The determinants of corporate cost of debt during a financial crisis
Why this work is in the frame
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Bibliographic record
Abstract
Panel data from publicly listed US industrial firms is used to investigate how firm- specific cost of debt (COD) determinants impact COD at different quantiles during a financial crisis. Six COD determinants: firm size, firm age, profitability, leverage, liquidity, and firm value, and advanced estimators: robust and bootstrapped fixed effects, bias-corrected least square dummy variable (LSDVC), and quantile regression, are employed within the context of pecking-order theory. The results show that firm size and leverage negatively impact COD, while liquidity positively impacts it when COD is high (90% quantile). The degree of profitability only confirms the pecking order theory when COD is extremely low (10% quantile) and contrasts with the theory for the 25% and above COD quantiles during the Global Financial Crisis (GFC). These findings confirm that the practicalities of access to finance matter during a financial crisis for corporate financing decisions. • US industrial firms' cost of debt (COD) determinants are studied in the context of pecking order theory. • Robust and bootstrapped fixed effects, LSDVC, and quantile regressions are employed. • Leverage positively affects the COD in the low quantiles and negatively in others. • Profitability and liquidity positively affect COD in the higher quantiles. • The finding for profitability mostly contrasts with expected pecking order theory.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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