MétaCan
Menu
Back to cohort
Record W3153649610 · doi:10.7202/1075635ar

Globally Trading Firms in Canada: Productivity and Global Value Chains

2021· article· en· W3153649610 on OpenAlexaffvenueabout
Ram C. Acharya

Bibliographic record

VenueJournal of Comparative International Management · 2021
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicGlobal trade and economics
Canadian institutionsInnovation, Science and Economic Development Canada
Fundersnot available
KeywordsProductivityValue (mathematics)WorkforceCapital (architecture)BusinessInternational tradeChinaEconomicsInternational economicsMonetary economicsLabour economicsEconomic growth

Abstract

fetched live from OpenAlex

Using firm-level data in Canada from 2002 to 2008, I compare the economic performance of three types of firms: those that both export and import (called globally trading firms—GTFs), exporters-only, and importers-only. The results show that GTFs are more productive, larger, more capital intensive, pay higher wages, trade more goods, and trade with more countries than both types of one-way traders. These premia for GTFs were found even before they turned into GTFs (self-selection). Moreover, even after turning into GTFs, the productivity growth of a subset of them was faster than that of one-way traders. The higher the involvement in global value chains (GVCs), the higher was the performance of the “learning-by-turning GTFs”. The GTFs with higher productivity growth were the ones that imported from multiple countries, not those that imported only from China. By another measure, they were both-in-both GTFs—those that traded both final and intermediate goods, and in both directions (exports and imports). Even though they employed only 10% of Canada’s business sector workforce, they contributed 60% of its labour productivity growth.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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: Empirical
Teacher disagreement score0.649
Threshold uncertainty score0.987

Codex and Gemma teacher scores by category

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

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 head0.061
GPT teacher head0.250
Teacher spread0.189 · 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 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

Citations0
Published2021
Admission routes3
Has abstractyes

Explore more

Same venueJournal of Comparative International ManagementSame topicGlobal trade and economicsFrench-language works237,207