Abstract We examine the health plan choices that 23,894 employees at a U.S. firm made from a large menu of options that differed only in financial cost-sharing and premium. These decisions provide a clear test of the predictions of the standard economic model of insurance choice in the absence of choice frictions because plans were priced so that nearly every plan with a lower deductible was financially dominated by an otherwise identical plan with a high deductible. We document that the majority of employees chose dominated plans, which resulted in excess spending equivalent to 24% of chosen plan premiums. Low-income employees were significantly more likely to choose dominated plans, and most employees did not switch into more financially efficient plans in the subsequent year. We show that the choice of dominated plans cannot be rationalized by standard risk preference or any expectations about health risk. Testing alternative explanations with a series of hypothetical-choice experiments, we find that the popularity of dominated plans was not primarily driven by the size and complexity of the plan menu, nor informed preferences for avoiding high deductibles, but by employees’ lack of understanding of health insurance. Our findings challenge the standard practice of inferring risk preferences from insurance choices and raise doubts about the welfare benefits of health reforms that expand consumer choice.
Can Consumers Make Affordable Care Affordable? The Value of Choice Architecture
Tens of millions of people are currently choosing health coverage on a state or federal health insurance exchange as part of the Patient Protection and Affordable Care Act. We examine how well people make these choices, how well they think they do, and what can be done to improve these choices. We conducted 6 experiments asking people to choose the most cost-effective policy using websites modeled on current exchanges. Our results suggest there is significant room for improvement. Without interventions, respondents perform at near chance levels and show a significant bias, overweighting out-of-pocket expenses and deductibles. Financial incentives do not improve performance, and decision-makers do not realize that they are performing poorly. However, performance can be improved quite markedly by providing calculation aids, and by choosing a “smart” default. Implementing these psychologically based principles could save purchasers of policies and taxpayers approximately 10 billion dollars every year.
The Oregon Health Insurance Experiment: Evidence from the First Year*
Abstract In 2008, a group of uninsured low-income adults in Oregon was selected by lottery to be given the chance to apply for Medicaid. This lottery provides an opportunity to gauge the effects of expanding access to public health insurance on the health care use, financial strain, and health of low-income adults using a randomized controlled design. In the year after random assignment, the treatment group selected by the lottery was about 25 percentage points more likely to have insurance than the control group that was not selected. We find that in this first year, the treatment group had substantively and statistically significantly higher health care utilization (including primary and preventive care as well as hospitalizations), lower out-of-pocket medical expenditures and medical debt (including fewer bills sent to collection), and better self-reported physical and mental health than the control group.
A Generalizable Scale of Propensity to Plan: The Long and the Short of Planning for Time and for Money
Abstract. Planning has pronounced effects on consumer behavior and intertemporal choice. We develop a six-item scale measuring individual differences in pr
Do Customers Learn from Experience? Evidence from Retail Banking
We study customers' adoption and subsequent switching decisions with regard to a menu of three-part tariff plans offered by a commercial bank. Using a rich panel data set covering 70,510 fee-based checking accounts over 30 months, before and after the introduction of the plans, we find that most customers adopt non-cost-minimizing plans, preferring plans with large monthly allowances and high fixed payments. Furthermore, after adoption, customers who exceed their allowances and consequently pay overage fees are more likely to switch to plans with larger allowances than customers who do not experience such fees. Notably, after switching, these overage-paying customers pay higher monthly payments than before. In contrast, switching customers who did not pay overage payments before switching pay less after switching. Our findings, unlike those of previous research on experience-based learning, suggest that the behavior of experienced customers does not converge to the predictions of neoclassical models. We propose that “overage aversion,” which is closely related to loss aversion and mental accounting, is the most plausible explanation for our findings. This paper was accepted by John List, behavioral economics.
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.
Behavioral Impediments to Valuing Annuities: Complexity and Choice Bracketing
Abstract This paper examines two behavioral factors that diminish people's ability to value a lifetime income stream or annuity, drawing on a randomized experiment with about 4,000 adults in a U.S. nationally representative sample. We find that increasing the complexity of the annuity choice reduces respondents' ability to value the annuity, measured by the difference between the sell and buy values they assign to the annuity. When we limit narrow choice bracketing by inducing people to think first about how quickly or slowly to spend down assets in retirement, their ability to value an annuity increases.
Behaviorally Informed Policies for Household Financial Decisionmaking
Low incomes, limited financial literacy, fraud, and deception are just a few of the many intractable economic and social factors that contribute to the financial difficulties that households face today. Addressing these issues directly is difficult and costly. But poor financial outcomes also result from systematic psychological tendencies, including imperfect optimization, biased judgments and preferences, and susceptibility to influence by the actions and opinions of others. Some of these psychological tendencies and the problems they cause may be countered by policies and interventions that are both low cost and scalable. We detail the ways that these behavioral factors contribute to consumers’ fiancial mistakes and suggest a set of interventions that the federal government, in its dual roles as regulator and employer, could feasibly test or implement to improve household financial outcomes in a variety of domains: retirement, short-term savings, debt management, the take-up of government benefits, and tax optimization.
The Exception Is the Rule: Underestimating and Overspending on Exceptional Expenses
Abstract Purchases fall along a continuum from ordinary (common or frequent) to exceptional (unusual or infrequent), with many of the largest expenses (e.g., electronics, celebrations) being the most exceptional. Across seven studies, we show that, while people are fairly adept at budgeting and predicting how much they will spend on ordinary items, they both underestimate their spending on exceptional purchases overall and overspend on each individual purchase. Based on the principles of mental accounting and choice bracketing, we show that this discrepancy arises in part because consumers categorize exceptional expenses too narrowly, construing each as a unique occurrence and consequently overspending across a series of discretely exceptional expenses. We conclude by proposing an intervention that diminishes this tendency by helping consumers consider their spending on exceptional items as part of a larger set of purchases.
The Realization Effect: Risk-Taking after Realized versus Paper Losses
Understanding how prior outcomes affect risk attitudes is critical for the study of choice under uncertainty. A large literature documents the significant influence of prior losses on risk attitudes. The findings appear contradictory: some studies find greater risk-taking after a loss, whereas others show the opposite—that people take on less risk. I reconcile these seemingly inconsistent findings by distinguishing between realized versus paper losses. Using new and existing data, I replicate prior findings and demonstrate that following a realized loss, individuals avoid risk; if the same loss is not realized, a paper loss, individuals take on greater risk.
Life insurance, loss aversion, and temporal orientation: a field experiment and replication with young adults
Young individuals rarely seek information about life insurance—a product that offers long-term benefits that might not motivate a desire to act now. Framing life insurance messaging as a gain in the present (e.g., “ensure your loved ones are protected today”) is thought to motivate younger individuals to seek information about insurance policies. A field experiment with a large life insurance issuer and a pre-registered experiment reveal that loss aversion and temporal orientation frames influences whether individuals aged 25–49 years shop for life insurance. Specifically, the results suggest that the superiority of gain frames over loss frames requires positioning the benefits well in the future, despite the need to act now. This study thus also contextualizes the realities and practical difficulty of framing financial products in ways that might interest a potentially vulnerable population.
A Framework for Studying AI Agent Behavior: Evidence from Consumer Choice Experiments
Environments built for people are increasingly operated by a new class of economic actors: LLM-powered software agents making decisions on our behalf. These decisions range from our purchases to travel plans to medical treatment selection. Current evaluations of these agents largely focus on task competence, but we argue for a deeper assessment: how these agents choose when faced with realistic decisions. We introduce ABxLab, a framework for systematically probing agentic choice through controlled manipulations of option attributes and persuasive cues. We apply this to a realistic web-based shopping environment, where we vary prices, ratings, and psychological nudges, all of which are factors long known to shape human choice. We find that agent decisions shift predictably and substantially in response, revealing that agents are strongly biased choosers even without being subject to the cognitive constraints that shape human biases. This susceptibility reveals both risk and opportunity: risk, because agentic consumers may inherit and amplify human biases; opportunity, because consumer choice provides a powerful testbed for a behavioral science of AI agents, just as it has for the study of human behavior. We release our framework as an open benchmark for rigorous, scalable evaluation of agent decision-making.
A Behavioral Model of Rational Choice
Abstract. Introduction, 99. — I. Some general features of rational choice, 100.— II. The essential simplifications, 103. — III. Existence and uniqueness of
Can Revealed Preferences Clarify LLM Alignment and Steering?
LLMs are increasingly used to make or support high-stakes decisions under uncertainty, where alignment depends not only on factual accuracy but on how models weigh tradeoffs between different outcomes. We present an empirical pipeline for estimating the implied preferences that an LLM's observed choices optimize: we elicit the model's probability distribution over unknowns along with the choice it would make for the decision task and then fit a discrete choice model to recover the cost function that best rationalizes the model's decisions. We show how this revealed-preference description allows rigorous evaluation of whether models behave in a consistently goal-directed way, whether they can verbalize a description of their objectives which matches their revealed decision policy, and whether prompting can reliably steer those policies to implement a user-specified cost function. We apply this evaluation across four medical diagnosis domains and multiple frontier and open-source models. We find that while many models have a nontrivial degree of internal coherence, they also have significant weaknesses in faithfully reporting or adopting preferences in response to user direction.
Consumer Spending during Unemployment: Positive and Normative Implications
Using de-identified bank account data, we show that spending drops sharply at the large and predictable decrease in income arising from the exhaustion of unemployment insurance (UI) benefits. We use the high-frequency response to a predictable income decline as a new test to distinguish between alternative consumption models. The sensitivity of spending to income we document is inconsistent with rational models of liquidity-constrained households, but is consistent with behavioral models with present-biased or myopic households. Depressed spending after exhaustion also implies that the consumption-smoothing gains from extending UI benefits are four times larger than from raising UI benefit levels. (JEL D14, D91, E21, E24, E70, J65)
5: Behavioural biases in personal finance
Behavioural economics merges psychology and economics to explore systematic deviations in financial decision-making from traditional economic models. This chapter examines key biases such as mental accounting, present bias, planning fallacy, and misunderstanding of risk, which influence spending, saving, investing, and insuring decisions. Demonstrating the interplay of cognitive biases and heuristics highlights why individuals make suboptimal choices despite financial literacy and resource capacity. Strategies like goal-setting, commitment devices, and education interventions are evaluated, focusing on their limitations and potential for addressing these biases. The chapter concludes by emphasising the need for systemic changes, such as policy-level interventions and financial regulation, to complement behavioural interventions and address structural barriers to better financial decisions. Future research directions are suggested, including tailoring interventions, exploring technology's role, and integrating systemic solutions to support sustainable financial well-being.
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.