There is an inherent conflict between the political marketing model of humans and pioneering theories in electoral behavior research. While political marketing logic implies an issue-based and highly volatile voting behavior, voting theories conventionally assume that positional issues have little effect on how individuals vote, and so parties have little incentive to develop issue-based electoral strategies. However, few people would challenge the role that marketing now plays in the modern campaign process. How can we reconcile these theories? This paper revisits the role and impact of positional issues on voting behavior by testing whether specific issues affect different subgroups of voters as contended by the ‘issue-public’ theory. The results show that previous models underestimate issue voting. Once measurement accuracy is improved and the salience-based heterogeneity of issue effects is taken into consideration, positional issues have non-negligible effects on individual vote choice. Furthermore, salience-based heterogeneity is shown to explain better the variation in issue voting than heterogeneity based on political sophistication.

Widespread testing is key to controlling the spread of COVID-19. But should we worry about self-selection bias in the testing? The recent literature on willful ignorance says we should – people often avoid health information. In the context of COVID-19, such willful ignorance can bias testing data. Furthermore, willful ignorance often arises when selfish wants conflict with social benefits, which might be particularly likely for potential ‘super-spreaders’ – people with many social interactions – given people who test positive are urged to self-isolate for two weeks. We design a survey in which participants (n = 897) choose whether to take a costless COVID-19 test. We find that 70% would take a test. Surprisingly, the people most likely to widely spread COVID-19 – the extraverts, others who meet more people in their daily lives and younger people – are the most willing to take a test. People's ability to financially or emotionally sustain self-isolation does not matter to their decision. We conclude that people are selfless in their decision to test for COVID-19. Our results are encouraging – they imply that COVOD-19 testing may succeed in targeting those who generate the largest social benefits from self-isolation if infected, which strengthens the case for widespread testing.

In a large study that involved 2637 participants recruited from a representative UK and US sample, we tested the influence of four behavioural interventions (versus control) on a range of behaviours important for reducing the spread of COVID-19 a day after the interventions were administered. Even if people largely complied with social distancing measures, our analyses showed that for certain subgroups of the population the interventions made a positive difference. More specifically, for those who started practising social distancing relatively recently, an information-based intervention increased general compliance with social distancing and reduced both the number of times people went out and the number of hours they spent outside. However, for people who started practising social distancing relatively early, the interventions tended to backfire and, in some cases, reduced compliance with social distancing. Overall, this research has various policy implications and shows that, although behavioural interventions can positively impact compliance with social distancing, their effect may depend on personal circumstances.

Policymakers are increasingly turning to insights gained from the experimental method as a means to inform large-scale public policies. Critics view this increased usage as premature, pointing to the fact that many experimentally tested programs fail to deliver their promise at scale. Under this view, the experimental approach drives too much public policy. Yet, if policymakers could be more confident that the original research findings would be delivered at scale, even the staunchest critics would carve out a larger role for experiments to inform policy. Leveraging the economic framework of Al-Ubaydli et al. (2019), we put forward 12 simple proposals, spanning researchers, policymakers, funders and stakeholders, which together tackle the most vexing scalability threats. The framework highlights that only after we deepen our understanding of the scale-up problem will we be on solid ground to argue that scientific experiments should hold a more prominent place in the policymaker's quiver.

Global climate change is the largest existential threat of our time. Glaciers are retreating, sea levels are rising, extreme weather is intensifying and the last four years have been the hottest on record (NASA, 2020; World Meteorological Organization, 2020). Although climate change is already significantly impacting natural and human systems around the world, mitigating further and potentially disastrous climate change will require large-scale individual and collective action, including public support for mitigation policies, as well as the more rapid development and implementation of adaptation plans (van der Linden et al., 2015; Pearson et al., 2016).

Few Americans demand that their local policy-makers take action to address the effects of large earthquakes, even in ‘high-risk’ areas. This poses an important political problem. If policy-makers do not perceive a mandate to prepare for catastrophe, certain areas of the country may be vulnerable to loss of life and economic productivity. Why do Americans not demand more from their policy-makers? We propose a simple answer – many Americans do not accurately appraise the likelihood that they will experience a major earthquake. In a unique survey of West Coast adults, we compared respondents’ perceived likelihood of experiencing a major earthquake to their actual geocoded hazard. We uncover a wide disconnect between actual and perceived earthquake hazard, even in areas where earthquakes are comparatively more common. Critically, and in contrast to previous public policy research, we show that threats in the physical environment can shape policy opinion, but only under certain circumstances. We show that accurate appraisals of hazard significantly increase the likelihood that respondents will support preventative local policy measures. Our results shed new light on the opinion dynamics of public attitudes toward natural disasters and ameliorative policy efforts and highlight the policy importance of communicating earthquake hazard to at-risk constituencies.

This paper highlights factors that need to be considered for improving the National Flood Insurance Program in the USA to address the biases that lead individuals to not protect themselves against low-probability, high-consequence flood events. The errors that individuals exhibit in deciding not to purchase insurance or invest in loss reduction measures prior to a disaster can be traced to the effects of six biases: myopia, amnesia, optimism, inertia, simplification and herding. Along with two guiding principles for insurance, a behavioral risk audit can assist in designing a strategy using concepts from choice architecture coupled with economic incentives to encourage property owners in hazard-prone areas to purchase insurance and invest in cost-effective adaptation measures to protect themselves against future disaster losses.

Al-Ubaydli et al. provide a far-reaching, insightful and directly actionable analysis of how social-behavioral research may exert more influence over the development and implementation of public policy. Their paper offers a sophisticated understanding of the ‘scale-up effect’, or factors that influence the extent to which positive experimental effects replicate as an intervention is implemented more broadly. Using economic principles, models and analyses, they offer 12 proposals for improving the process of scaling up effective and policy-relevant interventions. The current paper outlines how their proposals share a number of complementary features with behavioral psychology and applied behavior analysis. This response considers three possible points of intersection: (1) perspectives on the importance and challenges of studying and controlling our own behavior; (2) approaches to determining the social value of intervention outcomes and the procedures for achieving them; and (3) recommendations for deploying meaningful, common measures across phases of research.

One way to reduce waste and to make a system more robust is to allow its components to pool resources. For example, banks might insure each other or share a common capital reserve. Systems whose resources have been pooled in this way are highly prevalent in such diverse domains as finance, infrastructure, health care, emergency response and engineering. However, these systems have a combination of characteristics that leave them vulnerable to poor decision-making: non-linearity of risk; obvious rewards combined with hidden costs; and political and market incentives that encourage inadequate safety margins. Three studies demonstrate a tendency for managers of such systems to underestimate the probability of cascading failures. We describe a series of behaviorally based policy interventions to mitigate the resulting hazards.

The behavioral sciences were there at the beginning of the systematic study of climate change. However, in the ensuing quarter century, they largely faded from view, during which time public discourse and policy evolved without them. That disengagement and the recent reengagement suggest lessons for the future role of the behavioral sciences in climate science and policy. Looking forward, the greatest promise lies in projects that make behavioral science integral to climate science by: (1) translating behavioral results into the quantitative estimates that climate analyses need; (2) making climate research more relevant to climate-related decisions; and (3) treating the analytical process as a behavioral enterprise, potentially subject to imperfection and improvement. Such collaborations could afford the behavioral sciences more central roles in setting climate-related policies, as well as implementing them. They require, and may motivate, changes in academic priorities.

To help people make informed decisions, policy-makers often require entities to provide consumers with informational materials known as disclosures. However, it is unclear whether consumers pay attention to disclosures. In two experiments where we manipulate the delivery of disclosures, we find that the mere presence of an observer negatively affects attention to disclosures, while introducing a mandatory waiting period after receiving a disclosure increases attention. In a third study, we analyze more than 3000 surveys answered by recent mortgage borrowers. Borrowers who report receiving disclosures at mortgage closing meetings (which are often attended by multiple stakeholders) are less likely to have questions about their disclosures than those who receive disclosures beforehand, suggesting differential attention. Our findings demonstrate that both mandatory waiting periods and the presence of observers can affect consumers’ attention to disclosures. We discuss implications of our research for policies designed to promote informed consumer decision-making.

For educational researchers, Al-Ubaydli et al. raise a crucial question: How can the science of scaling experimental innovations contribute to school improvement? By assessing how particular innovative programs work, why, for whom and under what conditions, experimenters test theories: about how children and youth learn, about how adults can collaborate to create the required learning opportunities and about how policy can supply the required incentives and resources to support such effective collaboration. My focus in this response article thus shifts from the perspective of innovators who hope to scale their interventions to the perspective of practitioners who face the challenge of adopting, adapting or borrowing ideas from experimental studies and harmonizing those ideas with expert clinical judgment.

Five experiments are reported to compare models of attitude formation about hot-button policy issues like climate change. In broad strokes, the deficit model states that incorrect opinions are a result of a lack of information, while the cultural cognition model states that opinions are formed to maximize congruence with the group that one affiliates with. The community of knowledge hypothesis takes an integrative position. It states that opinions are based on perceived knowledge, but that perceptions are partly determined by the knowledge that sits in the heads of others in the community. We use the fact that people's sense of understanding is affected by knowledge of others’ understanding to arbitrate among these views in the domain of public policy. In all experiments (N = 1767), we find that the contagious sense of understanding is nonpartisan and robust to experimental manipulations intended to eliminate it. While ideology clearly affects people's attitudes, sense of understanding does as well, but level of actual knowledge does not. And the extent to which people overestimate their own knowledge partly determines the extremity of their position. The pattern of results is most consistent with the community of knowledge hypothesis. Implications for climate policy are considered.

Four experiments examine how lack of awareness of inequality affect behaviour towards the rich and poor. In Experiment 1, participants who became aware that wealthy individuals donated a smaller percentage of their income switched from rewarding the wealthy to rewarding the poor. In Experiments 2 and 3, participants who played a public goods game – and were assigned incomes reflective of the US income distribution either at random or on merit – punished the poor (for small absolute contributions) and rewarded the rich (for large absolute contributions) when incomes were unknown; when incomes were revealed, participants punished the rich (for their low percentage of income contributed) and rewarded the poor (for their high percentage of income contributed). In Experiment 4, participants provided with public education contributions for five New York school districts levied additional taxes on mostly poorer school districts when incomes were unknown, but targeted wealthier districts when incomes were revealed. These results shed light on how income transparency shapes preferences for equity and redistribution. We discuss implications for policy-makers.

Very often, significantly smaller benefits are observed in final policy outcomes than are indicated by initial research discoveries. Al-Ubaydli et al. have identified a poor understanding of the ‘science of scaling’ as the underlying cause of this discrepancy. They propose a framework to increase our understanding of the science of scaling. We build on this framework by making six specific suggestions capturing three key ideas. First, researchers need to move away from their preoccupation with general theoretical models and focus on subject-specific theories of intervention, leading to individualized treatments. Second, there should be greater collaboration between researchers and policymakers, as well as more transparency in reporting findings, to ensure that the research environment is more representative of the policy environment. Third, researchers should recognize that policymakers do not always maximize social welfare; policymakers may have their own short-term incentives. Therefore, researchers must consider policymakers’ short-term incentives in designing interventions in order to increase the chances of a research intervention becoming a policy.

Reducing global warming will require enacting strong climate policies, which is unlikely to happen without public support. While prior research has identified varied predictors of climate change policy support, it is unclear which predictors are strongest for the American electorate as a whole, and which predictors are strongest for Democrats and Republicans. In a nationally representative sample of registered voters (n = 2063), we use relative weight analysis to identify the strongest predictors of public climate policy support. We find that, among registered voters in the USA, the five most important predictors of climate policy support are: worry about global warming; risk perceptions; certainty that global warming is happening; belief that global warming is human-caused; and general affect toward global warming. Collectively, these five variables account for 51% of the variance in policy support. Results split by political party indicate that pro-climate injunctive norms and global warming risk perceptions are the variables that differ most between Republicans and Democrats, accounting for significantly more variance in policy support among Republicans. These findings can inform policymakers and advocates seeking to build public support for climate action.

We asked individuals about their willingness to pay (WTP) either: (1) for a mandate requiring restaurants to post calorie information on their menus; or (2) to avoid such a mandate. On average, more people were in in favor of the mandate and were willing to pay four times more than those who were against it, thereby leading to a Kaldor–Hicks improvement from this policy. To ensure robustness, we tested the impact of providing three types of information during individuals’ WTP determinations: (1) visual examples of the proposed calorie labels; (2) data on their effectiveness at the individual level; and (3) data on their wider social and economic benefits. For those in favor, providing a simple visual of the label had no impact on WTP. Data on the individual effectiveness of the labels increased the WTP, while evidence on broader obesity reduction and economic benefits reduced it. For opponents, WTP did not change with provision of additional information except when provided with information on social and economic benefits. Under this condition, the opponents increased their WTP 12-fold to avoid a mandate of this policy. Finally, we measured individual well-being under this policy and found directionally similar results, confirming a net improvement in aggregate welfare. Our results suggest that messaging that focuses on private benefits (providing calorie information so that individuals can effectively choose to reduce excessive caloric consumption) rather than wider public benefits (reduction in overall health-related costs and obesity) is more likely to be effective.