Speaker:Mikhail Golosov (Yale Department of Economics)

Venue:           MNB-Visitor Centre

Time:             15.15 pm, Wednesday, June 16,2010

We (the authours) develop a methodology to derive formulas that facilitate interpretation of the forces determining the optimal labor and savings distortions as well as taxes in dynamic settings. The formulas for the labor wedges extend the static optimal taxation analysis of (Diamond

1998) and (Saez 2001) to dynamic settings. Compared to the static analysis, the dynamic nature of the problem offers three novel insights.

First, the opportunity to provide incentives dynamically adds a force lowering labor distortions. Second, labor distortions in dynamic settings may differ significantly from those in static settings because a key determinant of the former is the conditional rather than the unconditional distribution of skill shocks. The conditional distribution of shocks differs significantly from the unconditional one. Third, the persistence of shocks manifests itself as an increase in the redistributionary motive of the government. Finally, we derive a novel formula to analyze the determinants of the savings distortions.

Our second set of results is to numerically simulate the optimal labor and savings distortions. The analysis is conducted for a realistically calibrated economy based on the empirical income distributions. The computed optimal dynamic distortions differ significantly from the optimal static distortions, highlighting the importance of the forces in the theoretical analysis. The welfare gain of switching from an optimal static system to the dynamic one is large.

Our third contribution is a novel implementation of the optimal allocations. We show that a tax system based on consolidated income accounts (CIA) implements the optimum. The labor income tax depends on the current labor income and on the balance on the CIA. The savings tax depends only on the amount of savings. The CIA balance is updated as a function of the labor income and the previous balance.