Abstract 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.

Abstract 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. (JEL E21, G51, H21, H24)

Taxation affects the allocation of talented individuals across professions by blunting material incentives and thus magnifying nonpecuniary incentives of pursuing a “calling.” Estimates from the literature suggest that high-paying professions have negative externalities, whereas low-paying professions have positive externalities. A calibrated model therefore prescribes negative marginal tax rates on middle-class incomes and positive rates on the rich. The welfare gains from implementing such a policy are small and are dwarfed by the gains from profession-specific taxes and subsidies. These results depend crucially on externality estimates and labor substitution patterns across professions, both of which are very uncertain given existing empirical evidence.