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Record W2302006903 · doi:10.55016/ojs/sppp.v9i1.42567

Rates of Return on Flow-Through Shares: Investors and Governments Beware

2016· article· en· W2302006903 on OpenAlexaffabout
Vijay M. Jog

Bibliographic record

VenueThe School of Public Policy Publications · 2016
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicNatural Resources and Economic Development
Canadian institutionsCarleton University
Fundersnot available
KeywordsBusinessFinanceFlow (mathematics)Monetary economicsFinancial systemEconomicsMechanics

Abstract

fetched live from OpenAlex

Canada’s tax code allows the use of flow-through shares for mining and oil and gas companies on the assumption that they are a good way to spur new productive exploration and are also beneficial to investors. In reality, it appears that flow-through shares are lousy for both. Flow-through shares are designed for corporations that cannot make good use of expense deductions from their taxes and so, through the use of these special type of shares, can pass along their expenses for shareholders to deduct from their own income taxes. This tax break is not insignificant: The amount of revenue foregone by the federal government due to flow-through shares and the related Mineral Exploration Tax Credit averaged $440 million every year between 2007 and 2012. But the steepest price has arguably been borne by investors, with returns on flow-through shares performing extraordinarily poorly. For small companies that issued these shares, the annualized absolute return was a nearly 100 per cent loss. For larger companies, the returns were not as bad — negative 14 per cent — but still a loss. And if adjusted for corresponding benchmarks, the returns were even worse. From the $2.5 billion raised from Canadians using flow-through shares, investors have lost $1.2 billion. Certainly these results would indicate that flow-through shares are hardly helping Canadian explorers strike lucrative new discoveries (it is impossible to say whether the limited success some larger companies had in locating productive assets, using flow-through shares, would not have occurred anyway). Meanwhile, these share issues, bearing the imprimatur of a special government right and the incentive of an investor tax benefit, have likely led to market distortions, luring capital that might have otherwise gone to more productive and rewarding investments. Compounding matters is the very real possibility that those projects that were funded by flow-through shares, but would have been better not begun at all, added competition for inputs and labour, increasing their prices — and lowering returns — for other mining and oil and gas projects with better prospects. In sum, the legacy of flow-through shares is effectively a list of everything that would indicate the policy’s failure. They have hurt investors. They have hurt economic efficiency. They have distorted market competition. And all at a cost to the federal government of nearly half-a-billion dollars a year. Furthermore, the incentives created by flow-through shares can only run counter to any desires among federal and provincial governments to diversify their economies and reduce dependency on mineral and fossil fuel resources. And even where it remains a goal to increase investment in such resources — or any other government-favoured sector, for that matter — it is clear that flow-through shares or tax incentives similar to this policy mechanism are an extremely poor way to achieve it.

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)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.703
Threshold uncertainty score0.905

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.077
GPT teacher head0.274
Teacher spread0.198 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
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
Published2016
Admission routes2
Has abstractyes

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