Interest Deductibility and International Taxation in Canada After BEPS Action 4
Bibliographic record
Abstract
Among the ways in which multinational enterprises (MNEs) can shift profits from one jurisdiction to another in order to minimize taxes, one of the most simple and widely-employed involves the payment of interest to related parties and third parties. For these reasons, it is not surprising that the Organisation for Economic Cooperation and Development’s Action Plan on Base Erosion and Profit Shifting (BEPS) identified the deduction of interest and other financial payments as a significant source of BEPS concerns, and that BEPS Action 4 was charged with developing “recommendations regarding best practices in the design of rules to prevent base erosion through the use of interest expense … and other financial payments that are economically equivalent to interest payments.”This article considers how Canada should respond to the recommendations of BEPS Action 4 in light of recent developments in the U.S. and other jurisdictions. The first section explains the ways in which interest payments may be used to shift profits from one jurisdiction to another in order to minimize taxes, considering both inbound investments and outbound investments, and why this base erosion and profit shifting may be problematic as a matter of tax policy. The second section reviews Canadian responses to these profit shifting strategies prior to BEPS Action 4. The third section summarizes the recommendations of BEPS Action 4 and the extent to which these recommendations have been implemented in other countries. A final section concludes by considering how Canada should respond to BEPS Action 4.
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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 | 0.003 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.016 | 0.005 |
| Scholarly communication | 0.010 | 0.002 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.006 | 0.008 |
| Insufficient payload (model declined to judge) | 0.005 | 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".