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Record W1532005403

The Valuation of the Alberta Oil Sands

2008· preprint· en· W1532005403 on OpenAlexaboutno aff
Andrew Sharpe, Jean-François Arsenault, Alexander G. Murray, Sharon Qiao

Bibliographic record

VenueRePEc: Research Papers in Economics · 2008
Typepreprint
Languageen
FieldEnvironmental Science
TopicAtmospheric and Environmental Gas Dynamics
Canadian institutionsnot available
Fundersnot available
KeywordsOil sandsOil reservesValuation (finance)Barrel (horology)Oil in placePetroleum industryEnvironmental scienceAgricultural economicsGeographyEconomicsPetroleumGeologyAccountingArchaeologyEnvironmental engineeringAsphalt
DOInot available

Abstract

fetched live from OpenAlex

The Alberta oil sands reserves represent a very valuable energy resource for Canadians. In 2007, Statistics Canada valued the oil sands at $342.1 billion, or 5 per cent Canada's total tangible wealth of $6.9 trillion. Given the oil sands' importance, it is essential to value them appropriately. In this report, we critically review the methods used by Statistics Canada in their valuation of the Alberta oil sands. We find that the official Statistics Canada estimates of the reserves (22.0 billion barrels) of Alberta's oil sands are very small compared to those obtained using more appropriate definitions, which results in an underestimation of the true value of the oil sands. Moreover, the failure to take into account the projected growth of the industry significantly magnifies this underestimation. We provide new estimates of the present value of oil sands reserves based on a set of alternative assumptions that are, we argue, more appropriate than those used by Statistics Canada. We find that the use of more reasonable measures of the total oil sands reserves (172.7 billion barrels), extraction rate (a linear increase from 482 million barrels per year in 2007 to 1,350 million barrels in 2015, and constant thereafter) and price ($70 per barrel, 2007 CAD) increases the estimated present value of the oil sands to $1,482.7 billion (2007 CAD), 4.3 times larger than the official estimate of $342.1 billion. Using our preferred estimate, Canada’s total tangible wealth increases by $1.1 trillion (17 per cent), and reaches $8.0 trillion with oil sands now accounting for 18 per cent of Canada’s tangible wealth. The importance of these revisions is also demonstrated by their impact on the per-capita wealth of Canadians, which increases from $209,359 to $243,950, or by $34,591 (or 17 per cent). Given the importance of the oil sands for Canada, Statistics Canada should undertake a review of its methodology. In light of the growing body of climatologic literature supporting an association between anthropogenic GHG emissions and global climate change, no analysis of the „true value? of the oil sands would be complete without an accounting of the social costs of the GHG emissions that arise from oil sands development. According to our baseline estimates, the oil sands impose a total social cost related to GHG emissions of $69.4 billion. In making this estimate, we assume that each barrel of oil sands output imposes a social cost of $2.25 (based on a cost of $30/tCO2-e and an intensity of 0.075 tCO2-e/bbl). Our preferred estimate of the net present value of oil sands wealth net of GHG cost is thus $1,413.3 billion, 4.1 times greater than the Statistics Canada estimate which does not account for any environmental costs. This report does not account for non-GHG related environmental and social costs. A comprehensive valuation of all environmental costs are needed to assess whether future benefits derived from oil sands development are outweighed by even larger environmental costs.

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)0.008
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.076
Threshold uncertainty score0.329

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.008
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.004
Science and technology studies0.0020.003
Scholarly communication0.0050.002
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.021
GPT teacher head0.261
Teacher spread0.240 · 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 designSimulation or modeling
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

Citations3
Published2008
Admission routes1
Has abstractyes

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