Wednesday, July 01, 2015

New paper posted on SSRN

I have just posted on SSRN my draft paper, Taxing Potential Community Members' Foreign Source Income, which I wrote for a conference on citizenship and taxation that will be held at the University of Michigan Law School on October 9 of this year.  The paper is available for download here.

The abstract goes as follows:

Recent years have witnessed rising debate, on both sides of the Atlantic, regarding how to define the category of individuals whom a given country classifies as domestic taxpayers, and who thus may be taxable on their foreign source income (FSI) even if they live abroad.  While the United States rules focus distinctively on citizenship, the broader issue is better viewed as pertaining to the taxation of “potential community members” (PCMs) – that is, all those who plausibly might be viewed as members of the home community.

This paper makes two main points regarding the taxation of PCMs on their FSI.  First, the issues turn in large part on drawing a distinction between “us” and “them” – that is, between people whom we classify as members of the home community, and thus whose welfare we care about, and those whom we classify as normatively irrelevant (or less relevant) outsiders.  While such a distinction is inevitable in a world with separate national governments, conventional tax policy and public economics tools shed little direct light on how one might operationalize it.

Second, for PCMs whom a given country classifies as domestic taxpayers, past debate has over-focused on issues of mitigating “double taxation” through exemption or foreign tax credits.  It should instead focus distinctly on the questions of (a) how heavily or lightly one should tax domestic taxpayers’ FSI in particular cases, and (b) how foreign taxes paid should affect domestic liability.  Refocusing the analysis not only helps to inform one’s understanding of the choice between the two standard tools, but also may suggest considering blended approaches that might avoid the worst features of each.

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