







Sustaining large-scale public goods requires individuals to make environmentally friendly decisions today to benefit future generations1–6. Recent research suggests that second-order normative beliefs are more powerful predictors of behaviour than first-order personal beliefs7,8. We explored the role that second-order normative beliefs—the belief that community members think that saving energy helps the environment—play in curbing energy use. We first analysed a data set of 211 independent, randomized controlled trials conducted in 27 US states by Opower, a company that uses comparative information about energy consumption to reduce household energy usage (pooled N = 16,198,595). Building off the finding that the energy savings varied between 0.81% and 2.55% across states, we matched this energy use data with a survey that we conducted of over 2,000 individuals in those same states on their first-order personal and second-order normative beliefs. We found that second-order normative beliefs predicted energy savings but first-order personal beliefs did not. A subsequent pre-registered experiment provides causal evidence for the role of second-order normative beliefs in predicting energy conservation above first-order personal beliefs. Our results suggest that second-order normative beliefs play a critical role in promoting energy conservation and have important implications for policymakers concerned with curbing the detrimental consequences of climate change.
Overcoming Salience Bias: How Real-Time Feedback Fosters Resource Conservation
Inattention and imperfect information bias behavior toward the salient and immediately visible. This distortion creates costs for individuals, the organizations in which they work, and society at large. We show that an effective way to overcome this bias is by making the implications of one’s behavior salient in real time, while individuals can directly adapt. In a large-scale field experiment, we gave participants real-time feedback on the resource consumption of a daily, energy-intensive activity (showering). We find that real-time feedback reduced resource consumption for the target behavior by 22%. At the household level, this led to much larger conservation gains in absolute terms than conventional policy interventions that provide aggregate feedback on resource use. High baseline users displayed a larger conservation effect, in line with the notion that real-time feedback helps eliminate “slack” in resource use. The approach is cost effective, is technically applicable to the vast majority of households, and generated savings of 1.2 kWh per day and household, which exceeds the average energy use for lighting. The intervention also shows how digitalization in our everyday lives makes information available that can help individuals overcome salience bias and act more in line with their preferences. This paper was accepted by Uri Gneezy, behavioral economics.

Ten Brighter Ideas? An Explorable Explanation
As with many areas of public interest, the common wisdom surrounding energy conservation consists of myths and legends, rules of thumb and superstitions. We're given guidelines as soundbites, catchy but insubstantial. We trust them blindly, not knowing whether our actions make any significant impact.
What Would You Do with $500? Spending Responses to Gains, Losses, News, and Loans
Abstract We use survey questions about spending in hypothetical scenarios to investigate features of propensities to consume that are useful for distinguishing between consumption theories. We find that (1) responses to unanticipated gains are vastly heterogeneous (either zero or substantially positive); (2) responses increase in the size of the gain, driven by the extensive margin of spending adjustments; (3) responses to losses are much larger and more widespread than responses to gains; and (4) even those with large responses to gains do not respond to news about future gains. These four findings suggest that limited access to disposable resources, and frictions in adjusting consumption, are important determinants of consumption behaviour. We also find that (5) households do not respond to the offer of a one-year interest-free loan, suggesting that this is not a consequence of short-term credit constraints; and (6) people do cut spending in response to news about future losses, suggesting that neither is this a consequence of myopia. A calibrated precautionary savings model with utility costs of changing consumption, and a sufficient fraction of low-wealth households, can account for these features of propensities to consume on both the extensive and intensive margins.

Eliciting Beliefs with Random Generation Tasks
Elicitation methods, such as asking people to produce the deciles of a distribution, are standard practices in policy or applied statistics. Similarly, much of cognitive science and psychology focuses on determining people's people's beliefs or latent traits through questionnaires or judgment tasks. However, these approaches often only capture a rough outline of what people know and are usually limited to point estimates of people's beliefs. Here, we present a novel experimental paradigm that allows us to access people's beliefs and how variable these beliefs are. Our task is based on an established random generation paradigm in which participants produce quantities from a particular domain as randomly as possible. We hypothesize that due to the minds' general-purpose mechanisms for probabilistic inferences, these random sequences represent the participants' underlying prior beliefs. We show that our method can infer participants' beliefs for a wide range of numeric quantities at comparable accuracy as an established elicitation method. Moreover, these inferred beliefs are consistent with individual participants' generalization and inference patterns in a subsequent conditional prediction task. We then extend our approach to non-numeric belief elicitation, highlighting how our method can go beyond numeric elicitation and provide insight into complex beliefs that are challenging to assess experimentally. Empirically, our results highlight that people know the rough shapes of environmental distributions, and these beliefs guide inference and generalization. Moreover, using our novel approach, we also show that people know the fine details of environmental distributions. Finally, our experimental results show that random generation paradigms can be a useful tool for cognitive scientists, psychologists, and applied statisticians.
Ditch the niceties in AI prompts to save energy use, say researchers
A UN report warns of the rapid growth in AI energy consumption, but suggests users can improve efficiency by making prompts more concise

Save More Today or Tomorrow: The Role of Urgency in Precommitment Design
To encourage farsighted behaviors, previous research suggests that marketers should invite consumers to precommit to adopting these behaviors “later.” However, the authors propose that people will draw different inferences from different types of precommitment offers, and that these inferences can help explain when precommitment is (and is not) effective at increasing adoption of farsighted behaviors. Specifically, the authors theorize that simultaneously offering consumers the opportunity to adopt a farsighted behavior now or later (i.e., offering “simultaneous precommitment”) may signal that the behavior is not urgently recommended; however, offering consumers the opportunity to adopt that behavior immediately and then, only if they decline, inviting them to adopt it later (i.e., offering “sequential precommitment”) may signal just the opposite. In a multisite field experiment (N = 5,196), the authors find that simultaneously giving consumers the chance to increase their savings now or later reduced retirement savings. Two preregistered lab studies (N = 5,080) show that simultaneous precommitment leads people to infer that taking action is not urgently recommended, and such inferences predict less adoption of recommended behaviors. Importantly, offering sequential precommitment increases inferred urgency, predicting greater adoption. Together, this research advances knowledge about the limits and potential of precommitment.

Self-Control and Optimal Goals: A Theoretical Analysis
Consumers set goals to achieve a variety of objectives such as losing weight, saving for retirement, and achieving better health. A large body of literature in psychology and consumer behavior shows that goals can help consumers achieve these objectives. However, there is almost no research that examines how we should set optimal goals. The purpose of this paper is to develop a parsimonious framework that examines how goals can help performance and how we should set optimal goals. We use the literature on hyperbolic discounting to model these issues. Our results show that goals can often increase performance but can also sometimes encourage procrastination. We show that some goals are worse than having no goals, even when the goals are achieved and the consumer exerts more effort because of the goal. We also find that the presence of goals can lead to myopic consumers behaving as if they were hyperopic. Our results also show that the most difficult goals should be assigned to consumers with moderate levels of motivation and self-control problems. We also find that it is sometimes optimal to set goals that are never achieved.

Consumers’ Mental Representation of Expenditures: Implications for Spending and Savings Decisions
Abstract People’s mental representation of expenditures is crucial to their budgeting. This article proposes that much like how they represent natural kinds (e.g., animals and plants), people represent expenditures in a hierarchical taxonomy. Seven studies, supported by six norming studies and three pilots, revealed that expenditures are represented hierarchically. We first recover people’s mental representations using a successive pile-sort method that asks people to form hierarchies of categories with common expenditures (e.g., rent, dining out, etc.). The pile-sort reveals consensus in people’s representations of expenditures and that these representations are relatively stable over time. Further, people’s adjustment in their spending behavior can be predicted by the distance between items in their representation. Specifically, when people overspent on an item, they spontaneously adjust spending more on taxonomically closer items. We examine this spontaneous adjustment behavior using both laboratory studies and field data with 6.5 million grocery shopping trips over 12 years. The findings highlight the connection between mental representation and consumer behavior, and they emphasize the importance of studying concepts and categories in the context of consumption.

Behavioural economics, consumer behaviour and consumer policy: state of the art
Counter to the traditional assumption of neoclassical economics that individuals are rational Homo oeconomici that always seek to maximize their utility and follow their ‘true’ preferences, research in behavioural economics has demonstrated that people's judgements and decisions are often subject to systematic biases and heuristics, and are strongly dependent on the context of the decision. In this article, we briefly review the transition of research from neoclassical economics to behavioural economics, and discuss how the latter has influenced research in consumer behaviour and consumer policy. In particular, we discuss the impacts of key principles such as status quo bias, the endowment effect, mental accounting and the sunk-cost effect, other heuristics and biases related to availability, salience, the anchoring effect and simplicity rules, as well as the effects of other supposedly irrelevant factors such as music, temperature and physical markers on consumers’ decisions. These principles not only add significantly to research on consumer behaviour – they also offer readily available practical implications for consumer policy to nudge behaviour in beneficial directions in consumption domains including financial decision making, product choice, healthy eating and sustainable consumption.

Resource-rational belief revision can mitigate as well as amplify polarization
People's beliefs sometimes diverge after observing the same information, which has been interpreted as evidence of irrationality. This behaviour has been proposed to result from people's limited cognitive resources and motivated reasoning, but how belief revision differs across these explanations has not been formalized or compared to a rational norm. Further, while people may be biased relative to a normative ideal, they may still make optimal choices given their limited cognitive resources, or rationally balance the utility of holding accurate beliefs with the belief's intrinsic utility. Across two studies, we develop and test a unified computational account of belief polarization under these proposed mechanisms, showing that people's performance on a belief updating task best fits a limited-resource Bayesian model; external motivations may contribute to divergence (or convergence) by determining what pre-existing information people consider relevant to a situation, rather than by changing how people evaluate new information in isolation.
The i-frame and the s-frame: How focusing on individual-level solutions has led behavioral public policy astray
An influential line of thinking in behavioral science, to which the two authors have long subscribed, is that many of society's most pressing problems can be addressed cheaply and effectively at the level of the individual, without modifying the system in which the individual operates. We now believe this was a mistake, along with, we suspect, many colleagues in both the academic and policy communities. Results from such interventions have been disappointingly modest. But more importantly, they have guided many (though by no means all) behavioral scientists to frame policy problems in individual, not systemic, terms: To adopt what we call the “i-frame,” rather than the “s-frame.” The difference may be more consequential than i-frame advocates have realized, by deflecting attention and support away from s-frame policies. Indeed, highlighting the i-frame is a long-established objective of corporate opponents of concerted systemic action such as regulation and taxation. We illustrate our argument briefly for six policy problems, and in depth with the examples of climate change, obesity, retirement savings, and pollution from plastic waste. We argue that the most important way in which behavioral scientists can contribute to public policy is by employing their skills to develop and implement value-creating system-level change.

Knowing When to Spend: Unintended Financial Consequences of Earmarking to Encourage Savings
Maintaining savings is an important financial goal. Yet there are times when savings should be spent, such as when people face unavoidable costs, and spending their savings allows them to avoid high interest rate debt. Existing behavioral research has focused on consumer decisions between savings and discretionary spending and has proposed interventions to promote savings in these contexts. However, when spending is not discretionary, such interventions could risk exacerbating a pattern found in economic research in which people borrow high interest rate debt while maintaining savings that earn low levels of interest. To examine how mental accounting interacts with considerations of personal responsibility and guilt to contribute to this pattern, this article explores whether people spend their savings when they need money most: during emergencies. Six studies reveal that people's tendency to preserve savings by borrowing from a high interest rate credit option varies as a function of the savings’ intended use. Paradoxically, people are most likely to turn to high interest rate credit with the belief that doing so is the responsible option.

Anticipation and Choice Heuristics in the Dynamic Consumption of Pain Relief
Humans frequently need to allocate resources across multiple time-steps. Economic theory proposes that subjects do so according to a stable set of intertemporal preferences, but the computational demands of such decisions encourage the use of formally less competent heuristics. Few empirical studies have examined dynamic resource allocation decisions systematically. Here we conducted an experiment involving the dynamic consumption over approximately 15 minutes of a limited budget of relief from moderately painful stimuli. We had previously elicited the participants’ time preferences for the same painful stimuli in one-off choices, allowing us to assess self-consistency. Participants exhibited three characteristic behaviors: saving relief until the end, spreading relief across time, and early spending, of which the last was markedly less prominent. The likelihood that behavior was heuristic rather than normative is suggested by the weak correspondence between one-off and dynamic choices. We show that the consumption choices are consistent with a combination of simple heuristics involving early-spending, spreading or saving of relief until the end, with subjects predominantly exhibiting the last two.
Characterizing the causes, dynamics, and consequences of choice deferral
The fact that people often avoid making decisions is well known, and past research has helped to identify some of the conditions and reasons for doing so. For instance, people may forgo choices between bad options because they prefer not to end up with one of those options. It is much less clear when and why people avoid choosing in cases where they eventually will have to make a given decision. To study such instances of choice deferral, we presented participants with a series of choices, and for each choice they were allowed to either choose immediately or defer the decision until later in the experiment. Across six experiments and three choice domains (choices among consumer goods, artwork, and political candidates), we find that the strongest predictor of choice deferral is the overall value of a given set of options, with relative value (i.e., how hard it is to identify the best option) counterintuitively playing a smaller role. We show that the influence of overall value on choice deferral can be accounted for by a dynamic decision model according to which participants appraise the option set relative to a criterion before deciding whether to choose or defer, comparing this to a previous model whereby participants make such a decision based on a predetermined decision time limit. We further reveal that the influence of overall value on choice deferral is determined by how congruent options are with a given choice goal (choose-best or choose-worst) rather than simply how bad those options are. Collectively, our findings shed new light on how people decide to put off the inevitable.
Misunderstanding Savings Growth: Implications for Retirement Savings Behavior
People systematically underestimate exponential growth. This article illustrates this phenomenon, its implications, and some potential interventions in the context of saving for retirement, where savings grow exponentially over long periods of time. Experiment 1 shows that a majority of participants expect savings over 40 years to grow linearly rather than exponentially, leading them to grossly underestimate their account balance at retirement. Experiment 2 demonstrates that this misunderstanding leads to underestimates of the cost of waiting to save, which makes putting off saving more attractive than it should be. Finally, Experiments 3–5 show that highlighting the exponential growth of savings motivates both college students and employees to save more for retirement. Making clear to employees the exponential growth of savings before they make crucial decisions about how much to save may be a simple and effective means of increasing retirement savings.

The Benefits of Emergency Reserves: Greater Preference and Persistence for Goals that Have Slack with a Cost
Marketers of programs that are designed to help consumers reach goals face dual challenges of making the program attractive enough to encourage consumer signup while still motivating consumers to reach desirable goals and thus stay satisfied with the program. The authors offer a possible solution to this challenge: the emergency reserve, or slack with a cost. They demonstrate how an explicitly defined emergency reserve not only is preferred over other options for goal-related programs but can also lead to increased persistence. Study 1 demonstrates that consumers prefer programs with emergency reserves to programs that do not have them, and Study 2 further clarifies that consumers' preference for an emergency reserve depends on the presence of a superordinate goal. Study 3 reveals that consumers prefer goals with emergency reserves because they perceive them to have both higher attainability and value than other goals. Study 4 demonstrates that reserves can lead to increased goal persistence in a realistic task that involves persistence over time. Finally, Studies 5 and 6 reveal that consumers persist more with reserve goals because they want to avoid using the “emergency” reserve.
