (PAYG) pension scheme helps the current generation of retirees but hurts future generations because they are forced to save via a return-dominated scheme. Abandoning it is deemed welfare-improving but typically not for all generations. But what if agents are present-biased (hence, undersave for retirement) and the “paternalistically motivated forced savings” component of a PAYG scheme motivated its existence in the first place? This paper shows it is possible to transition from such a PAYG scheme on to a higher return, mandated fully-funded scheme; yet, no generation is hurt in the process. The results inform the debate on policy design of pension systems as more and more policy makers push for the transition to take place but are forced to recognize that current retirees may get hurt along the way.

This paper examines the implications for regional policy of new research on the role played by a failure in the ‘capacity to aspire’ [Appadurai, A. (2004), ‘The capacity to aspire’, in Rao, V. and Walton, M. (eds), Culture and Public Action, Washington, DC: World Bank.] in perpetuating disadvantage traps. After a brief review of the magnitude of the challenge that regional policy needs to confront, it provides a summary of the theoretical and empirical literature on poverty and aspirations failure (and the associated loss of agency, beliefs and self-efficacy). The key implication for the design of an inclusive regional policy is that it needs to address simultaneously the sources of external constraints (such as the availability of resources or adequate infrastructure) and mitigate the aspirations failure inherently linked to persistent disadvantage.

This research seeks to determine effects of rising interest in gluten-free foods on U.S. retail food demand and, ultimately, producer and consumer welfare. Increased gluten-free interest led to a modest reduction in cereals and bakery demand and increases in meat, alcoholic beverages, and food away from home demand. Combining estimated effects with an equilibrium displacement model suggests the reduction in cereal and bakery demand decreases wheat and barley producer profits by US$7.2 million/year. After accounting for positive demand impacts on other products, results indicate wheat and barley supply is redistributed away from food production into animal production, increasing wheat producer welfare.

We have designed and implemented an experimental module in the 2014 Health and Retirement Study to measure older persons' willingness to defer claiming of Social Security benefits. Under the current system’ status quo where delaying claiming boosts eventual benefits, we show that 46% of the respondents would delay claiming and work longer. If respondents were instead offered an actuarially fair lump sum payment instead of higher lifelong benefits, about 56% indicate they would delay claiming. Without a work requirement, the average amount needed to induce delayed claiming is only $60,400, while when part-time work is stipulated, the amount is slightly higher, $66,700. This small difference implies a low utility value of leisure foregone, of under 20% of average household income.

Our research investigates the effects of residential energy efficiency audit programs on subsequent household electricity consumption. Here there is a one-time interaction between households, which participate voluntarily, and the surveyors. Our research objective is to determine whether and to what extent the surveys lead to behavioral changes. We then examine how persistent the intervention is over time and whether the effects decay or intensify. The main evaluation problem here is survey participants’ self-selection, which we address econometrically via several non-parametric estimators involving kernel-based propensity-score matching. In the first method we use difference-in-differences (DID) estimation. Our second estimator is quantile DID, which produces estimates on distributions. The comparison group consists of households who were not yet participating in the survey but participated later. Our evidence is that the customers who participated in the survey reduced their electricity consumption by about 7%, on average compared to customers who had not yet participated in the survey. Considering the total number of high-usage households participating in the survey in 2009, we estimate that electricity consumption was reduced by an aggregate of 2 million kWh per year, which is approximately equal to the monthly consumption of 3500 typical households in California with an estimated 1527 metric tons less of carbon dioxide emissions. Because the energy audit program is inexpensive ($10–$20 per household) a key issue is that while the program is cost-effective, is it regressive? We find that as the quantiles of the outcome distribution increase, high-use households save proportionally less electricity than do low-use customers. Overall, our results imply that program designers can better target low-use and low-income households, because they are more likely to benefit from the programs through energy savings.

We develop a dynamic economic model based on contemporary understanding of learning and motivation. The model and resulting comparative static analysis show the instructor's role in providing a productive learning environment. Instructors should set the complexity of course assignments and assessments to be consistent with student preparedness. Learning is enhanced when the rate of change in challenge is based on the rate of change of how rapidly students are learning. Instructors steer students toward a productive trajectory with tasks that cause students to work hard and by consistently providing feedback and fostering a culture of learning.

While much is known about dyslexia in school-age children and adolescents, less is known about its effects on quality of life in adults. Using data from the Connecticut Longitudinal Study, we provide the first estimates of the monetary value of improving reading, speaking, and cognitive skills to dyslexic and nondyslexic adults. Using a stated-preference survey, we find that dyslexic and nondyslexic individuals value improvements in their skills in reading speed, reading aloud, pronunciation, memory, and information retrieval at about the same rate. Because dyslexics have lower self-reported levels on these skills, their total willingness to pay to achieve a high level of skill is substantially greater than for nondyslexics. However, dyslexic individuals’ willingness to pay (averaging $3000 for an improvement in all skills simultaneously) is small compared with the difference in earnings between dyslexic and nondyslexic adults. We estimate that dyslexic individuals earn 15% less per year (about $8000) than nondyslexic individuals. Although improvements in reading, speaking, and cognitive skills in adulthood are unlikely to eliminate the earnings difference that reflects differences in educational attainment and other factors, stated-preference estimates of the value of cognitive skills may substantially underestimate the value derived from effects on lifetime earnings and health.

Consumers implicitly incorporate their perceptions of products into their decision processes, yet little research has explicitly focused on how those perceptions influence demand for meat. This study incorporates taste, health, and safety perceptions into a discrete choice experiment for meat products at a grocery store. Our results indicate that taste is the most important perception as a 1-unit increase in the perceived tastiness (on a −5 to +5 scale) of a food product leads to a $0.60 increase in willingness to pay, whereas equivalent increases in perceived health and safety lead to $0.31 and $0.21 increases, respectively.

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.

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.

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.

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.

The results of the vast array of willingness to accept compensation/ willingness to pay (WTA/WTP) disparity studies provide strong evidence that people value many losses and reductions of losses, more, and often much more, than otherwise commensurate gains or foregoing of gains. These findings also make it clear that people commonly value many changes not as final states as standard theory assumes, but as positive or negative changes relative to a neutral reference state. Consequently, not only are losses to be most accurately assessed with the WTA measure, but most positive changes that reduce losses are as well. Current practice, which rarely takes such reference dependence into account, is therefore likely to substantially understate the value and importance of projects, policies, and programs that reduce losses. Failing to take the possibilities of valuation disparities into account also appears to undermine other kinds of analyses as well, including, for example, the estimation of elasticities and setting effective levels of Pigouvian taxes.

Benefit-cost analysis (BCA), a discipline best known for guiding policy choices, can also guide personal decisions. In either application, traditional BCA tallies benefits and costs using market values or willingness to pay. When future outcomes are uncertain, as they are across a wide array of situations, BCA must call as well on the methods of decision analysis. Thus, von Neumann–Morgenstern utilities, subjective probabilities, and sequential decision strategies are brought into play.

Traditional decision analysis distinguishes between risk and uncertainty. With risk, the probabilities of possible outcomes are known; with uncertainty, those outcomes are known, but not their probabilities. We introduce the concept of ignorance: a third, less tractable category. With ignorance, even the possible outcomes of decisions cannot be identified. Ignorance takes particular importance when high payoffs are associated with these unidentified outcomes, as is often the case. We identify such outcomes as consequential amazing developments (CADs). In the policy realm, the 2008 financial meltdown or the Arab Spring would represent a CAD. For an individual, a CAD might be that one’s secure tenured position had been inexplicably terminated, or that one’s trusted business partner had long been shuttling corporate secrets to a competitor. We distinguish between unrecognized and recognized ignorance. In the latter category, we identify specific cognitive biases that impair decision making.

Consequential ignorance cannot be studied in a controlled laboratory setting, since its payoffs are high, its time delays often long, and merely introducing the subject would tend to give away the game. Thus we develop a descriptive understanding of ignorance drawing on great works of literature, from antiquity to the present day, positing that skilled writers understand how humans make decisions and respond to unanticipated outcomes. Shakespearean examples would be Hamlet’s ignorance of his father’s killer, and Macbeth’s lack of awareness of the tragic ramifications following his actions to seize the Scottish crown.

Following this descriptive analysis, we turn to prescription. We draw on decision analysis to develop a formula for calculating consequential ignorance; it incorporates the expected magnitudes and assessed base rates for CADs. Finally, we propose a decision-analytic framework for measured decision making, given ignorance. Our recommended approach explicitly recognizes decision-making costs, and thus proposes when to use quick and intuitive as opposed to more deliberative approaches to decision, or the labels Kahneman has popularized as System 1 and System 2.

Studying ignorance through literature has important implications for BCA. Given the potential for ignorance, there are two key goals for prudent decision making. First, steps should be taken to recognize when ignorance might be present. Second, efforts should be made not to respond in a suboptimal fashion when ignorance is anticipated or when a CAD springs upon us. Great literature can provide the equivalent of widespread life experience, and can help a decision maker reach both goals. At its heart, this essay represents a benefit-cost approach to dealing with ignorance. Numerous connections to BCA are made throughout.

In this article, we focus on two types of “aversion” which we deem essential aspects of the notion of trust: betrayal aversion (social) and ambiguity aversion (a special case of aversion to uncertainty). Based on trust-games studies in experimental economics and neuroeconomics, our main goal is to assess the conceptual, behavioral and neurobiological connections between betrayal and ambiguity aversions.

From a social and individual psychological point of view the bottom line of our trusting behavior could be our general aversion to ambiguous signals. We approach social trust in the terms of a phenomenon based on uncertainty aversion. Specifically, a reduction of the perceived uncertainty of a social interaction tends to build up a trusting climate conducive to trade by decreasing betrayal aversion. We hypothesize that betrayal aversion and ambiguity aversion bear such a negative correlation.

Focusing on this potential negative correlation our approach clearly differs from more positive accounts of trust centred on altruism.

The current fiscal climate is focusing attention on the need for more efficient government. However, we have remarkably little rigorous information on which are the most cost-effective strategies for achieving common goals like delivering high quality education in deprived neighbourhoods or reducing carbon emissions. This paper argues that randomised impact evaluations can provide an effective way to generate the information needed to make government more effective. Advances in the theory and practice of running randomised evaluations mean that a wider range of questions can be answered than ever before. Elsewhere in the world, fundamental questions are being answered about how humans behave, which in turn are being used to design new policies which themselves are rigorously tested. By learning from these results, and by conducting more randomised evaluations on issues important to UK policy (both at home and abroad) it will be possible to design more effective policies and do more with less.