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Record W3126143874

Piling On – How Provincial Taxation of Insurance Premiums Costs Consumers

2018· article· en· W3126143874 on OpenAlexaboutno aff
Alex Laurin, Farah Omran

Bibliographic record

VenueC.D. Howe Institute Commentary · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicCanadian Policy and Governance
Canadian institutionsnot available
Fundersnot available
KeywordsBusinessProperty insuranceRevenueInsurance policyGeneral insuranceAuto insurance risk selectionLife insuranceFinanceActuarial science
DOInot available

Abstract

fetched live from OpenAlex

Insurance premiums have been taxed by Canadian governments for so long – some provinces and municipalities collected small levies as early as the late 1800s – that they’ve become a fixture rarely discussed in the literature and the financial press. For many years, insurance premium taxes were collected from insurers as an alternative to taxing their profits. But this practice is now long gone since all Canadian governments tax the corporate income of insurance companies, in addition to premium taxes and other taxes and levies. Most insurance consumers do not know that a provincial insurance premium tax (IPT) ranging from 2 percent to 5 percent is levied on their premiums. In addition, five provinces charge a retail sales tax (RST) ranging from 6 to 15 percent on top of the premium taxes for certain types of insurance. In Quebec and Ontario, the RST rates of respectively 9 and 8 percent generally apply to group life and health insurance, and property and casualty insurance (although Ontario excludes auto insurance). Saskatchewan is the latest province to introduce an RST. Since insurance is a financial service, premiums are exempt from GST/HST. So why do provinces still tax insurance premiums? While IPTs and RSTs on premiums are largely invisible to customers on whom the burden ultimately falls, they generate more than $7 billion of stable and growing provincial government revenues – representing about 7 percent of all provincial taxes collected on goods and services. Premium-based taxes increase the price of insurance products and lower the demand for them. We find that an increase of one percentage point in the provincial IPT rate leads to a 10 percent decrease in the number of life insurance contracts sold. Reduced insurance coverage for natural disasters such as floods and earthquakes, other catastrophes, relief to a deceased's family, or relief of the financial burden of illness and disability may lead to increased cost pressures on government budgets down the road. Canadian governments should revisit and reassess the taxes imposed on insurance products. At a minimum, IPT liabilities should be made creditable against corporate income tax liabilities, partly restoring their original role as a substitute for taxing profits. And provinces that impose an RST on IPTinclusive premiums should lead the way and eliminate this form of double taxation. A more ambitious reform would remodel the patchwork of transaction taxes for insurance services to a comprehensive and broad-based, value-added system, bringing down the insurance industry's high transaction tax burden and ensuring greater comparability with other industries.

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)0.011
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: Commentary · Consensus signal: none
Teacher disagreement score0.069
Threshold uncertainty score0.316

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.011
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.002
Science and technology studies0.0040.001
Scholarly communication0.0050.001
Open science0.0010.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0230.002

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 head0.026
GPT teacher head0.294
Teacher spread0.269 · 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
GenreCommentary

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".

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Citations0
Published2018
Admission routes1
Has abstractyes

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