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Peering into Alberta’s Darkening Future: How Oil Prices Impact Alberta’s Royalty Revenues

2017· article· en· W6884623126 on OpenAlexaboutno aff

Bibliographic record

VenueUniversity of Calgary · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicCanadian Policy and Governance
Canadian institutionsnot available
Fundersnot available
KeywordsRevenueFalling (accident)Quarter (Canadian coin)Barrel (horology)Government (linguistics)Government revenueCrude oilPeering

Abstract

fetched live from OpenAlex

The price of oil just keeps collapsing — and the fate of Alberta’s revenues is buckling with it. Going into March 2015, it seemed as if prices might have finally found a bottom, somewhere between US$48 and US$52. By the second week of March, they began falling again, to the low forties. These are prices the Alberta government had not even ventured to fathom when first putting together its forecasts for the impact of falling oil prices on the province’s finances. Come the fourth quarter of the Alberta government’s 2014/15 fiscal year, the province’s finances will begin to really feel the blow from the plunge in oil, as royalty payments dry up significantly. Come the 2015/16 fiscal year, the situation becomes even bleaker. In fact, the current fiscal year will seem pleasant compared to the next one. Due to a stronger than expected first half of the year, actual bitumen and crude oil royalties collected in Alberta from April to September 2014 exceeded estimates by $1.3 billion. That will mitigate some of the damage that the continuing slide in prices will cause by the year’s end, with the government’s third quarter update showing expected year-end crude oil and bitumen royalty revenues falling short of the budget target by $549 million. So severe has the fall in oil prices been that, in March 2015, the number of barrels of conventional oil that the government collects in royalties could plummet by up to 53,000 barrels from the 2014/15 budget forecast, declining to just 4,100 barrels per day. This suggests that prices may be nearing a point where royalty collection from conventional crude oil production is at risk of being virtually eliminated. Bitumen royalties are not faring much better. Relative to July 2014, per barrel royalties in February 2015 have potentially declined by 60 to 90 per cent. All told, the combined effect of the changing exchange rate, lower prices, and the lower royalty rates that take effect in this low-price environment, will lead to a potential decline in crude oil and bitumen royalty revenues of 42 to 74 per cent in the 2015/16 fiscal year. This corresponds to a monetary decline of roughly $3.3 billion to $5.8 billion. If oil prices stay below US$45 per barrel, that decline will become even more severe. The pain for Alberta revenues does not end there. The government will be facing additional losses in land sale revenues, natural gas royalties, and tax revenues. Still, even the surprisingly strong revenues for the first half of the year suggest a serious problem with government forecasts. By the end of September, the government had collected $5.198 billion in crude oil and bitumen royalties, 33 per cent higher than originally forecast. That government estimates could be so far off the mark raises serious questions about the methods the province is using to forecast royalties. In a province so dependent on resource royalties for its revenues, adding the unpredictability of unreliable forecasting methods can only put its fiscal planning at that much greater risk of instability.

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)0.002
metaresearch head score (Gemma)0.010
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.133
Threshold uncertainty score0.268

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.010
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0110.003
Scholarly communication0.0130.003
Open science0.0010.003
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0190.003

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 head0.010
GPT teacher head0.248
Teacher spread0.238 · 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 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".

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Citations0
Published2017
Admission routes1
Has abstractyes

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