Productivity performance and international competitiveness: an old test reconsidered
Bibliographic record
Abstract
A modern adaptation of the Ricardian model is used, which incorporates monopolistic competition and multiple factors to derive a MacDougall‐type relation between a country’s international competitiveness at the industry level and its productivity performance. This relation is implemented empirically for Canada and the United States, using panel data for twenty‐five years and forty industries. A key finding is that the Canadian‐U.S. productivity ratio is an important determinant of relative shares of Canadian firms in both Canadian and U.S. markets. Trade liberalization between Canada and the United States also plays a significant role in influencing market shares. JEL Classification: F11, F12 Niveau de productivité et compétitivité internationale : un autre coup d’œil à un vieux test. Ce mémoire utilise une adaptation moderne du modèle ricardien qui postule concurrence monopolistique et plusieurs facteurs pour dériver une relation à la MacDougall entre la compétitivité internationale d’un pays au niveau de l’industrie et son niveau de productivité. On calibre cette relation pour le Canada et les États‐Unis en utilisant des données pour quarantes industries sur une période de vingt‐cinq ans. Un résultat important est que le ratio de la productivité entre le Canada et les États‐Unis est un déterminant important des parts de marché des firmes canadiennes tant au Canada qu’aux États‐Unis. La libéralisation du commerce entre les deux pays joue aussi un rôle important dans la définition de ces parts de marché.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.001 | 0.007 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".