Relative Influence of Push Attributes and Pull Factors on Corporate Debt Issuance
Bibliographic record
Abstract
Many corporate events are self-selected, but the relative impact of internal (firm-specific) and external (environmental) influences on discretionary corporate decisions remains largely unknown. In this paper, focusing on corporate debt issuance, we apply the contemporary push-pull theory to establish whether bond issuance are pushed by the firms due to internal considerations, or pulled by the enticement of exogenous forces. We explore the impact of eight firm-specific push attributes and four systematic pull factors on the likelihood and volume of five types of debt issued, and disentangle the relative significance of push and pull effects. We find three key results. First, unconditionally, both firm-specific push attributes and exogenous pull factors are relevant. Second, the relative significance of push effects are always decidedly larger than those of pull effects. Finally, pull factors have no conditioning role in how markets react to debt issuance. Although pull effects do matter, push effects compellingly dominate.
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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 | 0.003 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".