Public figures often apologize after making controversial statements. There are reasons to believe, however, that apologizing makes public figures appear weak and risk averse, which may make them less likeable and lead members of the public to want to punish them. This paper presents the results of an experiment in which respondents were given two versions of two real-life controversies involving public figures. Approximately half of the participants read a story that made it appear as if the person had apologized, while the rest were led to believe that the individual had stood firm. In the first experiment, hearing that Rand Paul apologized for his comments on civil rights did not change whether respondents were less likely to vote for him. When presented with two versions of the controversy surrounding Larry Summers and his comments about women scientists and engineers, however, liberals and females were more likely to say that he should have faced negative consequences for his statement when presented with his apology. The effects on other groups were smaller or neutral. The evidence suggests that when a prominent figure apologizes for a controversial statement, individuals are either unaffected or become more likely to desire that the individual be punished.

Naturalistic monitoring tools provide detailed information about people's behaviours and experiences in everyday life. Most naturalistic monitoring research has focused on measuring subjective well-being. This paper discusses how naturalistic monitoring can inform behavioural public policy-making by providing detailed information about everyday decisions and the choice architecture in which these decisions are made. We describe how the Day Reconstruction Method (DRM) – a naturalistic monitoring tool popular in the subjective well-being literature – can be used to: (i) improve ecological validity of behavioural economics; (ii) provide mechanistic evidence of the everyday workings of behavioural interventions; and (iii) help us to better understand people's true preferences. We believe that DRM data on everyday life have great potential to support the design and evaluation of behavioural policies.

The COVID-19 pandemic has forced governments around the world into drastic measures without the normal evidence base or analyses of consequences. We present a quantitative model that can be used to rapidly assess the introduction and interaction of nonpharmaceutical infection prevention measures (NPI) both in rapid a priori predictions and in real-world a posteriori evaluations. Two of the most popular NPIs are imposing minimum physical interpersonal distancing and the use of face coverings. The success of both measures is highly dependent on the behavior of the public. However, there is very little published information about the interactions between distance, mask wearing, and the behavioral adaptations that they are likely to generate. We explore the relation between these two fundamental NPIs and the behavioral responses that they may induce, considering both risk compensation and social norms enhancement. At present, we do not have the necessary information to parameterize our model to a sufficient degree to generate quantitative, immediately applicable, advice, but we explore a vast parameter space and illustrate how the consequences of such measures can range from highly beneficial to paradoxically harmful in plausible real situations.

By identifying well-being with preference satisfaction, mainstream normative economists were able to leave the determination of which specific things make people better or worse off to the individuals themselves. The findings of behavioral economics undermine the possibility of deferring in this way to individual preference. One response to this challenge to welfare economics is to distinguish the true preferences of individuals from their manifest preferences and to take true preferences to guide policy. In The Community of Advantage, Robert Sugden criticizes this strategy and proposes that economists appraise policies, institutions and outcomes by the opportunities they provide rather than by their contributions to welfare. This paper criticizes Sugden's view and argues for a modest solution that makes cautious use of preferences as indicators of well-being.

Evidence on the effectiveness of health promotion interventions is mixed, especially in terms of the magnitude of their impact and long-term adherence. This paper proposes a comprehensive approach informed by behavioural economics of developing behavioural change programmes, which is designed to educate, activate, engage and empower people by taking into consideration individual and social mechanisms. Three applied pilots and their results are presented in order to illustrate the approach using cognitive and social mechanisms to lead to better health outcomes, individually and community-wide. More research is needed to explore levers and barriers for the systemic adoption of this framework in implementing health promotion interventions.

Many people delay their preparation for retirement. Policy-makers often attempt to motivate people to take timely action by increasing the perceived importance of retirement saving, yet the effectiveness of such strategies can be doubted. We examined why a strategy of emphasizing importance may be ineffective by distinguishing between intention to prepare for retirement and action in actually taking steps toward preparation. Two surveys (n1 = 1171; n2 = 832) showed that importance and difficulty were both predictive of people's intentions to prepare for retirement, but that difficulty was a much stronger predictor of people's actual actions. Using data from an additional survey (n3 = 986), a series of follow-up tests provided further evidence that difficulty of retirement preparation is a stronger predictor of inaction than importance of retirement saving. These findings help explain why policies aimed at simplifying retirement preparation (e.g., automatic enrollment) have been more successful than policies aimed at increasing the importance of retirement saving (e.g., tax advantages).

A behavioural public policy movement has flourished within the global policy realm. While this movement has been deemed interdisciplinary, incorporating behavioural science theories and methods in a neoclassical economics-governed policy process, this paper analyses the bounded form of interdisciplinarity that characterizes it. We claim that an engagement is missing with the broader sweep of social sciences, which share similar concerns but deploy different analytical perspectives from those of behavioural public policy. Focusing on two central concepts (context and evidence), we aim to show how behavioural public policy's bounded interdisciplinarity implies constrained understandings of context and evidence, thereby limiting its complex problem-solving abilities. At the same time, we highlight some alternative examples of behavioural public policy practice that do explore new critical interdisciplinary horizons.

Some of the most important decisions young people make are choices about education. Yet recent research shows that educational decisions are poorly explained by classical models of human capital investments: adolescents do not always choose what would best optimize their long-term net outcomes. Instead, students have been shown to be influenced by their current group of peers at the time when they make educational decisions. We expand on existing models by showing that students’ stated educational preferences can be influenced by simply priming them with their peers’ preferences. Further, we show that students are unaware of this peer influence in the sense that: (1) they claim that peers have no influence; (2) in a conjoint experiment, they do not select educations based on peers’ assessments; and (3) in a list experiment absent of any social desirability bias, they do not ascribe any influence to their peers either. All in all, the results show that young people are unwittingly influenced by their peers. These results have important implications for public policies aimed at encouraging young people to make more deliberate and informed educational choices.

Do differences in worldview ideology hinder people from objectively interpreting the effect of immigration? In an experiment with Swedish adults (n = 1015), we investigate whether people display motivated reasoning when interpreting numerical information about the effects of refugee intake on crime rate. Our results show clear evidence of motivated reasoning along the lines of worldview ideology (i.e., whether people identify themselves primarily as nationally oriented or globally oriented). In scenarios where refugee intake was associated with higher crime rate, nationally oriented people were 18 percentage points more likely to make the correct assessment compared to globally oriented people. Likewise, in scenarios where refugee intake was associated with lower crime rate, nationally oriented people were 20 percentage points less likely to make the correct assessment compared to globally oriented people. Individuals with higher numeric ability were less likely to engage in motivated reasoning, suggesting that motivated reasoning more commonly is driven by feelings and emotional cues rather than deliberate analytical processes.

One major challenge facing policy-makers is to design education and workplace training programs that are appropriately challenging. We review previous research that suggests that difficult training is better than easy training. However, surveys we conducted of students and of expert sport coaches showed that many prescribed easy rather than difficult training for those they coached. We analyzed the performance of National Collegiate Athletic Association (NCAA) basketball teams in postseason tournaments to see whether the existing research, largely on individuals in short-term situations, would generalize to teams in the long run. Indeed, playing difficult nonconference (training) games modestly improved performance for NCAA teams in the postseason. Difficult training particularly benefitted teams that lost many nonconference games, and the effect of difficulty was positive within the range of difficulty NCAA teams actually encounter, making it clear that difficult training is superior. We suggest that our results can be generalized beyond sports, although with careful consideration of differences between NCAA basketball teams and other teams that may limit generalizability. These results suggest that policy-makers might consider amplifying the difficulty of team training exercises under certain conditions.

Defaults may not directly get people to behave as intended, such as saving more, eating healthy food or donating to charity. Rather, defaults often only put people on the ‘right’ path, such as joining a savings plan, buying healthy food or pledging money to charity. This an issue because getting more people to take those first steps does not necessarily motivate them to go on with further steps. Indeed, the default does little to help them understand the benefit of doing so. This can greatly reduce the impact of the default. We test this idea in a charitable giving experiment where people first can promise to give to charity (‘pledge’) and then can go on to donate. We find that participants pledge more often when that is the default, but those who pledge in that case are less likely to take further steps to donate than those who pledge when pledging is against the default. We interpret this in terms of motivation and transaction costs. Some people pledge only to avoid the psychological costs of going against the default. Those people are closest to indifference between donating or not and are therefore less motivated to go on to donate. We also show that the intrinsic motivation of pledgers is lower when pledging is the default and that making pledges the default does not change attitudes to charities.

Surveys based on self-reported hygiene-relevant routine behaviors have played a crucial role in policy responses to the COVID-19 pandemic. In this article, using anchoring to test validity in a randomized controlled survey experiment during the COVID-19 pandemic, we demonstrate that asking people to self-report on the frequency of routine behaviors are prone to significant measurement error and systematic bias. Specifically, we find that participants across age, gender, and political allegiance report higher (lower) frequencies of COVID-19-relevant behaviors when provided with a higher (lower) anchor. The results confirm that such self-reports should not be regarded as behavioral data and should primarily be used to inform policy decisions if better alternatives are not available. To this end, we discuss the use of anchoring as a validity test relative to self-reported behaviors as well as viable alternatives to self-reports when seeking to behaviorally inform policy decisions.

The concept and use of choice architecture in public policy arouses warranted suspicion among scholars and the general public. Liberal scholars fear that without limitations, the contemporary wave of nudge theory and policies threaten individual autonomy. In this paper, I argue that the use of choice architecture in particular policy areas can not only enhance individual autonomy, but also work to mitigate larger social inequalities. Research demonstrates that too much choice leads to ‘choice paralysis’, especially in instances where knowledge is low and stakes are high. By limiting and nudging choices in these contexts, individuals are likely to feel less overwhelmed and more in control. A stronger sense of control and additional resources elevates the experience of autonomy felt by vulnerable populations (those with low knowledge and resources). This paper offers a theoretically robust defense of choice architecture by examining the relationship between choice architecture and autonomy.

Behavioral economics research has helped with understanding charitable behavior and has shown that charities can encourage donations by carefully designing their pledges. However, there is still scope to extend current research on who gives, what drives the decision to donate and at what levels, especially when behavioral insights are applied in context. In cooperation with a major Italian charity for cancer research, this study implements a natural direct mail field experiment, with over 150,000 letters sent to donors. By exploring the behavioral responses to different donation anchors, evidence was found that, within the given framework, including donation menus significantly increased the average amount donated without affecting the likelihood of donation. Furthermore, introducing additional explanations of how to make a payment significantly increased overall returns. Lastly, individual heterogeneity (high- and low-frequency donors, as well as senior and junior donors) had a direct effect on donations.

Nudging has become a well-known policy practice. Recently, ‘boosting’ has been suggested as an alternative to nudging. In contrast to nudges, boosts aim to empower individuals to exert their own agency to make decisions. This article is one of the first to compare a nudging and a boosting intervention, and it does so in a critical field setting: hand hygiene compliance of hospital nurses. During a 4-week quasi-experiment, we tested the effect of a reframing nudge and a risk literacy boost on hand hygiene compliance in three hospital wards. The results show that nudging and boosting were both effective interventions to improve hand hygiene compliance. A tentative finding is that, while the nudge had a stronger immediate effect, the boost effect remained stable for a week, even after the removal of the intervention. We conclude that, besides nudging, researchers and policymakers may consider boosting when they seek to implement or test behavioral interventions in domains such as healthcare.

Gamblers are frequently reminded to ‘gamble responsibly’. But these qualitative reminders come with no quantitative information for gamblers to judge relative product risk in skill-based gambling forms. By comparison, consumers purchasing alcohol are informed of product strength by alcohol by volume percentage (ABV%) or similar labels. This paper uses mixed logistic regression machine learning to uncover the potential variation in soccer betting outcomes. This paper uses data from four bet types and eight seasons of English Premier League soccer, ending in 2018. Outcomes across each bet type were compared using three betting strategies: the most-skilled prediction, a random strategy and the least-skilled prediction. There was a large spread in betting outcomes, with, for example, the per-bet average loss varying by a factor of 54 (from 1.1% to 58.9%). Gamblers’ losses were positively correlated with the observable betting odds across all bets, indicating that betting odds are one salient feature that could be used to inform gamblers about product risk. Such large differences in product risk are relevant to the promotion of responsible gambling.

We explore whether simple behavioural insights techniques can be successful for addressing a policy issue within one of society's more complex and difficult sectors: child protection. Child protection reporting practices in New South Wales, Australia, reveal that the public's primary response is to report to the statutory authority, who only deal with cases of the highest risk. As a result, a large volume of statutory resources are spent processing lower-risk reports that lead to no benefits for lower-risk families and slow down response times for families that require a statutory response most. Our goal was to reduce lower-risk reporting by encouraging alternative responses to these situations. To do this, we altered report feedback for cases deemed lower risk in order to make alternative responses more salient and we added a persuasive message framed as a gain or loss. We then examined subsequent reporting accuracy. We found that our trial was linked to a modest improvement in reporting accuracy, though the results may have been diluted by a spill-over effect. We discuss how facilitating a greater behavioural change likely requires multi-organization collaborations, extending the range of insights drawn from behavioural science and/or addressing issues from multiple angles.

Corruption in the form of bribery continues to be a major societal challenge around the world. The current lab-in-the-field study tested whether dynamic descriptive norms messages on posters can help to reduce bribery. Before, during and after placing posters throughout a medium-sized South African town, incentivized measures of social norms and bribery were assessed in a mobile lab. A total of 311 participants stemming from the general population took part. In line with the pre-registered predictions, the results reveal that people: (1) perceive bribery to be less common; and (b) engage in bribery in a corruption game less frequently when the posters were displayed. The discussion outlines how social norms nudging campaigns can be leveraged to spur collective action against corruption.

Insights from the behavioural sciences are increasingly used by governments and other organizations worldwide to ‘nudge’ people to make better decisions. Furthermore, a large philosophical literature has emerged on the ethical considerations on nudging human behaviour that has presented key challenges for the area, but is regularly omitted from discussion of policy design and administration. We present and discuss FORGOOD, an ethics framework that synthesizes the debate on the ethics of nudging in a memorable mnemonic. It suggests that nudgers should consider seven core ethical dimensions: Fairness, Openness, Respect, Goals, Opinions, Options and Delegation. The framework is designed to capture the key considerations in the philosophical debate about nudging human behaviour, while also being accessible for use in a range of public policy settings, as well as training.

When policymakers focus on costs and benefits, they often find that hard questions become easy – as, for example, when the benefits clearly exceed the costs, or when the costs clearly exceed the benefits. In some cases, however, benefits or costs are difficult to quantify, perhaps because of limitations in scientific knowledge. In extreme cases, policymakers are proceeding in circumstances of uncertainty rather than risk, in the sense that they cannot assign probabilities to various outcomes. We suggest that in difficult cases in which important information is absent, it is useful for policymakers to consider a concept from poker: ‘freerolls.’ A freeroll exists when choosers can lose nothing from selecting an option but stand to gain something (whose magnitude may itself be unknown). In some cases, people display ‘freeroll neglect.’ In terms of social justice, John Rawls’ defense of the difference principle is grounded in the idea that, behind the veil of ignorance, choosers have a freeroll. In terms of regulatory policy, one of the most promising defenses of the Precautionary Principle sees it as a kind of freeroll. Some responses to climate change, pandemics and financial crises can be seen as near-freerolls. Freerolls and near-freerolls must be distinguished from cases involving cumulatively high costs and also from faux freerolls, which can be found when the costs of an option are real and significant, but not visible. ‘Binds’ are the mirror-image of freerolls; they involve options from which people are guaranteed to lose something (of uncertain magnitude). Some regulatory options are binds, and there are faux binds as well.