How To Become Seductive: Make Canada More Investment-Friendly
Bibliographic record
Abstract
Federal and provincial finance ministers need a wake-up call during this budget season. They have to make Canada a far more attractive location for investment capital. As it stands, Canada’s business investment taxes are the third highest in the world, using a representative selection of 20 industrialized and large developing countries. That is a potentially self-destructive status. Because of the importance of business capital investment for productivity improvement, technological advancement and the country’s standard of living, it is urgent that federal and provincial governments put together a new action plan to improve Canada’s business tax competitiveness. Many analysts define tax competitiveness using only one element of the business tax system — the statutory income tax rate that applies to corporate income. That approach can lead to an illusionary result that, more often than not, creates complacency among the nation’s governments. In fact, the taxes that businesses actually pay depend on the rules that define income, such as depreciation and inventory cost deductions, as well as many other taxes directly related to capital investment. A better measure of the overall business-tax structure is the marginal effective tax rate (METR) for investments. The METR is the amount of corporate income and other capital-related taxes as a percentage of pre-tax profits for marginal investments — investments that earn a rate of return on capital that is just sufficient to attract savings from international markets. The METR calculation takes account, for example, of the lower income taxes payable in countries that allow higher depreciation charges than other jurisdictions, even if the statutory rate is the same or higher. As well, a low statutory tax rate can produce a high effective tax rate if the definition of taxable income permits few deductions. A summary of the 2004 tax provisions is available upon request. Canada’s METR on capital investments in the manufacturing and services industries was 31.3 percent in 2004, the third highest among the 20 countries examined (Table 1). Specific disadvantages in Canada include: • The sixth highest general corporate income tax rate, surpassed only by Japan,
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.015 | 0.005 |
| Scholarly communication | 0.012 | 0.005 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.004 | 0.006 |
| Insufficient payload (model declined to judge) | 0.043 | 0.009 |
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".