We study optimal tax and educational policies in a dynamic private information economy, in which ex-ante heterogeneous individuals make an educational investment early in their life and face a stochastic wage distribution. We characterize labor and education wedges in this setting analytically...

We study Pareto optimal tax and education policies when human capital upon labor market entry is endogenous and individuals face wage uncertainty. Though optimal labor distortions are history-dependent, i.e. depend on income and education, simple policy instruments can yield the desired...

We study the incidence and the optimal design of nonlinear income taxes in a Mirrleesian economy with a continuum of endogenous wages. We characterize analytically the incidence of any tax reform by showing that one can mathematically formalize this problem as an integral equation. For a CES...

We study the optimal design of student financial aid as a function of parental income. We derive optimal financial aid formulas in a general model. For a simple model version, we derive mild conditions on primitives under which poorer students receive more aid even without distributional...

We analyze Pareto-efficient tax deduction rules for work-related expenses (e.g. housekeeping services, child care or elderly care). Pareto efficiency dictates a tight rule for how the rate of deductibility should vary with income and expenditures. An immediate implication is a recipe for...

We analyze Pareto-efficient tax deduction rules for work-related expenses. Pareto efficiency dictates a strict rule for marginal deductions along the income distribution. An immediate implication is a recipe for designing Pareto-improving reforms. We apply our theory and simulate a...

We analyze Pareto-efficient tax breaks for work-related expenses in a Mirrleesian environment. Individuals are heterogenous in their ability. In addition to a labor-leisure choice, they decide how to spend their money between normal consumption and work-related goods. We derive an efficiency...