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Record W3122581897

Taxing issues with privatization: a checklist

2000· preprint· en· W3122581897 on OpenAlexaboutno aff
Jack Mintz, Duanjie Chen, Evangelia Zorotheos

Bibliographic record

VenueRePEc: Research Papers in Economics · 2000
Typepreprint
Languageen
FieldSocial Sciences
TopicCanadian Policy and Governance
Canadian institutionsnot available
Fundersnot available
KeywordsTaxable incomeBusinessTax creditTax revenueValue-added taxTax reformRevenueTax policyPublic economicsEconomicsFinanceMarket economyAccounting
DOInot available

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.017
metaresearch head score (Gemma)0.082
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.970
Threshold uncertainty score0.088

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0170.082
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0130.017
Science and technology studies0.0080.006
Scholarly communication0.0090.020
Open science0.0050.005
Research integrity0.0100.009
Insufficient payload (model declined to judge)0.0100.002

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.

Opus teacher head0.031
GPT teacher head0.345
Teacher spread0.313 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreOther

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".

Quick stats

Citations2
Published2000
Admission routes1
Has abstractyes

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Same venueRePEc: Research Papers in EconomicsSame topicCanadian Policy and GovernanceFrench-language works237,207