Fitness Versus Fatness: Productivity, Financial Conditions, and the Survival of New Canadian Manufacturing Firms
Bibliographic record
Abstract
The recent economic and financial crisis highlights the role of balance sheets on firm survival. This paper considers the role of initial financial leverage (debt-to-asset ratio) on the survival of entrant Canadian manufacturing firms. Due to limited data availability, little is known about how financing affects the performance of young, private firms. This study utilizes a unique administrative dataset, T2LEAP, which contains employment and balance sheet information for all incorporated Canadian firms. We find that there is a non-monotonic relationship between leverage and firm exit (hazard) rate. The hazard rate decreases as leverage increases up to the four quintile of the leverage distribution and then increases for firms in the top leverage quintile. These effects are present while controlling for: firm characteristics, such as size and labour productivity; industry conditions, such as the real exchange rate, the differential US-Canada tariff rates, entry penetration, and the capital-labour ratio; and aggregate conditions in terms of the yield gap.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".