Imperfect information and inattention to energy costs are important potential motivations for energy efficiency standards and subsidies. We evaluate these motivations in the lightbulb market using a theoretical model and two randomized experiments. We derive welfare effects as functions of reduced-form sufficient statistics capturing economic and psychological parameters, which we estimate using a novel within-subject information disclosure experiment. The main results suggest that moderate subsidies for energy-efficient lightbulbs may increase welfare, but informational and attentional biases alone do not justify a ban on incandescent lightbulbs. Our results and techniques generate broader methodological insights into welfare analysis with misoptimizing consumers.

This paper shows that accounting for variation in mistakes can be crucial for welfare analysis. Focusing on consumer underreaction to not-fully-salient sales taxes, we show theoretically that the efficiency costs of taxation are amplified by differences in underreaction across individuals and across tax rates. To empirically assess the importance of these issues, we implement an online shopping experiment in which 2,998 consumers purchase common household products, facing tax rates that vary in size and salience. We replicate prior findings that, on average, consumers underreact to non-salient sales taxes-consumers in our study react to existing sales taxes as if they were only 25% of their size. However, we find significant individual differences in this underreaction, and accounting for this heterogeneity increases the efficiency cost of taxation estimates by at least 200%. Tripling existing sales tax rates nearly doubles consumers' attention to taxes, and accounting for this endogeneity increases efficiency cost estimates by 336%. Our results provide new insights into the mechanisms and determinants of boundedly rational processing of not-fully-salient incentives, and our general approach provides a framework for robust behavioral welfare analysis.

A common objection to “sin taxes”—corrective taxes on goods that are thought to be overconsumed, such as cigarettes, alcohol, and sugary drinks—is that they often fall disproportionately on low-income consumers. This paper studies the interaction between corrective and redistributive motives in a general optimal taxation framework and delivers empirically implementable formulas for sufficient statistics for the optimal commodity tax. The optimal sin tax is increasing in the price elasticity of demand, increasing in the degree to which lower-income consumers are more biased or more elastic to the tax, decreasing in the extent to which consumption is concentrated among the poor, and decreasing in income effects, because income effects imply that commodity taxes create labor supply distortions. Contrary to common intuitions, stronger preferences for redistribution can increase the optimal sin tax, if lower-income consumers are more responsive to taxes or are more biased. As an application, we estimate the optimal nationwide tax on sugar-sweetened beverages, using Nielsen Homescan data and a specially designed survey measuring nutrition knowledge and self-control. Holding federal income tax rates constant, our estimates imply an optimal federal sugar-sweetened beverage tax of 1 to 2.1 cents per ounce, although optimal city-level taxes could be as much as 60% lower due to cross-border shopping.

A corrective tax or subsidy is “well-targeted” if it primarily affects choices that are more distorted by market failures. Energy efficiency subsidies are designed to correct multiple distortions: externalities, credit constraints, “landlord-tenant” information asymmetries, imperfect information, and inattention. We show that three important energy efficiency subsidies are primarily taken up by consumers who are wealthier, own their own homes, and are more informed about and attentive to energy costs. This suggests that these subsidies are poorly targeted at the market failures they were designed to address. However, we show that “tagging” can lead to large efficiency gains.

We study how people’s beliefs about the economy covary with household-level events, utilizing a unique link between Danish administrative data and a large-scale survey of consumer expectations. We find that compared to actual inflation, people’s inflation forecasts covary much more strongly (and negatively) with both recently realized household income changes and measures of expected future household income changes. We formally establish that these findings are stark deviations from the Bayesian rational expectations benchmark. Similar results hold for perceptions of past inflation (“backcasts” ), suggesting that imperfect recall is a key mechanism for biased forecasts. Building on this, a series of additional tests, some of which utilize data on adverse health events, suggests that the forecast biases are at least partly due to affect-cued recall. That is, negative (positive) household-level events cue negative (positive) recollections, which lead to pessimistic (optimistic) forecasts.

We use natural experiments embedded in state-run lotteries and a new nationally representative survey to provide reduced-form and structural estimates of risk preferences and behavioural biases in lottery demand, and to explore the implications for optimal lottery design. We find that sales respond more to the expected value of the jackpot than to price but are unresponsive to variation in the second prize—a pattern that is consistent with probability weighting but is inconsistent with standard parameterizations. In the survey, we find that lottery spending decreases modestly with income and is strongly associated with measures of innumeracy, poor statistical reasoning, and other proxies for behavioural bias, which also decline with income. Regression predictions suggest that Americans would spend 43% less on lotteries if they were unbiased, while the remaining lottery demand is due to other factors such as anticipatory utility or entertainment value. We use these empirical moments to estimate a model of socially optimal lottery design. In the model, current multi-state lottery designs increase welfare but may harm heavy spenders.

This paper provides empirically implementable sufficient statistics formulas for optimal nonlinear tax systems in the presence of across-income heterogeneity in preferences, inheritances, income-shifting capabilities, and other sources. We characterize optimal smooth tax systems on income and savings (or other commodities), as well as simpler tax systems. We use familiar elasticity concepts and a novel sufficient statistic for heterogeneity correlated with earnings ability: the difference between across-income variation in savings and the causal effect of income on savings. We apply these formulas to the United States and find that the optimal savings tax is mostly positive and progressive.

This article investigates whether offers of commitment contracts, in the form of self-imposed choice-set restrictions and penalties with no financial upside, are well-targeted tools for addressing self-control problems. In an experiment on gym attendance (N=1,248), we examine take-up of commitment contracts and also introduce a separate elicitation task to identify actual and perceived time inconsistency. There is high take-up of commitment contracts for greater gym attendance, resulting in significant increases in exercise. However, this take-up is influenced both by noisy valuation and incorrect beliefs about one’s time inconsistency. Approximately half of the people who take up commitment contracts for higher gym attendance also take up commitment contracts for lower gym attendance. There is little association between commitment contract take-up and reduced-form and structural estimates of actual or perceived time inconsistency. A novel information treatment providing an exogenous shock to awareness of time inconsistency reduces demand for commitment contracts. Structural estimates of a model of quasi-hyperbolic discounting and gym attendance imply that offering our commitment contracts lowers consumer surplus and is less socially efficient than utilizing linear exercise subsidies that achieve the same average change in behaviour.

This paper develops and deploys a methodology for testing whether people correctly value tools that reduce attention costs. We call these tools bandwidth enhancements (BEs) and characterize how demand for BEs varies with the pecuniary incentives to be attentive, under the null hypothesis of correct perceptions and optimal choice. We examine if the theoretical optimality conditions are satisfied in three experiments. The first is a field experiment ( n = 1373) with an online education platform, in which we randomize incentives to complete course modules and incentives to utilize a plan‐making tool to complete the modules. In the second experiment ( n = 2306), participants must complete a survey in the future. We randomize survey‐completion incentives and how long participants must wait to complete the survey, and we elicit willingness to pay for reminders. The third experiment ( n = 1465) involves a psychometric task in which participants must identify whether there are more correct or incorrect mathematical equations in an image. We vary incentives for accuracy, elicit willingness to pay to reduce task difficulty, and examine the impact of learning and feedback. In all experiments, demand for reducing attention costs increases as incentives for accurate task completion increase. However, in all experiments—and across all conditions—our tests imply that this increase in demand is too small relative to the null of correct perceptions. These results suggest that people may be uncertain or systematically biased about their attention cost functions, and that experience and feedback do not necessarily eliminate bias.