New Research

Alan J. auerbach, Laurence J. Kotlikoff, Darryl Koehler

This study combines the 2013 Federal Reserve Survey of Consumer Finances data and the Fiscal Analyzer, a highly detailed life-cycle consumption-smoothing program, to a) measure ultimate economic inequality – inequality in lifetime spending power – within cohorts, b) assess fiscal progressivity within cohorts, c) calculate marginal remaining lifetime net tax rates, taking into account all major federal and state tax and transfer policies, d) evaluate the ability of current income to correctly classify households as rich, middle class, and poor, e) determine whether current-year average net tax rates accurately capture actual fiscal progressivity, and f) determine whether current-year marginal tax rates on labor supply accurately capture actual remaining lifetime marginal net tax rates.

We find far less inequality in spending power than in wealth or labor earnings due to the fiscal system’s high degree of progressivity. But U.S. fiscal redistribution generally comes with very high work disincentives for households of all ages, regardless of income class. There is, however, substantial dispersion in marginal net tax rates, which seems hard to reconcile with standard norms of optimal taxation. We also find that current income is a very poor proxy for remaining lifetime resources and that current-year net tax rates can provide a highly distorted picture of true fiscal progressivity and work disincentives.

Seth G. Benzella, Eugene Goryunov,b Maria Kazakovac, Guillermo Lagardad, Kristina Nesterovae, Laurence J. Kotlikofff, and Andrey Zubarevg

This paper develops a large-scale, dynamic life-cycle model to simulate Russia’s demographic and fiscal transition under favorable and unfavorable fossil-fuel price regimes. The model includes Russia, the U.S., China, India, the EU, and Japan+ (Japan plus Korea). The model predicts dramatic increases in tax rates in the U.S., EU, India, and Russia. Indeed, the increases are so large as to question their political feasibility let alone their actual collection given the potential for tax avoidance and evasion.

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Christian Baker, Jeremy Bejarano, Richard W. Evans, Kenneth L. Judd, Kerk L. Phillips

In this study, we characterize and demonstrate a solution method for an optimal commodity (sales) tax problem consisting of multiple goods, heterogeneous agents, and a nonconvex policy maker optimization problem. The contribution of our approach is to allow for more dimensions of heterogeneity than has been previously possible, to incorporate potential model uncertainty and policy objective uncertainty, and to relax some of the assumptions in the previous literature that were necessary to generate a convex optimization problem for the policy maker. Our solution technique involves creating a large database of optimal responses by different individuals for different policy parameters and using \big data” techniques to compute policy maker objective values over these individuals.

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Jasmina Hasanhodzic and Laurence J. Kotlikoff

Valuing future government spending commitments and tax receipts, whether they are sure or risky, is critical to assessing the sustainability of fiscal policy. If markets were complete it would be an easy matter to determine if the present value of projected spending exceeded the present value of projected receipts. But such markets don’t exist for numerous reasons including the inability of the living to trade with the unborn. Nor can one use prevailing security prices since they don’t span long-term states of nature let alone cover all relevant contingencies in the short and medium runs. How then should one value state-contingent government payments and taxes, or, equivalently, discount their expected values?

The approach taken here posits and simulates a ten-period overlapping generations model and uses it to determine the immediate payments – the compensating variations – agents would require to forego promised government future net payments. “Agents” include future generations who are assumed to discount their utility while alive for the number of years it will take for them to be born. Our metric for pricing the compensating variations is agents’ expected utility functions. I.e., we determine what immediate payment will deliver the same expected utility as the government’s promised net payments.