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The Impact of Converting Federal Non-Refundable Tax Credits Into Refundable Credits

2017· article· en· W6940993418 on OpenAlexaboutno aff

Bibliographic record

VenueUniversity of Calgary · 2017
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicMycorrhizal Fungi and Plant Interactions
Canadian institutionsnot available
Fundersnot available
KeywordsTax creditTax exemptionGovernment (linguistics)CensusTax reformAd valorem taxTax deductionInequality

Abstract

fetched live from OpenAlex

With economic inequality on the rise in Canada, the federal government needs to consider innovative solutions. One possibility for improving the tax-transfer system involves refundable tax credits (RTCs). Making all tax credits refundable wouldn’t require Ottawa to introduce new tax measures; the Canadian tax system already contains a mix of RTCs and NRTCs, so the government could simply continue its practice of designing tax credit programs to be refundable. Using Statistics Canada’s Social Policy Simulation Database and Model, this paper examines the impacts and cost of converting NRTCs to RTCs, with and without an income exemption equal to 25 percent of the before-tax lowincome standard for a census family, the Census Family Low-Income Line. Under the Option Without Exemption (OW/OE), RTC recipients are taxed at a single rate of 15 percent, regardless of family size, right up to the Line. Under the Option With Exemption (OWE), RTC recipients are taxed at zero percent up to 25 percent of the Line and at a single rate of 20 percent, regardless of family size, up to 100 percent of the Line. The incremental cost of switching NRTCs to RTCs under the OW/OE is $6.6 billion, as additional benefits are provided to 6.4 million families — slightly less than 37 percent of all families. The cost of the OWE is $7.2 billion, as benefits flow to slightly more families — 6.45 million. However, the percentage of benefits reaching low-income families is much higher under the OWE (69 percent vs. 49 percent). Additionally, the OWE provides an average of nine percent more RTC benefits to low-income tax filers, making it clearly the superior option for poverty reduction. Moreover, the paper shows that alternative conversion schemes that set benefit reduction rates to differ by family size can further increase the benefits to low-income families at a lower overall cost. Such changes would elicit a labour-supply response in terms of a reduction in hours worked, and while the effect is smaller under the less expensive OW/OE, the difference between the two options is slight. This paper simulates the conversion of NRTCs to RTCs in comprehensive detail, besides providing practical advice on how such a shift would be funded. It offers valuable food for thought on an issue that is increasingly critical to Canadian society.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.402
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.012
GPT teacher head0.224
Teacher spread0.211 · 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 designObservational
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

Citations0
Published2017
Admission routes1
Has abstractyes

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