THE IMPACT OF THE TAX LANDSCAPE OF THE COUNTRY ON THE TAX PLANNING OF TNCs UNDER THE BEPS PROJECT
Bibliographic record
Abstract
The article notes that in the context of globalization, multinational corporations exert an increasing influence on the economies of their home countries, host countries, and the overall state of international economic relations. The authors underline that tax planning is one of the TNC activities that grabs attention of the global public in terms of both its favorable and unfavorable effects. The article offers its own definition of the term «tax landscape», in which, unlike the existing ones, vertical, horizontal and temporal aspects are distinguished. The vertical aspect is presented as a synthesis of the supranational level of taxation and the national one; horizontal, as a system of tax rules and laws within a separate state; temporal, as a change in the main elements of taxation over time. It has been proven that at the current stage of formation of tax landscapes to characterize the supranational level, it is necessary to take into account the elements of taxation defined as part of the implementation of the international BEPS project: the global minimum tax, tax rates for surplus profits, and surplus profits as an object of taxation. The authors have been able to divide the studied countries into three groups depending on the level of direct taxation: high (United States, Canada and Australia), moderate (Great Britain, France, Italy, India, Germany and Switzerland), and low (China and Saudi Arabia). The first group (the United States) and the second group (the United Kingdom, Germany, France, Switzerland, and Italy) have been found to have the greatest tax losses as a result of «tax havens.» The level of direct taxation (profit and capital) in the countries of registration and countries of digital presence, the volatility of tax legislation, and compliance with the conditions of tax justice have been proposed as factors of the tax landscape to be taken into account by transnational corporations when developing tax planning strategies.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".