The Impact of Corporate Reputation on Cost of Debt: A Panel Data Analysis of Indian Listed Firms
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The study analyses the impact of financial reputation on the cost of debt financing for Indian companies. In doing so, panel regression analysis is performed using firm-specific data on 395 Indian listed firms covering 2002–2017. The paper uses market capitalization as a benchmark of financial reputation. For robustness check, excess of market value over book value is also used as a proxy of financial reputation. The study found that the reputation of a firm in financial markets plays a vital role in determining the cost of financing. The results provide evidence supporting a significant negative relationship between financial reputation and the cost of debt. The findings provide motivation for corporate managers to invest in reputation-building activities to reduce the cost of borrowing. The relevance of reputation in lowering the cost of debt capital has garnered limited attention, especially in emerging economies like India. This study is a preliminary attempt to link two strands of research in the Indian context: financial reputation and the cost of debt.
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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 | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 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