Tax Knowledge and Tax Manipulation: A Unifying Model
We provide a unified analysis of taxation and taxpayer education when individuals have an incomplete understanding of a complex tax system. The analysis is independent of whether income is earned legitimately, or by avoiding or evading taxes. In this sense, learning about tax minimization strategies (tax manipulation) is isomorphic to learning about tax rates. The government in our model balances a trade-off: A better understanding of the tax system potentially allows taxpayers to optimize more effectively, but also affects government revenue. Optimal taxpayer education and the optimal amount of redistribution can both be characterized by aggregate sufficient statistics, which do not require information about how biases or behavioral responses vary across the decision margins. We provide similarly simple rules for how tax rates on different income-generating activities should be set relative to each other.
We are grateful to Antoine Ferey, Nathan Hendren, Jim Hines, Louis Kaplow, Kai Konrad, Kory Kroft, John Leahy, Dylan Moore, Christian Moser, Alex Rees-Jones, and Nicolas Werquin for comments and suggestions, as well as seminar participants at LSE, Oxford, Princeton University, Tsinghua University, the Office of Tax Policy Research M-TAXI 2021 Conference, the Online Public Finance Seminar, the National Tax Association, and the Paris Tax Workshop. Financial support from the University of Michigan is gratefully acknowledged. There are no other sources of research support to disclose. The views expressed herein are those of the authors and do not necessarily reflect the views of the National Bureau of Economic Research.