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Record W2939088537 · doi:10.1177/152397211701700302

Overselling the Economic Efficiency Gains from Shifting the Tax Mix towards Consumption Taxes

2017· article· en· W2939088537 on OpenAlexaffabout
Peter S. Spiro

Bibliographic record

VenuePublic Finance and Management · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicCanadian Policy and Governance
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsEconomicsIndirect taxValue-added taxConsumption (sociology)Public economicsState income taxDistribution (mathematics)Tax reformDirect taxIncome taxLabour economicsTax deferralConsumption taxGross income

Abstract

fetched live from OpenAlex

It is frequently argued that it would be beneficial to move the tax mix towards greater reliance on consumption taxes, with offsetting reductions in income taxes. Proponents argue that this would increase the incentives to “work, save, and invest” and would help improve productivity growth. in Canada, policy experts have generally advocated shifting the tax mix towards consumption. However, on a number of occasions when such a choice was put to the electorate, this shift was rejected. In fact, when one looks at the empirical research on response elasticities, it suggests that the net positive impacts are likely to be relatively small. the most reliable estimates from economic models indicate a small positive impact on economic efficiency from changing the tax mix. the largest and clearest impact of changing the tax mix is on the distribution of income, as the income tax is much more susceptible to being progressive. Therefore, the positive impact on overall GDP would be too small to compensate most taxpayers. Middle income earners in particular are likely to be net losers from changes in the tax mix. Designing changes in the tax mix so as to make everybody better off is a complex task. Voters seem to be aware of the income distribution impacts, and vote in their own self-interest. in a referendum in the province of British Columbia, the majority voted to repeal a value added tax. the percentage voting for repeal was highest in the lowest income electoral districts.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.853
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0030.000
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.052
GPT teacher head0.301
Teacher spread0.249 · 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 teacher head, not a consensus.

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

Citations1
Published2017
Admission routes2
Has abstractyes

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