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.

Traditionally, corruption is seen as a rational pursuit of profit, focusing on personal gain. However, this view overlooks other influences. This paper focuses on the behavioral aspects of corruption, providing a deeper understanding of its complexities, and addressing the factors overlooked by conventional approaches. Reviewing some of the literature, we highlight how researchers have approached corruption from the perspective of behavioral sciences. Additionally, we examine how the emerging discipline of Behavioral Public Policy (BPP) employs innovative methods to reduce corrupt practices, offering new strategies that transcend traditional perspectives. Our paper innovates by demonstrating how corruption can be reduced by substituting traditional regulations with nonregulatory tools like nudges and sludge audits, or by leveraging digital choice architectures to minimize human-to-human interactions, known corruption enablers. By reducing regulations and administrative red tape, and introducing digital frameworks, these tools simplify processes minimizing opportunities for corrupt behavior. In this paper, we aim to infuse corruption research with a behavioral twist, a digital approach, and a deregulatory perspective, offering policymakers an alternative path to foster transparency, accountability and ethical governance. While this approach will not completely eradicate corruption, it strives to show how BPP can reduce its occurrences.

In this paper, I pick up on an important theme in Mario Rizzo’s work: that rationality should be understood more broadly than the rational choice model as learning to adjust behaviour in the light of experience and the mistakes that it yields. In particular, I focus on learning-by-doing (LBD). I argue in the first part of the paper that it should be regarded as one of the central insights in economics, alongside those that are more usually recognised like the gains from trade and the importance of unintended consequences. I use Smith and Hirschman’s discussion of LBD to ground this claim. In the second part of the paper, I turn to the determinants of LBD in teams. I argue that the key rule or constitutional/policy design question is how best to embrace the diversity that is central to LBD within teams without this undermining the social origins of co-operation in teams.

We have previously argued thatbehavioral scientists have been testing and advocating individualistic (i-frame) solutions to policy problems that have systemic (s-frame) causes and require systemic solutions. Here, we consider the implications of adopting an s-frame approach for research. We argue that an s-frame approach will involve addressing different types of questions, which will, in turn, require a different toolbox of research methods.

There are both negative and positive stereotypes about public sector workers. Most studies focus on negative stereotypes, like the idea that public servants are lazy. We, however, do the opposite. We focus on a positive stereotype: public sector workers are seen as caring and helpful. We test the effects of positive stereotypes on the quality of public service delivery. Using a pre-registered audit experiment in elderly care in the Netherlands and Belgium, we find that activating a pro-social stereotype does not affect the outcome of public service quality in terms of response rate and information provision. However, it does improve the bureaucratic process: public sector workers are friendlier toward citizens. They say around 12% more ‘thank you’ in their replies. Moreover, the citizens’ gender affects the response rate: female citizens receive around 10% more replies. Concluding, we show that positive stereotyping can improve parts of the quality of public service delivery but not all.

While in his early years, Kahneman followed the world of classic utilitarianism in which smart individuals base decisions on how they will truly feel each moment in the future, Kahneman in Mandel (2018) adopted a very different position, namely that what matters is the story people tell of their lives. He thus grappled with evolving stories of both the future and the past, and the presence of different decision-supporting evaluations for the short-run and the long-run.

In March 2024, Daniel Kahneman – the man who did perhaps more than anyone else to shape the field of behavioural public policy – died. He is among a small handful of scholars who have had a huge effect on my own career, and in this essay – the first in a series of essays in a special section of the Journal that honour him – I reflect on how his work inspired much of my own.

To improve public health and promote environmental sustainability, widespread dietary changes are necessary in high-income countries. However, adopting and maintaining dietary goals is challenging and requires repeated self-regulation. Effective public policies can facilitate healthy food choices and reduce the likelihood of goal failure. This study examines the relationship between individuals’ dietary goal failures and their acceptance of public food policies, using data from an experience-sampling study (Ni = 409 and Nobs = 6,447). Regression analyses revealed that participants who experienced more frequent dietary goal failures were generally less accepting of health-promoting food policies and perceived them as less effective. Additionally, perceived policy effectiveness positively predicted policy acceptance. Exploratory analyses showed that the negative relationship between dietary goal failure and food policy acceptance varied depending on the type of intervention (pull policies vs push policies) and the location of food selections (home vs out-of-home). Notably, we found a positive relationship between dietary goal failure and acceptance of pull policies for food selections made out-of-home. These findings highlight the importance of better understanding the complex interplay between public policy attitudes, the food environment and adherence to dietary goals.