Behavioral economics and field experiments within the social sciences have advanced well beyond academic curiosum. Governments around the globe as well as the most powerful firms in modern economies employ staffs of behavioralists and experimentalists to advance and test best practices. In this study, we combine behavioral economics with field experiments to reimagine a new model of early childhood education. Our approach has three distinct features. First, by focusing public policy dollars on prevention rather than remediation, we call for much earlier educational programs than currently conceived. Second, our approach has parents at the center of the education production function rather than at its periphery. Third, we advocate attacking the macro education problem using a public health methodology, rather than focusing on piecemeal advances.

The use of behavioural sciences in government has expanded and matured in the last decade. Since the Behavioural Insights Team (BIT) has been part of this movement, we sketch out the history of the team and the current state of behavioural public policy, recognising that other works have already told this story in detail. We then set out two clusters of issues that have emerged from our work at BIT. The first cluster concerns current challenges facing behavioural public policy: the long-term effects of interventions; repeated exposure effects; problems with proxy measures; spillovers and general equilibrium effects and unintended consequences; cultural variation; ‘reverse impact’; and the replication crisis. The second cluster concerns opportunities: influencing the behaviour of government itself; scaling interventions; social diffusion; nudging organisations; and dealing with thorny problems. We conclude that the field will need to address these challenges and take these opportunities in order to realise the full potential of behavioural public policy.

Behavioural science is increasingly applied to policy in many countries. While the empirical approach to policy development is welcome, we argue with reference to existing literature that laboratory experiments are presently underused in this domain, relative to field studies. Assumptions that field experiments, including randomised controlled trials, produce more generalisable results than laboratory experiments are often misplaced. This is because the experimental control offered by the laboratory allows underlying psychological mechanisms to be isolated and tested. We use examples from recent research on energy efficiency and financial decision-making to argue that mechanism-focused laboratory research is often not only complementary to field research, but also necessary to interpreting field results, and that such research can have direct policy implications. The issues discussed illustrate that in some policy contexts a well-designed laboratory study can be a good – perhaps the best – way to answer the kinds of research questions that policy-makers ask.

Some of the challenges in Sanders et al. (2018, this issue) can be aptly illustrated by means of charity nudges; that is, nudges designed to increase charitable donations. These nudges raise many ethical questions. First, Oxfam's triptychs with suggested donations are designed to increase giving. If successful, do our actions match ex ante or ex post preferences? Does this make a difference to the autonomy of the donor? Second, the Behavioural Insights Team conducted experiments using social networks to nudge people to give more. Do these appeals steer clear of exploiting power relations? Do they respect boundaries of privacy? Third, in an online campaign by Kiva, donors are asked to contribute directly to personalised initiatives. In many cases, the initiative has already been funded and donor money is funnelled to a new cause. Is such a ‘pre-disbursal’ arrangement truthful and true to purpose as a social business model?

Over the last decade, health care in many parts of the world has shifted toward a more patient-centric, consumeristic model, marked by an emphasis on choice and a proliferation of typical consumer-facing information (e.g. price and quality data). However, while the ‘patients as consumers’ perspective is an apt one, there are crucial differences between health care and typical consumer domains that warrant special consideration by policy-makers and researchers alike. This article discusses some of these differences and explores the challenges that consumers (i.e. patients) face when making trade-offs between price and quality.

In a ‘post-truth’ era in which personality and opinion trump evidence and reason, the need for frankness in debates about the use and boundaries of science and policy is high. We welcome the reflective and nuanced approach to behavioural science in policy-making in Sanders, Snijders and Hallsworth's (2018) piece. Despite our support for the approach in this paper, we suggest that there are deeper issues than are currently acknowledged. Our critique tackles three issues: the empirical, the normative and the political. In the first section, we examine what counts as ‘behavioural’ and how this label is used to legitimate a range of policy activities. We then look at randomised controlled trials in the next section, highlighting the extra-scientific dimensions of the empirical ‘What Works’ revolution. Finally, we question some ontological assumptions that drive empirical research and its translation into policy, asking where the collective is to be found in behavioural public policy.

Behavioural economic research has established that defaults, one form of nudge, powerfully influence choices. In most policy contexts, all individuals receive the same nudge. We present a model that analyses the optimal universal nudge for a situation in which individuals differ in their preferences and hence should make different choices and may incur a cost for resisting a nudge. Our empirical focus is on terminated choosers (TCs), individuals whose prior choices become no longer available. Specifically, we examine the power of defaults on individuals who had enrolled in Medicare Advantage plans with drug coverage and whose plans were then discontinued. Currently, if these TCs fail to actively choose another Medicare Advantage plan, they are defaulted into traditional fee-for-service Medicare (TM) without drug coverage. Overall, the rate of transition of TCs into TM is low, implying that original preferences and status quo bias overpower the default. Increasing numbers of Americans are choosing plans in health insurance exchange settings such as Medicare, the Affordable Care Act and private exchanges. Plan exits and large numbers of TCs are inevitable, along with other forms of turmoil. Any guidance and defaults provided for TCs should factor in their past revealed preferences.

The Behavioural Insights Team (BIT) has led in the promotion and adoption of behavioural science research in public policy. This comment addresses a number of issues that must be faced by BIT and the wider behavioural public policy agenda as the field becomes institutionalised and normalised within public policy internationally, in particular issues of ethics and professional codes.

Limits on consumer attention give firms incentives to manipulate prospective buyers’ allocation of attention. This paper models such attention manipulation and shows that it limits the ability of disclosure regulation to improve consumer welfare. Competitive information supply from firms competing for attention can reduce consumers’ knowledge by causing information overload. A single firm subjected to a disclosure mandate may deliberately induce such information overload to obfuscate financially relevant information or engage in product complexification to bound consumers’ financial literacy. Thus, disclosure rules that would improve welfare for agents without attention limitations can prove ineffective for consumers with limited attention. Obfuscation suggests a role for rules that mandate not only the content, but also the format of disclosure; however, even rules that mandate ‘easy-to-understand’ formats can be ineffective against complexification, which may call for regulation of product design.

During the last decade, the Behavioural Insights Team (BIT) has been the main driver of establishing behavioural public policy as a novel approach in public policy. Adhering to a set of strategic principles, BIT has succeeded in translating insights from the behavioural science literature into policy interventions to show how behavioural science may be applied to public policy in a methodologically as well as economically efficient way. However, as Sanders, Snijders and Hallsworth (2018) note in their paper, the wide-ranging transformation of public policy development that many thought possible has remained absent. In this comment, I argue that this situation itself is due, at least partly, to the strategic principles adopted by BIT, and I call for developing more ‘diagnostic’ approaches, including better tools and models, to ensure that behavioural science is not perceived as offering merely technocratic tweaks.

‘Nudge’ is a concept of policy intervention that originates in Thaler and Sunstein's (2008) popular eponymous book. Following their own hints, we distinguish three properties of nudge interventions: they redirect individual choices by only slightly altering choice conditions (here ‘nudge 1’); they use rationality failures instrumentally (here ‘nudge 2’); and they alleviate the unfavourable effects of these failures (here ‘nudge 3’). We explore each property in semantic detail and show that no entailment relation holds between them. This calls into question the theoretical unity of nudge as intended by Thaler and Sunstein and most of their followers. We eventually recommend pursuing each property separately, both in policy research and at the foundational level. We particularly emphasise the need for reconsidering the respective roles of decision theory and behavioural economics to delineate nudge 2 correctly. The paper differs from most in the literature in focusing on the definitional rather than the normative problems of nudge.

Common principles for resource allocation in health care can prioritise the alleviation of small health burdens over lifesaving treatment. I argue that there is some evidence that these principles are at odds with a sizable share of public opinion, which holds that saving a life should take priority over any number of cures for minor ailments. I propose two possible explanations for this opinion, one debunking and one vindicatory. I also outline how well-designed surveys and moral enquiry could help decide between them. Finally, I consider how priority-setting principles could be adjusted if the view that saving a life always trumps alleviating small burdens were vindicated.

There are inherent differences in the priorities of academics and policy-makers. These pose unique challenges for teams such as the Behavioural Insights Team (BIT), which has positioned itself as an organisation conducting academically rigorous behavioural science research in policy settings. Here we outline the threats to research transparency and reproducibility that stem from working with policy-makers and other non-academic stakeholders. These threats affect how we perform, communicate, verify and evaluate research. Solutions that increase research transparency include pre-registering study protocols, making data open and publishing summaries of results. We suggest an incentive structure (a simple ‘nudge’) that rewards BIT's non-academic partners for engaging in these practices.

Socially minded nudges are the more sociable cousin of regular nudges: they reveal important information about other people's behavior, raise normative expectations about what is desirable, can be shared and transmitted online or offline and leverage social incentives and sanctions that regulate individual and group behavior. In this article, I argue that many of the most successful nudges – that is, nudges that have been well replicated, offer positive spill-over and whose effects last over time – have in fact been social nudges. Moreover, the efficacy of other nudges can be enhanced by considering the social dimension of the problem that they are trying to address. In asking where behavioral science should go next, I argue that although the Behavioural Insights Team has traditionally shied away from addressing more complex and sticky societal issues, socially situated nudges are particularly well suited to address many of the important challenges raised by Sanders et al. (2018).

Behavioral public policies are aimed at influencing the behavior of the public in a way that is advantageous for the public itself and within the law. Sanders, Snijders and Hallsworth (2018, this issue) summarize the state of the art of this new field of study and introduce a number of challenges and opportunities for the time to come. We address an additional challenge that is present and central in all attempts to influence behavior, namely the public – the people that are the target of behavioral public policies. We review evidence revealing that people do not passively accept those influence attempts, but often show reactant responses. We propose that the Persuasion Knowledge Model provides a framework both to understand the reactions of the public and to facilitate communication between academic researchers and practitioners.

This paper is a response to Sanders, Snijders and Hallsworth (2018). The challenges and opportunities of behavioural public policy Sanders, Snijders and Hallsworth discuss highlight a conundrum for the field: the impact of behavioural interventions is difficult to measure accurately in complex situations, and yet complexity is inherent in the very areas in most need of impact. Behavioural interventions will be only one tool of many to work towards broader organisational, systems and social change. As a field, we should be looking to other disciplines, inviting them into the fold of discussions on how to achieve these changes. Finally, while the mantra of nudge for good is a useful beacon, intentions are only part of the equation, and a number of questions should be asked when considering a behavioural policy intervention.

The application of behavioural insights to public policy has been a success story of recent years, in academia and in the civil service. Alongside this, a parallel group of practitioners has emerged, using the same underlying research to pursue commercial and marketing goals. Although the objectives are mostly different, many of the approaches are similar. This article contrasts public and private sector approaches and highlights lessons each group can learn from the other.