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Record W3121596749

The GST Cut and Fiscal Imbalance

2006· preprint· en· W3121596749 on OpenAlexaboutno aff
Michael Smart

Bibliographic record

VenueRePEc: Research Papers in Economics · 2006
Typepreprint
Languageen
FieldEconomics, Econometrics and Finance
TopicFiscal Policy and Economic Growth
Canadian institutionsnot available
Fundersnot available
KeywordsRevenueProductivityTax reformInvestment (military)Tax revenueEconomic policyGovernment (linguistics)BusinessBlameSales taxTax incidenceEconomicsGovernment revenueFederal budgetMonetary economicsAd valorem taxPublic economicsFinanceFiscal yearEconomic growthPolitical science
DOInot available

Abstract

fetched live from OpenAlex

The federal government is reducing its GST rate from 7% to 5%. We examine a broader reform in which this reduction in federal tax rates and revenues is accompanied by a similar reduction in federal transfers to the provinces. At the same time, the provinces may if they wish increase their own sales tax rates to make up the difference, while some provinces, including Ontario, reform their retail sales taxes to emulate the federal GST more closely. We analyze the likely impacts of such reforms on provincial revenues, tax incidence, and business investment. The result of combining these measures would be (1) a better ‘balanced’ federation, with less room for ‘blame-shifting’ between levels of government and consequently greater accountability at all levels, and (2) owing to the removal of the present surprisingly heavy tax on investment imposed by the provincial retail sales taxes an expansion in investment and, over time, in productivity, employment, and perhaps economic growth.

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)0.001
metaresearch head score (Gemma)0.005
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.058
Threshold uncertainty score0.115

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.003
Science and technology studies0.0030.002
Scholarly communication0.0040.002
Open science0.0000.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0170.001

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 head0.036
GPT teacher head0.277
Teacher spread0.241 · 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
GenreEmpirical

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

Citations4
Published2006
Admission routes1
Has abstractyes

Explore more

Same venueRePEc: Research Papers in EconomicsSame topicFiscal Policy and Economic GrowthFrench-language works237,207