Bibliographic record
Abstract
Purpose The purpose of the study is to examine the zero-leverage (ZL) phenomenon in family and non-family firms. Design/methodology/approach The authors consider three hypotheses and empirically test them using a sample of the largest US firms over the 2001–2016 period. Findings The authors find that, on average, 19.20% of family firms have zero debt vs 10.42% for non-family firms. The authors also find that family firms strategically choose to be ZL to maintain financial flexibility for future investments and exercise control over the decision-making process, consistent with the hypotheses of financial flexibility and control considerations. However, non-family firms are more likely to have zero debt if they have financial constraints and the credit market does not lend them money at affordable credit rates, consistent with the financial constraint hypothesis. Originality/value This paper contributes to different strands of literature. First, the authors contribute to the literature examining family firms' financial decisions. Second, the authors complement previous studies by exploring the reasons for the ZL behavior of family firms compared to non-family firms. The authors also examine the previously unexplored impact of ownership concentration on the ZL question.
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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 | 0.009 |
| 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 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".