Methods from CS have enabled new understanding of topics in game theory and economics, but have been explored only for a small collection of subareas of game theory and economics. There may be opportunities more broadly and especially in areas that computer scientists would not naturally explore on their own. The following workshop is a coordinated effort of AGT researchers and economists in the Cambridge area to explore possible interactions more broadly. Feel free to attend if you are in the Cambridge area; if not you may find the format interesting. The official announcement follows.
Reverse AGT Workshop on Optimal Taxation
Harvard U, 20 University Road, Room 646
1-4pm, Monday, November 24, 2014
At the Reverse AGT Workshop local economists will present an area of economic study for an algorithmic game theory (AGT) audience. The presentations will include a brief introduction to the area and several current research topics. The schedule includes ample time for discussion to make connections to related research in AGT and to highlight research questions that methods from AGT might help to answer. The topic of the first workshop is Optimal Taxation and it is organized by Glen Weyl, Brendan Lucier, and Jason Hartline.
1:00: Glen Weyl: Introduction to Optimal Redistributive Taxation
1:30: Q/A and discussion
1:45: Stefanie Stantcheva: Approximating Optimal Tax Systems
2:15: Q/A and discussion
2:30: Benjamin Lockwood: Optimal Income Taxation with Misoptimizing Consumers
3:00: Q/A and discussion
3:15: Coffee and cookies
3:45: Summary discussion and closing comments
Introduction to Optimal Redistributive Taxation
Glen Weyl (Microsoft Research and U. of Chicago)
I will give a brief introduction to the theory of utilitarian optimal redistributive taxation proposed by Vickrey (1945) based on insurance behind the veil of ignorance. I will mostly focus on the types of models studied and results obtained, rather than on techniques used. I will discuss the veil of ignorance argument for utilitarianism, the optimal linear income tax, the nonlinear income tax problem, the optimal top tax rate, the Atkinson Stiglitz theorem, tagging, the taxation of leisure complements and, briefly, a few more recent results that I find particularly interesting.
Approximating Optimal Tax Systems
Stefanie Stantcheva (Harvard Economics)
In this talk, I will highlight how complex dynamic optimal tax systems are in realistic settings. I will show how economists have tried to simplify the optimal systems numerically. I will then argue that it is crucial to have a theory of approximation of optimal tax systems that can be applied in a consistent manner to different environments and tax problems. I will propose directions along which to think about this and present the beginning of the work I am doing on this.
Optimal Income Taxation with Misoptimizing Consumers
Benjamin Lockwood (Harvard Business School)
This paper studies optimal redistributive income taxation in the presence of psychological frictions. We augment familiar formulas for optimal taxes using “sufficient statistics” for misoptimization, which abstract from the underlying behavioral model generating misoptimization. We show that corrections are likely to be strongest at the bottom of the income distribution, and we clarify conditions under which the planner should work to correct or exacerbate misoptimization. Finally, we show how this approach can be implemented empirically, using reduced-form evidence about responses to the Earned Income Tax Credit to estimate the degree of misoptimization. Simulations suggest that this type of misoptimization generates substantial optimal work subsidies for low income individuals. Joint with Dmitry Taubinsky.