Taxing issues with privatization: a checklist
Bibliographic record
Abstract
Privatization has been a popular strategy for improving efficiency in both market and transition economies. The literature on privatization includes broad discussions of pricing techniques but overlooks tax issues. In reality, a state-owned company loses its privilege of paying no taxes once it is privatized. This change in tax status would certainly complicate the financial transaction of a newly privatized company, affect industry-wide economic efficiency, and change the revenue pattern of governments. Using Ontario Hydro and the Canadian tax regime as examples, the authors provide policymakers with a checklist on tax issues under privatization. Their main observations: 1) The tax status of the company to be privatized must be considered in analyzing the firm's financial transition. 2) The economic efficiency targeted by privatization may depend partly on the tax regime for a particular industry. 3) Privatization affects government revenue through the revenue-sharing structure determined by intergovernmental fiscal relationships and cross-border tax arrangements. Time is a factor in tax and transition issues. At the time of privatization, for example, how are assets to be valued for calculatingcapital gains and cost deductions, for tax purposes? Are the assets transferred to the new owners at fair market value, book value, or at cost, for tax purposes? How should heavy debt loads be treated? Ontario Hydro will not be privatized but it will become taxable. How the taxes will be paid will depend on how the transition is treated. Tax policy will be a key determinant of the industry's future development.
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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 | 0.017 | 0.082 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.013 | 0.017 |
| Science and technology studies | 0.008 | 0.006 |
| Scholarly communication | 0.009 | 0.020 |
| Open science | 0.005 | 0.005 |
| Research integrity | 0.010 | 0.009 |
| Insufficient payload (model declined to judge) | 0.010 | 0.002 |
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".