Sources of Productivity Growth: Technology, Terms of Trade, and Preference Shifts
Bibliographic record
Abstract
D'habitude, on mesure la croissance de la productivité par le résidu de Solow. Pour ce faire, on a besoin de prix et de parts de facteurs. Puisque ces prix sont supposés être égaux aux productivités marginales, la mesure habituelle prend pour acquis ce qu'elle est censée mesurer. Dans cet article, nous déterminons la croissance de la productivité totale des facteurs sans avoir recours à des données sur les prix des facteurs. Les productivités factorielles sont définies comme des multiplicateurs de Lagrange d'un programme qui maximise le niveau de la demande finale domestique. La mesure qui découle de la croissance de la productivité totale des facteurs inclut non seulement le résidu de Solow,0501s aussi les effets dus aux termes de l'échange et aux changements de préférence. En utilisant les tableaux entrée-sortie canadiens de 1962 à 1991, nous montrons que la source de la croissance de la productivité au Canada est passée du changement technique aux améliorations des termes de l'échange.
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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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".