Education, preferences for leisure, and the optimal income tax schedule

Recent advances in dynamic Mirrlees economies have incorporated the treatment of human capital investments as an important dimension of government policy. This paper adds to this literature by considering a two period economy where agents are di erentiated by their preferences for leisure and their productivity, both private information. The fact that productivity is only learnt later in an agent's life introduces uncertainty to agent's savings and human capital choices and makes optimal the use of multi-period tie-ins in the mechanism that characterizes the government policy. We show that optimal policies are often interim ine cient and that the introduction of these ine ciencies may take the form of marginal tax rates on labor income of varying sign and educational policies that include the discouragement of human capital acquisition. With regards to implementation, state-dependent linear taxes implement optimal savings, while human capital policies may require labor income taxes that depend directly on agents' schooling.

On the optimality of the Friedman Rule with heterogeneous agents and non-linear income taxation

We study the optimal “inflation tax” in an environment with heterogeneous agents and non-linear income taxes. We first derive the general conditions needed for the optimality of the Friedman rule in this setup. These general conditions are distinct in nature and more easily interpretable than those obtained in the literature with a representative agent and linear taxation. We then study two standard monetary specifications and derive their implications for the optimality of the Friedman rule. For the shopping-time model the Friedman rule is optimal with essentially no restrictions on preferences or transaction technologies. For the cash-credit model the Friedman rule is optimal if preferences are separable between the consumption goods and leisure, or if leisure shifts consumption towards the credit good. We also study a generalized model which nests both models as special cases.