It is often argued that people might take on too much high-cost debt because they are present focused and/or over-optimistic about how soon they will repay. We measure borrowers’ present focus and over-optimism using an experiment with a large payday lender. Although the most inexperienced quartile of borrowers under-estimate their likelihood of future borrowing, the more experienced three quartiles predict correctly on average. This finding contrasts sharply with priors we elicited from 103 payday lending and behavioural economics experts, who believed that the average borrower would be highly overoptimistic about getting out of debt. Borrowers are willing to pay a significant premium for an experimental incentive to avoid future borrowing, which we show implies that they perceive themselves to be time inconsistent. We use borrowers’ predicted behaviour and valuation of the experimental incentive to estimate a model of present focus and naivete. We then use the model to study common payday lending regulations. In our model, banning payday loans reduces welfare relative to existing regulation, while limits on repeat borrowing might increase welfare by inducing faster repayment that is more consistent with long-run preferences.

This paper tests costly attention models of consumers' misreaction to opaque taxes. We report an online shopping experiment that involves shrouded sales taxes that are exogenously varied within consumers over time. Some consumers systematically underreact to sales taxes whereas others systematically overreact, but higher stakes decrease both under- and overreaction. This is consistent with consumers using heterogeneous rules of thumb to compute the opaque tax when the stakes are low, but using costly mental effort at higher stakes. The results allow us to differentiate between various theories of limited attention. We also develop novel econometric techniques for quantifying individual differences.

What mental models do individuals use to approximate their tax schedule? Using incentivized forecasts of the U.S. Federal income tax schedule, we estimate the prevalence of the “schmeduling” heuristics for constructing mental representations of nonlinear incentive schemes. We find evidence of widespread reliance on the “ironing” heuristic, which linearizes the tax schedule using one’s average tax rate. In our preferred specification, 43% of the population irons. We find no evidence of reliance on the “spotlighting” heuristic, which linearizes the tax schedule using one’s marginal tax rate. We show that the presence of ironing rationalizes a number of empirical patterns in individuals’ perceptions of tax liability across the income distribution. Furthermore, while our empirical framework accommodates a rich class of other misperceptions, we find that a simple model including only ironers and correct forecasters accurately predicts average underestimation of marginal tax rates. We replicate our finding of prevalent ironing, and a lack of other systematic misperceptions, in a controlled experiment that studies real-stakes decisions across exogenously varied tax schedules. To illustrate the policy relevance of the ironing heuristic, we show that it augments the benefits of progressive taxation in a standard model of earnings choice. We quantify these benefits in a calibrated model of the U.S. tax system.

We use public finance sufficient statistic approaches to characterize the welfare effects of “nudges,” such as simplified information and warning labels, in markets with taxes and endogenous prices. While many studies focus on average effects, we show that welfare also depends on how the nudge affects the variance of choice distortions, and average effects become irrelevant with zero pass-through or optimal taxes. We implement the framework with experiments evaluating automotive fuel economy labels and sugary drink health labels. Labels decrease purchases of low-fuel economy cars and sugary drinks but may decrease welfare because they increase the variance of choice distortions.

Public recognition is frequently used to motivate desirable behavior, yet its welfare effects—such as costs of shame or gains from pride— are rarely measured. We develop a portable empirical methodology for measuring and monetizing social image utility, and we deploy it in experiments on exercise and charitable behavior. In all experiments, public recognition motivates desirable behavior but creates highly unequal image payoffs. High-performing individuals enjoy significant utility gains, while low-performing individuals incur significant utility losses. We estimate structural models of social signaling, and we use the models to explore the social efficiency of public recognition policies.