Challenges of the digital economy on international taxation rules from the perspective of global business society
Bibliographic record
Abstract
While the examination process on a new tax allocation rule has been developed in the OECD and its final discussion is still on-going, this paper explores what kind of efforts and contributions have been made by businesses who are important stakeholders on this issue and identifies whether those responses have been well addressed or not. During the drafting stage managed by the Inclusive Framework (IF), supported by the OECD secretariat, the main issue has been to what extent any residual profits of digital transformation enterprises (digital MNEs) should be allocated between the home country of the digital MNEs and market countries. The features of the digital economy, especially “Scale without mass” have served as a mechanism to allocate their residual profits to their home countries. The private sector generally believes that such outcome seems reasonable, mainly because the digital economy heavily depends on intangibles developed by the headquarters company, that bears the huge R&D expenditures. The private sector claims that the traditional allocation methodology looks reasonable and legitimate and that the government should respect it to a great extent. To support this discussion, the private sector has been referring to the 1998 Ottawa Principle endorsed by the OECD participants’ ministers. The agreed document referred to several taxation principles, including neutrality, equity, etc, as a guidance on how to address taxation of e-commerce transactions. During the discussion on the Action1 of the BEPS Project (taxation on the digital economy), businesses again have been sticking to the same Principle. It claims that any new allocation rule to address the challenge of digitalization should be proportionate to the value creation mechanism within any business model. The comments from businesses are summarized as following;. To structure a new tax base and designate allocation keys to it, if necessary, the governments should respect business accounting practice as much as possible, and the additional allocation of profits to market countries should be minimized, because the private sector heavily depends on the intangibles that are developed by its parent company as well as on the global network that is managed by its parent company. Thus, even if a new additional allocation rule would be agreed, the compliance cost for the new rule should be minimized. During the final stage of drafting the two pillar approaches, input from the private sector is important and indispensable, especially for the technical issues, such as the use of consolidated accounting reports, documentation requirements on taxpayers and dispute prevention and resolution program. So far, it is observed that public consultations have been organized in a timely manner and working effectively, however, before final political negotiations among the IF countries, consultations with businesses could produce practical and administrable adjustments to the OECD frameworks.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.016 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.005 | 0.012 |
| Scholarly communication | 0.017 | 0.016 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.007 | 0.010 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".