Determinants of Capital Structure in Canadian Non-financial Firms: A Recent Study
Bibliographic record
Abstract
The purpose of this research is to examine firm-specific determinants of capital structure in Canadian non-financial firms. The research uses a sample of 208 firms listed on Toronto Stock Exchange from 1999 to 2016. Panel data analysis has been performed using a fixed effects model estimation. The study also investigates the impact of firm-specific factors on capital structure in three different phases: pre-crisis (1999-2006), during crisis (2007-2009), and post-crisis (2010-2016). The analysis suggests that age, liquidity, asset tangibility, size, growth opportunities, and profitability are the determinants of capital structure in Canadian non-financial firms. The findings suggest that Pecking Order Theory better explains capital structure choices across Canadian non-financial firms. However, some hypotheses of Trade-off Theory are also applicable in certain contexts. This study adds to the existing literature on factors influencing capital structure of Canadian non-financial firms. Both practitioners and academicians may benefit from the findings of this study.
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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 | 0.002 | 0.005 |
| Science and technology studies | 0.002 | 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".