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Exporting, Foreign Direct Investment, and Wages: Evidence from the Canadian Manufacturing Sector

2011· article· en· W1553303662 on OpenAlexaffabout
Sébastien Breau, W. Mark Brown

Bibliographic record

VenueGrowth and Change · 2011
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicGlobal trade and economics
Canadian institutionsMcGill University
Fundersnot available
KeywordsWageForeign direct investmentLabour economicsForeign ownershipBusinessManufacturing sectorManufacturingInvestment (military)Economics

Abstract

fetched live from OpenAlex

Do exporters and foreign-controlled establishments pay their workers higher wages than non-exporters and domestic-controlled establishments? This paper draws on an employer–employee data set to explore the existence of exporter and foreign-owned wage premiums in the Canadian manufacturing sector. Results from wage regression models reveal that, on the whole, exporters and foreign-controlled plants do pay higher wages than non-exporters and domestic-controlled plants. These results hold even after controlling for other plant and worker characteristics, although the wage differentials are substantially smaller. Furthermore, while the impact of foreign ownership on wages is found to be widespread across industries and regions, that of exporting is not. At the industry level, the wage effects of export-market participation are strongest for workers in plants belonging to scale-based industries; regionally, they are strongest in Quebec and British Columbia.

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)0.004
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.013
Threshold uncertainty score0.091

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.006
Science and technology studies0.0020.001
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.226
GPT teacher head0.205
Teacher spread0.021 · 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".

Quick stats

Citations8
Published2011
Admission routes2
Has abstractyes

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