Siezing the BEPS: an assessment of the efficacy of South Africa’s thin capitalisation regime in combating base erosion and profit shifting (BEPS) through excessive interest deductions
Bibliographic record
Abstract
This study serves to critically assess the effectiveness of South Africa’s thin capitalisation framework in dealing with Base Erosion and Profit Shifting (BEPS) through excessive interest deductions by multinational enterprises (MNEs). Given the impact of globalisation in interconnecting economic activities across multiple countries, BEPS presents a major policy concern both internationally and domestically. Thin capitalisation, a situation in which an entity utilises to their tax benefit the deductions/exemption mismatch that arises from crossborder debt financing, is one of the most common methods of BEPS utilised by MNEs. This study aims to ascertain whether the framework is effective in dealing with thin capitalisation whilst balancing the need to attract investment and boost economic development and, to assess whether the framework is reflective of South Africa’s contextual realities. It achieves this by engaging with the South Africa’s legislative framework consisting of s 31 and s 23M of the Income Tax Act and the Draft Note on Thin Capitalisation and their relationship with international tax norms and standards. The study relies on the Organisation for Economic Cooperation and Development (OECD) to identify the international standards and contrasts South Africa’s framework with Canada, a developed and OECD member state. The study concludes that the framework is fraught with uncertainties and administrative difficulties that hinder its effectiveness. It also concludes that the framework’s reliance on the OECD’s standards is misguided and does not reflect South Africa’s contextual realities. This is a stark contrast to Canada which opted for a thin capitalisation approach outside the OECD’s recommendations which more reflects its context. The study thus concludes that South Africa’s thin capitalisation framework is ineffective in dealing with BEPS by way of thin capitalisation.
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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 | 0.008 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".