1. bookVolume 11 (2021): Issue 2 (September 2021)
Journal Details
License
Format
Journal
eISSN
2674-4619
First Published
18 Jun 2013
Publication timeframe
2 times per year
Languages
English
access type Open Access

Legal Engineering of the Anti-Abuse Rule in ATAD: Architecture of the Regression Tree Model

Published Online: 15 Nov 2021
Volume & Issue: Volume 11 (2021) - Issue 2 (September 2021)
Page range: 65 - 82
Journal Details
License
Format
Journal
eISSN
2674-4619
First Published
18 Jun 2013
Publication timeframe
2 times per year
Languages
English
Abstract

Every taxable arrangement is subject to an anti-abuse test. Abusive arrangements are treated as not valid for tax purposes, which is similar to the treatment of artificial arrangements in civil law. The European Union has introduced in its Anti-Tax Avoidance Directive a general anti-abuse test which must be transposed into the domestic laws of Member States. Such a test has its inner structure, consisting of an elimination and requalification stage, while the elimination stage entails genuineness and a tax benefit test. The general anti-abuse test has a great potential (or scalability when speaking in the language of start-ups) of being automated and integrated into different legal application processes (such as taxpayer self-assessment systems, transactions certified by public notary or merger and acquisition deals) to discover debt push down abuses or other arrangement structures which may have abusive content. While the best method for create a reliable algorithm is a decision tree type model, the inner ambiguity of the general anti-abuse test prevents using the full benefits of automation of tax laws. The purpose of this article is to design a decision tree type model for the test and address the main challenges of such a model, both from the perspective of the clarity of concepts and the quality of input information such an engine would use.

Keywords

Aarno, A. (1996), Õiguse tõlgendamise teooria [The theory of legal intepretation], Tallinn: Avatud Eesti Fond. Search in Google Scholar

Allahyari, M.; Pouriyeh, S.; Assefi, M; Safaei, S.; Trippe, E. D.; Gutierrez, J. B. & Kochut, K. (2017), ‘A brief survey of text mining: Classification, clustering and extraction techniques,’ 23rd ACM SIGKDD Conference on Knowledge Discovery and Data Mining, KDD2017, Halifax Nova Scotia, Canada, August 13–17, 2017. Retrieved from https://arxiv.org/pdf/1707.02919.pdf [accessed 27 Feb 2021] Search in Google Scholar

Council Directive (EU) no. 2016/1164 of 12 July 2016 on laying down rules against tax avoidance practices that directly affect the functioning of the internal market (ATAD), OJ L 193, 19.7.2016, pp. 1–14. Search in Google Scholar

Council Directive (EU) no. 2017/952 of 29 May 2017 amending Directive (EU) 2016/1164 as regards hybrid mismatches with third countries (ATAD II), OJ L 144, 7.6.2017, pp. 1–11. Search in Google Scholar

Frey, C. B. & Osborne, M. A. (2017), ‘The future of employment: how susceptible are jobs to computerization?’ Technological Forecasting & Social Change, vol. 114, pp. 254–280. https://doi.org/10.1016/j.techfore.2016.08.01910.1016/j.techfore.2016.08.019 Search in Google Scholar

Helsgaun, K. (2019), ‘Ten project proposals in artificial intelligence.’ Retrieved from http://akira.ruc.dk/~keld/teaching/Projektforslag/AI_Projects.pdf [accessed 25 Feb 2021] Search in Google Scholar

Hill, R. K. (2016), ‘What an algorithm is,’ Philosophy & Technology, vol. 29, no. 1, pp. 35–59. https://doi.org/10.1007/s13347-014-0184-510.1007/s13347-014-0184-5 Search in Google Scholar

de Jong, S. & Derksen, S. (2019), ‘Binary translation of legislation and case law—A Deep Learning dive into the possibilities of natural language processing for legislation and case law,’ Research paper, Tax & Technology Pt. II, Tilburg University, 14 June. Search in Google Scholar

Jordan, M. I. & Mitchell, T. M. (2015), ‘Machine learning: Trends, perspectives, and prospects’ Science, vol. 349, no. 6245, pp. 255–260. https://doi.org/10.1126/science.aaa841510.1126/science.aaa841526185243 Search in Google Scholar

Kõrgessaar v. Tax Board [2001], Administrative Chamber of the Estonian Supreme Court, no. 3-3-1-57-00, 15.1.2001. Search in Google Scholar

Künnapas, K. (2020), ‘Dysfunctionality from the sovereignty conflict in the ATAD GAAR,’ TalTech Journal of European Studies, vol. 10, no. 1(30), pp. 97–122. https://doi.org/10.1515/bjes-2020-000610.1515/bjes-2020-0006 Search in Google Scholar

Kuzniacki, B. (2018), ‘The artificial intelligence tax treaty assistant: decoding the principal purpose test,’ Bulletin for International Taxation, vol. 72, no. 9, pp. 524–534, IFBD Online Journals.10.2139/ssrn.3235151 Search in Google Scholar

Kuzniacki, B. (2021), ‘Poland’s implementation of EU GAAR compromises constitutional and EU principles,’ Intertax, vol. 49, no. 3, pp. 237–253. Search in Google Scholar

Longarte, I. (2020), ‘Embedding AI and blockchain into next-generation tax policy design,’ LawAhead. Retrieved from https://lawahead.ie.edu/embedding-a-iand-block-chain-in-the-next-generation-digitalized-economy-tax-policy-design/ [accessed 10 Jan 2020] Search in Google Scholar

Maret Lilleorg v. Tax Board [2012], Administrative Chamber of the Estonian Supreme Court, no. 3-3-1-79-11, 13.2.2012. Search in Google Scholar

Marge Sirge v. Tax Board [2011], Administrative Chamber of the Estonian Supreme Court, no. 3-3-1-15-11, 25.4.2011. Search in Google Scholar

Mittelstadt, B. D.; Allo, P.; Taddeo, M.; Wachter, S. & Floridi, L. (2016), ‘The ethics of algorithms: Mapping the debate,’ Big Data & Society, vol. 3, no. 2, pp. 1–21. https://doi.org/10.1177/205395171667967910.1177/2053951716679679 Search in Google Scholar

Narits, R. (2004), Õiguse entsüklopeedia [Encyclopaedia of law], Tallinn: Juura. Search in Google Scholar

OAO Neftyanaya Kompaniya Yukos v. Russia [2011], ECHR 14902/04, 20.10.2011. Search in Google Scholar

OECD (2014), Addressing the Tax Challenges of the Digital Economy, OECD/G29 Base Erosion and Profit Shifting Project, OECD Publishing. Search in Google Scholar

OECD (2019), OECD Model Tax Convention on Income and on Capital: Condensed version 2017, OECD Publishing. http://dx.doi.org/10.1787/mtc_cond-2017-en10.1787/mtc_cond-2017-en Search in Google Scholar

Pianatavigna, P. (2018), ‘The role of the subjective element in tax abuse and aggressive tax planning,’ World Tax Journal, vol. 10, no. 2. Search in Google Scholar

Proposal for a Regulation of the European Parliament and of the Council Laying down harmonised rules on artificial intelligence (Artificial Intelligence Act) and amending certain Union legislative acts, European Commission, 2021/0106 (COD), 21.4.2021. Search in Google Scholar

Raso, F. A.; Hilligoss, H.; Krishnamurthy, V.; Bavitz, C. & Kim, L. (2018), Artificial Intelligence & Human Rights: Opportunities & Risks, The Berkman Klein Center for Internet & Society Research Publication Series, no. 6. https://doi.org/10.2139/ssrn.325934410.2139/ssrn.3259344 Search in Google Scholar

Solarte-Vásquez, M. C. & Nyman-Metcalf, K. (2017), ‘Smart contracting: A multidisciplinary and proactive approach for the EU digital single market,’ Baltic Journal of European Studies, vol. 7, no. 2(23), pp. 208–246. https://doi.org/10.1515/bjes-2017-001710.1515/bjes-2017-0017 Search in Google Scholar

de Wilde, M. F. (2018), ‘Is the ATAD’s GAAR a Pandora’s Box?’ in P. Pistone & D. Weber (eds.) The Implementation of Anti-BEPS Rules in the EU: A Comprehensive Study, Amsterdam: IBFD Online Books, pp. 301–328. Search in Google Scholar

Yale Law School, Information Society Project & Immuta (2017), Governing Machine Learning. Exploring the Intersection Between Machine Learning, Law, and Regulation. Retrieved from https://law.yale.edu/sites/default/files/area/center/isp/documents/governing_machine_learning_-_final.pdf [accessed 15 Jan 2020] Search in Google Scholar

Yan, C. (2019), ‘Economic substance: a machine learning perspective on the multi-factorial analysis,’ Blue J legal, 22 April. Retrieved from https://www.bluejlegal.com/blog/economic-substance-machine-learning-analysis [accessed 25 Feb 2021] Search in Google Scholar

Zalnieriute, M.; Moses, L. B. & Williams, G. (2019), ‘The rule of law and automation of government decision-making,’ The Modern Law Review, vol. 82, no. 3, pp. 425–455. https://doi.org/10.1111/1468-2230.1241210.1111/1468-2230.12412 Search in Google Scholar

Zimmer, F. (2019), ‘In defence of general anti-avoidance rules,’ Bulletin of International Taxation, vol. 73, no. 4, IFBD Online Journals. Search in Google Scholar

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