Following the seminal work of Mirrlees (REStud, 1971), there has been a large amount of work on how to design an optimal tax system when agents' skills are private information. This literature makes a strong assumption: it assumes that the data generation process for skills in the economy is...

This paper studies dynamic non-linear taxation in a two-period model without government commitment and a continuum of agents with privately known skill parameters, which are constant overtime. The government is utilitarian but cannot commit at t=1 to the tax scheme that she will propose at t=2....

We study the optimal Mirrlees taxation problem in a dynamic economy with idiosyncratic (productivity or preference) shocks. In contrast to the standard approach, which implicitly assumes that the mechanism is operated by a benevolent planner with full commitment power, we assume that any...

This paper considers the existence of bad equilibria in a random auditing tax model with limits on the number of households which can be audited. Specifically, we present sufficient conditions for a tax-audit mechanism which has truth telling as one equilibrium to have other equilibiria in which...

In this paper we address the time-inconsistency of optimal debt policy—the incentive for a current government to “manipulate interest ratesâ€â€”raised in Lucas and Stokey’s celebrated 1983 paper. The literature that followed suggested various ways to fully overcome...

Where the state evolves according to a discrete-state Markov chain, we sustain Lucas and Stokey's debt structure dynamics by having it emerge sequentially as the unique outcome of a sequence of choices made by two sequences of independent government departments. Each period a tax authority sets...

All developed countries have government debt, usually a sizeable proportion of output. This paper proposes that governments that cannot commit to future policy choices face a trade-off that explains the level of debt. On the one hand, the government would like to increase debt and delay...