Taxing data when the United States disagrees

Abstract What is the best way to tax data-driven business models without contravening the existing global quasi-constitutionalist order on tax, trade, and investment law? A number of countries in Europe and around the world have begun imposing standalone digital services taxes pending multilateral agreement on a coordinated reform of bilateral income tax treaties (aka the OECD-G20/Inclusive Framework’s ‘Pillar 1’). But if Pillar 1 fails to materialise and countries go forward with unilateral digital services taxes, the United States and U.S. firms will likely seek redress using domestic measures as well as trade and investment treaties where applicable. This Article argues that in the face of such U.S. resistance, EU member states and countries elsewhere ought to reconsider using the income tax system to achieve their goals instead. We first review the events that led countries to avoid the income tax in favour of standalone taxes only to become embroiled in domestic U.S. trade policies. We then explain how European and other source jurisdictions for business services related to data collection, mining, and commercialisation could revisit the income tax to get to the same tax base, namely by taking an ambulatory interpretation approach to provisions in existing tax treaties in a way that renders possible to accommodate withholding taxes on those services. We show that an ambulatory interpretation approach could achieve the underlying goals of taxing data-driven businesses, in some cases even without any domestic law or treaty reform, with treaty-based rules for dispute resolution a ready tool to draw upon if and when the United States disagrees.

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Institutions

Publication Details

Journal
European Law Open
Published
2024-12-01
DOI
https://doi.org/10.1017/elo.2024.49
Citations
3
Primary Topic
Gender, Labor, and Family Dynamics
Type
article
Field-Weighted Citation Impact
2.79

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article

Taxing data when the United States disagrees

Allison Christians, Tarcísio Diniz Magalhães
3 citations
European Law Open
Gender, Labor, and Family Dynamics
2.79
article

Taxing data when the United States disagrees

Allison Christians, Tarcísio Diniz Magalhães
article en
3 citations

Abstract

Abstract What is the best way to tax data-driven business models without contravening the existing global quasi-constitutionalist order on tax, trade, and investment law? A number of countries in Europe and around the world have begun imposing standalone digital services taxes pending multilateral agreement on a coordinated reform of bilateral income tax treaties (aka the OECD-G20/Inclusive Framework’s ‘Pillar 1’). But if Pillar 1 fails to materialise and countries go forward with unilateral digital services taxes, the United States and U.S. firms will likely seek redress using domestic measures as well as trade and investment treaties where applicable. This Article argues that in the face of such U.S. resistance, EU member states and countries elsewhere ought to reconsider using the income tax system to achieve their goals instead. We first review the events that led countries to avoid the income tax in favour of standalone taxes only to become embroiled in domestic U.S. trade policies. We then explain how European and other source jurisdictions for business services related to data collection, mining, and commercialisation could revisit the income tax to get to the same tax base, namely by taking an ambulatory interpretation approach to provisions in existing tax treaties in a way that renders possible to accommodate withholding taxes on those services. We show that an ambulatory interpretation approach could achieve the underlying goals of taxing data-driven businesses, in some cases even without any domestic law or treaty reform, with treaty-based rules for dispute resolution a ready tool to draw upon if and when the United States disagrees.

European Law OpenVol. 3(4)
University of Antwerp (BE), Province of Antwerp (BE), McGill University (CA)
Università degli Studi di Trento, Social Sciences and Humanities Research Council of Canada
Openalex Percentile: Top 9%
Gender, Labor, and Family Dynamics
2.79
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