Export Growth, Capacity Utilization, and Productivity Growth: Evidence from the Canadian Manufacturing Plants
Bibliographic record
Abstract
Aggregate labor and multifactor productivity growth slowed substantially post‐2000 in the Canadian manufacturing sector. To examine the source of the decline, this paper proposes a decomposition method that delves deeper into the two micro‐components of aggregate productivity growth: a within‐plant component and a between‐plant component. The decomposition builds on earlier work by Jorgenson and his collaborators that decomposes aggregate productivity growth into its industry components, but applies it to the plant level and introduces non‐neoclassical features of the plant‐level economic environment. It finds that the preponderance of the aggregate labor and multifactor productivity growth slowdown is due to the pro‐cyclical nature of productivity growth arising from capacity utilization. Almost all of the aggregate productivity growth slowdown is driven by exporters, as exporters experienced large declines in labor productivity growth in the post‐2000 period as a result of large declines in their capacity utilization.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
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".