Tuesday, July 26, 2022
Jeremy Bearer-Friend (George Washington; Google Scholar) received the Senior Paper Award for his article, Colorblind Tax Enforcement, 97 N.Y.U. L. Rev. 1 (2022), at the ComplianceNet Conference (program) held at the University of Amsterdam Law School earlier this month:
The United States Internal Revenue Service (IRS) has repeatedly taken the position that because the IRS does not ask taxpayers to identify their race or ethnicity on submitted tax returns, IRS enforcement actions are not affected by taxpayers’ race or ethnicity. This claim, which I call “colorblind tax enforcement,” has been made by multiple IRS Commissioners serving in multiple administrations (both Democratic and Republican). This claim has been made to members of Congress and to members of the press.
In this Article, I refute the IRS position that racial bias cannot occur under current IRS practices.
I do so by identifying the conditions under which race and ethnicity could determine tax enforcement outcomes under three separate models of racial bias: racial animus, implicit bias, and transmitted bias. I then demonstrate how such conditions can be present across seven distinct tax enforcement settings regardless of whether the IRS asks about race or ethnicity. The IRS enforcement settings ana- lyzed include summonses, civil penalty assessments, collection due process hear- ings, innocent spouse relief, and Department of Justice (DOJ) referrals.
By establishing that every major enforcement function of the IRS remains vulner- able to racial bias, this Article also challenges the IRS decision to omit race and ethnicity from the collection and analysis of tax data. The absence of publicly avail- able data on IRS enforcement activities by race should not be interpreted as evi- dence that no racial disparities exist. I conclude by describing alternative approaches to preventing racial bias in tax enforcement other than the current IRS policy of purported colorblindness.