This paper analyzes the optimal taxation of married couples. We develop a tax perturbation approach that decomposes the efficiency costs of jointness reforms into a tagging gain from conditioning on spousal income and a secondary distortion from the endogeneity of that income. We show that starting from a separable, revenue-maximizing tax schedule, introducing negative jointness weakly increases tax revenue whenever the joint income distribution is right-tail increasing, a condition satisfied by most commonly used copula families. Using U.S. data on married couples, we show that under a Rawlsian welfare criterion, secondary earners should face marginal tax rates 10–20% lower than primary earners at the same income level. For more general welfare functions, the optimal degree of jointness varies with the planner's preferences: negative jointness becomes optimal over a larger income range when marginal social welfare weights decline quickly and are small for households where at least one spouse is income-rich.

I study optimal nonlinear income taxation and education subsidies in a labor market where education increases the precision of productivity signals observed by employers. More precise signals improve employers’ inferences and task assignment, raising output and wages and making the earnings distribution more informative about workers’ underlying earning potential. Because the government cannot tax ability directly and must rely on income as a proxy, this generates an information externality: education tightens the link between income and ability, relaxing the planner’s informational constraint and improving the efficiency of redistribution. I show that incorporating this channel calls for higher education subsidies to encourage investments that improve signal precision and matching, and allows more progressive taxation since redistribution can be implemented more efficiently when income better reflects ability.

Progressive taxes redistribute income from the rich to the poor, but also provide income insurance by redistributing income from periods of high income to periods of low income within the life-cycle of an individual taxpayer. This paper provides a framework for characterizing and measuring this insurance value. I provide a novel Slutsky-style decomposition of individual-level welfare impacts of tax changes when there is income uncertainty. Using this decomposition, I characterize optimal taxes with both redistributive preferences and uncertainty and the MVPF of tax reforms under income uncertainty. I estimate the ex-ante MVPF of marginal tax increases at different points of the income distribution for the United States. The results indicate that when the insurance value is taken into account, the efficiency losses of tax increases are lower than otherwise, and those losses are decreasing rather than increasing with income.

When should governments sacrifice production efficiency for redistribution? We generalize the celebrated result of Diamond and Mirrlees (1971a,b) by allowing for imperfect competition, suboptimal and nonlinear taxation. We demonstrate that production efficiency hinges on the flexibility of the tax system in compensating gains and losses from changes in factor prices. This requires the tax system to target each factor’s income. We show how to adjust tax systems or production policies for imperfect targeting and market failures, even when the tax system is not flexible enough. We then obtain new sufficient statistics formulas. Endogenous factor prices do not modify the test to identify Pareto-improving tax reforms.