Do Multi‐Plant Firms Reduce Misallocation? Evidence from Canadian Manufacturing
Why this work is in the frame
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Bibliographic record
Abstract
Abstract Using Canadian plant‐level data, this paper shows that, depending on the industry, the differences in the average plant‐level productivity and cross‐plant allocation of resources between multi‐plant and single‐plant firms account for 1 to 15 per cent of the industry‐level TFP. A large part of this contribution stems from more efficient cross‐plant allocation of resources, measured by the covariance between plant size and productivity, in the pool of plants in multi‐plant firms compared to the pool of plants in single‐plant firms. There is less dispersion in the marginal products of the inputs, and thus less misallocation, in industries in which multi‐plant firms account for a larger share of output. The patterns found in the cross‐plant distribution of productivity and size are also consistent with better allocative efficiency among plants in multi‐plant firms than among plants in single‐plant firms.
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Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it