Groups, Pricing, and Cost of Debt: Evidence from Turkey
Bibliographic record
Abstract
The paper examines the impact of business group affiliation on cost of loans in an emerging market setting. It focuses on operational strategy, organizational structure and internationalization policies of business group firms and their impact on borrowing cost of affiliated firms. Bank loans are a dominant source of corporate funding in emerging markets, in which business groups exist as leading economic entities. Yet, the impact of belonging to a group on the firm’s cost of debt has not been studied in depth. Our results reveal that the extent of group affiliation, government ownership, and diversification increase the cost of loans. However, a group bank is advantageous in terms of borrowing, and decreases the cost of loans. While foreign ownership is beneficial in terms of pricing, being affiliated with a foreign group is not. Being a financial firm and being cross-listed are not significantly associated with bank loan terms. Borrowing costs are thus influenced in various ways by organizational structure, operational strategies, and global policies of business groups and affiliates. Therefore, business groups may benefit from strategically implementing policies and selecting loan applicant firms.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".