Do Managers Have Capital Structure Targets? Evidence from Corporate Spinoffs
Bibliographic record
Abstract
The two main theories of capital structure—the tradeoff theory and the pecking order theory—have opposite predictions about the expected relationship between corporate leverage and profitability. According to the tradeoff theory, companies that earn higher profits will use more debt both to shield their income from corporate taxes and to discipline corporate investment policy. In contrast, the pecking order theory predicts that more profitable companies will borrow less mainly because they have less need to borrow. Corporate spinoffs provide a unique opportunity to investigate the influence of profitability and other asset characteristics on the design of capital structure. In their study of 98 spinoffs over the period 1979–1997, the authors began by investigating the popular argument that managers routinely assign more debt to subsidiaries than parents in order to leave the parents less encumbered—a possibility they reject after finding that the average leverage ratios of the parents and spunoff units were roughly equal. At the same time, the authors reported large differences in the leverage ratios among both parents and spun‐off units, and that the variation was explained primarily by differences in three factors: asset tangibility and the level and variability of cash operating profits. Consistent with the tradeoff theory (but not the pecking order), the study found a significantly positive correlation between a post‐spinoff company's cash profitability and its assigned debt load, as well as a negative correlation between debt and the variability of operating cash flow.
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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 | 0.002 | 0.022 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".