Are Family Firms Different in Choosing and Adjusting Their Capital Structure? An Empirical Analysis through the Lens of Agency Theory
Bibliographic record
Abstract
How do family firms choose and adjust their capital structure? A significant number of contributions have examined the problem from several angles but many issues remain a puzzle. We examine capital structure choices of family firms in Italy, a context characterized by high private benefits of control, separation between ownership and control, and diffusion of family-controlled pyramidal groups. Consistent with the agency-based models, family firms are found to be more leveraged than non-family counterparts as a result of their desire to hold control. We also find higher debt ratios in firms with a higher separation between ownership and control if and only if the firm is controlled by a family. This lends support to the fact that controlling families may want to allocate more debt to subsidiaries, where the separation is higher, in order to inflate assets under domination at the expense of minority shareholders, while controlling negative effects in case of bankruptcy of an affiliate. Finally, family firms are also found to behave differently when they adjust their debt ratio. We show that leverage persistence is higher in family firms because they bear higher adjustment costs as a result of higher agency costs of equity, but lower costs of deviating from the optimal debt level, because the tight links between controlling families and banks may allow family owners to negotiate deviations with banks more easily.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.006 |
| 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 | 0.003 | 0.003 |
| 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".