Nudging is often proposed as a promising policy approach for improving healthy choices among lower socioeconomic position (SEP) populations. However, nudges may not suit lower SEP contexts and empirical studies are scarce. We examined the efficacy of a repositioning nudge at a supermarket in a deprived neighborhood in improving healthier snack purchases and described customers’ healthy grocery shopping needs. Daily sales were collected during 4-week control and intervention periods, where healthier snacks replaced unhealthy snacks at the checkout. Besides, questionnaires were administered. More healthier snacks were sold per day during the intervention (Median = 2.50, Q1 = 2.00, Q3 = 3.50) than control period (Median = 0, Q1 = 0, Q3 = 1.00), B = 1.77, z = 5.50, p < .001, incidence rate ratio = 5.87 (95%CI [3.52, 10.17]). Despite statistical significance, the absolute number of healthier snacks sold remains negligible. Customers report to find it important to eat healthily and to think carefully about their groceries, but to hardly buy snacks at the checkout and desire a healthy and affordable food offer. Repositioning nudges may not suit the circumstances and needs of lower SEP populations. Interventions must be tailored to lower SEP groups and integrated with system-level policies.

We report the results of a field experiment designed to increase honest disclosure of claims at a U.S. state unemployment agency. Individuals filing claims were randomized to a message (‘nudge’) intervention, while an off-the-shelf machine learning algorithm calculated claimants’ risk for committing fraud (underreporting earnings). We study the causal effects of algorithmic targeting on the effectiveness of nudge messages: Without algorithmic targeting, the average treatment effect of the messages was insignificant; in contrast, the use of algorithmic targeting revealed significant heterogeneous treatment effects across claimants. Claimants predicted to behave unethically by the algorithm were more likely to disclose earnings when receiving a message relative to a control condition, with claimants predicted to most likely behave unethically being almost twice as likely to disclose earnings when shown a message. In addition to providing a potential blueprint for targeting more costly interventions, our study offers a novel perspective for the use and efficiency of data science in the public sector without violating citizens’ agency. However, we caution that, while algorithms can enable tailored policy, their ethical use must be ensured at all times.

Dark patterns that manipulate consumer behaviour are now a pervasive feature of digital markets. Depending on the choice architecture utilised, they can affect the perception, behaviour and purchasing patterns of online consumers. Using a novel empirical design, we find strong evidence that individuals across all groups are susceptible to dark patterns, and only weak evidence that user susceptibility is materially affected by commonly used general proxies for consumer vulnerability (such as income, educational attainment or age). Our conclusions provide empirical support for broad restrictions on the use of dark patterns, such as those contained in the EU’s Digital Services Act, that protect all consumer groups. Our study also finds that added friction, in the form of required payment action following successful deployment of dark patterns, reduces their effectiveness. This insight highlights the instances in which dark patterns would be most effective – when no further action is required by the user. Consumer vulnerability is therefore more pronounced when dealing with online providers who store users’ payment details and can rely on a ‘single click’ to complete the purchase.

This essay is a write-up of my Professorial Inaugural Lecture, delivered at the London School of Economics on 9 December 2024. Herein, I describe how I became involved and have helped develop the field of behavioural public policy (BPP). I detail how the intellectual architecture of BPP – its journal, Annual International Conference and Association – came into existence, and allude to my hopes for how the field might develop as we go forward.

This paper critically assesses Rizzo and Whitman’s theory of inclusive rationality in light of the ongoing cross-disciplinary debate about rationality, welfare analyses and policy evaluation. The paper aims to provide three main contributions to this debate. First, it explicates the relation between the consistency conditions presupposed by standard axiomatic conceptions of rationality and the standards of rationality presupposed by Rizzo and Whitman’s theory of inclusive rationality. Second, it provides a qualified defence of the consistency conditions presupposed by standard axiomatic conceptions of rationality against the main criticisms put forward by Rizzo and Whitman. And third, it identifies and discusses specific strengths and weaknesses of Rizzo and Whitman’s theory of inclusive rationality in the context of welfare analyses and policy evaluation.

This essay is in celebration of the contributions of Mario Rizzo. I argue that among contemporary economists in the Austrian School of Economics tradition it is Rizzo that advanced, more than his contemporaries, the scientific research program of rational choice as if the choosers were human beings; the dynamic subjectivism and the agony of choice and social interaction; the causal processes and the institutional dynamics that make up a complex social order; and the role of law, politics and civil society in shaping commercial life. In making this argument, I attempt to arbitrage the contributions of two essays of Rizzo’s: ‘Law Amid Flux’ and ‘The Genetic-Causal Tradition and Modern Economic Theory’.

Safety villages are interventions that aim to boost children's knowledge and behaviour regarding risk-taking behaviours and their consequences via an experiential learning approach. In safety villages, children experience scenarios involving risks that resemble real-life situations. We investigated the extent to which desirable learning outcomes from a single-session safety village visit are visible outside the safety village context. In a well-powered quasi-experimental preregistered field study, we compared students (aged 11–13) who received experiential safety education to a control group of students who had not yet received the education on three important learning outcomes: Knowledge-application, risk-taking behaviour and general risk-taking tendencies. Data were collected outside of the safety village environment, before or after the visit, and without explicit reminders of the visit. Results show students who received experiential safety education outperformed those who did not yet receive experiential education on knowledge-application and reduced risk-taking behaviours. We found no differences on general risk-taking tendencies. These results show a single visit to a safety village visit can reduce risk-taking of risks that were experienced in the village, but not general risk-taking tendencies. Theoretical and policy implications are discussed.

Viewed from the perspective of public policy, behavioural public policy (BPP) faces challenges in four main areas: Systems, Impatience, Nudging, and Scaling. To address these challenges, several suggestions are proposed. First, understanding how BPP interventions unfold in complex systems requires better diagnostics and the development of predictive and generative models of human behaviour. Second, the rapid pace of policy processes necessitates a shift towards generating timely and fit-for-purpose evidence. Third, maximising the opportunities presented by BPP, beyond merely ‘nudging’, demands the early and proactive application of behavioural science in the policy cycle. Fourth, achieving widespread impact in BPP initiatives means considering scale-up from the start. Lastly, the consistent and comprehensive integration of behavioural science into standard policymaking practices would support sustainable progress in addressing these challenges.

This special issue explores foundational questions in behavioral economics and behavioral public policy, drawing on the work of Mario Rizzo, a critical voice in the debate on behavioral paternalism. Behavioral economics has offered significant insights into decision-making, often challenging traditional economic models. However, it has also introduced normative frameworks into policy analysis, such as preference purification, that critics argue oversimplify human decision-making and risk imposing external values. Contributions to this issue examine themes including the tension between standard rationality and inclusive rationality, the epistemological limitations of paternalistic interventions, and the role of tacit knowledge and dynamic learning in policymaking. By engaging perspectives from economics, psychology, philosophy, and law, the issue discusses process-based approaches to policy analysis that respect individual agency and accommodate uncertainty. It also highlights the political economy dimensions of behavioral public policy, emphasizing the need for institutional reforms that enable learning and systematic change rather than narrowly focusing on individual cognitive biases. This issue serves as both a tribute to Mario Rizzo’s intellectual contributions and a call for a deeper reflection on the methodological and normative foundations of behavioral public policy.

Pro-environmental behavior, including waste sorting and recycling, involves a combination of future-oriented (futureness) and other-oriented (otherness) attributes. Inspired by the perspective of intergenerational choice, this work explores whether eliciting concerns for future others could increase public support for recycling policy and recycling behavior. Study 1 consisted of an online random controlled trial and a laboratory experiment. In Study 1A (N = 400), future other-concern was primed using a static text manipulation, whereas in Study 1B (N = 192), a dynamic virtual manipulation was employed. The results showed that people in the conditions that elicited future other-concern reported greater household recycling intentions and more actual recycling behavior than those in the control conditions. Study 2A (N = 467) and Study 2B (N = 600) generalized this effect on the acceptance of the ‘Certain Time Certain Place’ waste sorting policy in China. Consistent with the intergenerational choice model, envisioning the future of subsequent generations is more impactful in gaining policy approval than merely envisioning a future time. These findings provide a new method for promoting public policy approval and recycling behavior, suggesting that people could become environmentally friendly when they are guided to consider future others.

Despite a long history of research on democratic backsliding, the process itself − in which the executive branch amasses power and undermines democratic processes and institutions − remains poorly understood. We seek to shed light on the underlying mechanisms by studying democratic near misses: cases in which a period of autocratic governance is quickly reversed or full backsliding is prevented at the last minute. Building on the literature on near misses in sociotechnical systems such as nuclear power plants, we adapt the drift-to-danger model to the study of democratic systems. Two key findings emerge: First, democratic backsliding is often triggered by political elites pushing the boundaries of their power by violating norms, which are crucial yet vulnerable safeguards for democracy. Second, democratic backsliding is unpredictable and non-linear, being driven by the interaction between political elites and the public. Norm-violating elites may feel legitimized by a supportive public that sees norm violations as justified. At the same time, political elites may signal that norm-violating behaviour is acceptable, potentially leading the public to adopt anti-democratic beliefs and behaviours. We identify risk factors that make norm violations more likely and outline behavioural sciences-based interventions to address these violations.

Developing countries, with limited monitoring and auditing capabilities, face significant tax evasion issues. This study examines the impact of various text message combinations on promoting tax compliance, particularly in encouraging service providers to submit monthly sales tax returns in Khyber Pakhtunkhwa, Pakistan. A randomised controlled trial involved 18,087 service providers and tested three types of SMS reminders. These included a basic reminder for the due date, a reciprocity message emphasising social responsibility, and a loss aversion (LA) message highlighting financial penalties and deactivation. Subsequently, service providers who didn’t file on time received one of three warning messages. These warnings included a basic alert about potential legal action, financial penalties, and deactivation, as well as a message framing continued non-compliance as an active choice (AC). Overall, the interventions did not significantly influence tax filing behaviour beyond basic reminders and warnings. However, compliance improved for early registrants with the LA reminder and AC warning, and these results were robust to multiple hypothesis testing corrections. Compliance worsened for recent registrants in all combinations except the LA reminder and AC warning. These findings suggest that targeted low-cost messages that convey vague threats can improve tax compliance among certain taxpayer groups.

Indoor air pollution is one of the leading causes of morbidity and mortality worldwide, but its sources and impacts are largely misunderstood by the public. In a randomised controlled trial including 281 households in France, we test two interventions aimed at changing indoor polluting behaviour by raising households’ awareness of health risks associated with indoor air pollution. While both generic and personalised information increased knowledge, only personalised information including social comparison feedback changed behaviour, leading to a reduction of indoor PM2.5 (particulate matter with an aerodynamic diameter ≤2.5 µm) emissions by 20% on average. Heterogeneous treatment effects show that this effect is concentrated on the most polluted households at baseline, for whom the reduction reaches 40%.

In this paper, we revisit the Knowledge Problem addressed by Hayek eight decades ago and emphasised more recently by Rizzo and Whitman in their critique of the new paternalist approach of mainstream behavioural economics promoted by Sunstein and Thaler. We do this in light of the work of Michael Polanyi. Polanyi developed a theory of knowledge which has some commonalities with Hayek’s but also departs from it by emphasising the tacit, personal and perceptual dimensions of any process of knowing, thus radically renouncing any attempt of a knowledge typology separating different types of tacit knowledge (TK) and even denying that general knowledge could exist independently of TK.

In 1921, John Maynard Keynes and Frank Knight independently insisted on the importance of making a distinction between uncertainty and risk. Keynes referred to matters about which ‘there is no scientific basis on which to form any calculable probability whatever’. Knight claimed that ‘Uncertainty must be taken in a sense radically distinct from the familiar notion of Risk, from which it has never been properly separated’. Knightian uncertainty exists when people cannot assign probabilities to imaginable outcomes. People might know that a course of action might produce bad outcomes A, B, C, D and E, without knowing much or anything about the probability of each. Contrary to a standard view in economics, Knightian uncertainty is real, and it poses challenging and unresolved issues for decision theory and regulatory practice. It bears on many problems, potentially including those raised by artificial intelligence. It is tempting to seek to eliminate the worst-case scenario, and thus to adopt the maximin rule, which might seem to be the appropriate approach under Knightian uncertainty. But serious problems arise if eliminating the worst-case scenario would (1) impose high risks and costs, (2) eliminate large benefits or potential ‘miracles’ or (3) create uncertain risks.

Following the growing interest in using behavioral theory and choice architecture in the public sector, several new studies have looked at how changes in the choice architecture of budget simulations influence the participants’ budgetary decisions. These studies have also introduced the possible problem that participants may make inappropriate choices in the budget simulation, like creating a budget with unacceptably high budget surpluses. Building on Thaler and Sunstein’s NUDGES framework, we seek to answer the question, ‘How can budgetary choice architects correct for errors such as large ending surpluses at the end of the budget simulation?’ We replicate earlier results on budget starting conditions. Additionally, we test a budget treatment that encourages participants to reduce ending budget surpluses. The budget treatment works as intended and suggests that the large ending budget surpluses stem from errors made by participants in the simulation rather than loss aversion. The need to both nudge and budge participants is important for practicing choice architects, like public budgeters who have to design and implement tools that inform citizens and reveal accurate preferences that conform with legal requirements.

Small and medium-sized enterprises constitute the largest share of companies in most economies. As major resource users and significant contributors to environmental pollution, they are relevant targets for public policy programs aimed at increasing sustainability. We study how ‘sludge’ – small frictions in the choice architecture – can impact the uptake and effectiveness of such public policy programs targeted at SMEs. To this end, we conducted a field experiment within an existing policy program designed to support SMEs in implementing cost-effective environmental management practices. We manipulated the process of receiving free green items intended to support the implementation of those environmentally friendly practices within firms. We find that sludge, in the form of minor additional effort required to order the items, substantially undermined the program’s effectiveness. These results have important implications for policymakers: even minor sludge in the choice architecture can seriously impair the effectiveness of public policy programs targeted at companies.

A core normative assumption of welfare economics is that people ought to maximise utility and, as a corollary of that, they should be consistent in their choices. Behavioural economists have observed that people demonstrate systematic choice inconsistences, but rather than relaxing the normative assumption of utility maximisation they tend to attribute these behaviours to individual error. I argue in this article that this, in itself, is an error – an ‘error error’. In reality, a planner cannot hope to understand the multifarious desires that drive a person’s choices. Consequently, she is not able to discern which choice in an inconsistent set is erroneous. Moreover, those who are inconsistent may view neither of their choices as erroneous if the context reacts meaningfully with their valuation of outcomes. Others are similarly opposed to planners paternalistically intervening in the market mechanism to correct for behavioural inconsistencies, and advocate that the free market is the best means by which people can settle on mutually agreeable exchanges. However, I maintain that policymakers have a legitimate role in also enhancing people’s agentic capabilities. The most important way in which to achieve this is to invest in aspects of human capital and to create institutions that are broadly considered foundational to a person’s agency. However, there is also a role for so-called boosts to help to correct basic characterisation errors. I further contend that government regulations against self-interested acts of behavioural-informed manipulation by one party over another are legitimate, to protect the manipulated party from undesired inconsistency in their choices.

During the Cold War, logical rationality – consistency axioms, subjective expected utility maximization, Bayesian probability updating – became the bedrock of economics and other social sciences. In the 1970s, logical rationality underwent attack by the heuristics-and-biases program, which interpreted the theory as a universal norm of how individuals should make decisions, although such an interpretation is absent in von Neumann and Morgenstern’s foundational work and dismissed by Savage. Deviations in people’s judgments from the theory were thought to reveal stable cognitive biases, which were in turn thought to underlie social problems, justifying governmental paternalism. In the 1990s, the ecological rationality program entered the field, based on the work of Simon. It moves beyond the narrow bounds of logical rationality and analyzes how individuals and institutions make decisions under uncertainty and intractability. This broader view has shown that many supposed cognitive biases are marks of intelligence rather than irrationality, and that heuristics are indispensable guides in a world of uncertainty. The passionate debate between the three research programs became known as the rationality wars. I provide a brief account from the ‘frontline’ and show how the parties understood in strikingly different ways what the war entailed.

Since the emergence of psychological and behavioural science, one of its foundational goals has been to explain human behaviour. Although the discipline has been highly successful in this endeavour, there is an elephant in the room. Psychological and behavioural science has neglected studying the most challenging aspect of human behaviour−transformative behavioural change. This change can be described as a fundamental and difficult-to-achieve shift in someone’s actions that involves a transformation of one’s way of living. Understanding transformative behavioural change is essential not only for psychological and behavioural science to accomplish its foundational goal but also to maintain its contemporary relevance. Indeed, it is imminent that both solving the world’s biggest issues (e.g., climate change) and living through major disruptions (e.g., technological revolution) will require people to transform their behaviour. In this perspective, I first review and discuss previous relevant research, and then propose a seven-step agenda for how psychological and behavioural science can become the science of transformative behavioural change.