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Record W2206698985

Title: Going Dutch? The Impact of Oil Price Shocks on the Canadian Economy

2015· preprint· en· W2206698985 on OpenAlexaffabout
Jared C. Carbone, Kenneth J. McKenzie

Bibliographic record

VenueRePEc: Research Papers in Economics · 2015
Typepreprint
Languageen
FieldEconomics, Econometrics and Finance
TopicNatural Resources and Economic Development
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsComputable general equilibriumShock (circulatory)Oil priceEconomicsDutch diseaseExchange rateWelfareSupply shockRelative priceMonetary economicsMacroeconomicsMarket economyMonetary policy
DOInot available

Abstract

fetched live from OpenAlex

We examine the steady-state impact of a 10 percent reduction in the price of oil using a CGE model of the Canadian economy. The model includes a high degree of disaggregation at both the sectoral and provincial level, international and interprovincial flows of goods and services, labour which is mobile between sectors, capital which is partly mobile both inter-provincially and inter-sectorally, and equilibrium exchange rate adjustments arising from the oil price shock. The key result of our simulations is that--on balance--a negative oil price shock leaves Canadians worse off. We also find that the welfare losses associated with a negative oil price shock are shared broadly across the provinces. The corollary, of course, is that a positive price shock leaves Canadians better off. Our results have implications for the presence (or significance) of Dutch Disease in Canada; we argue that the disease is just one of a number of effects generated by oil-price changes.

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)0.000
metaresearch head score (Gemma)0.003
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: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.022
Threshold uncertainty score0.160

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.001
Science and technology studies0.0020.001
Scholarly communication0.0030.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0100.000

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 head0.064
GPT teacher head0.297
Teacher spread0.233 · 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

Citations2
Published2015
Admission routes2
Has abstractyes

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