Generational Socioemotional Wealth and Debt Maturity: Evidence from Private Family Firms of GIPSI Countries
Bibliographic record
Abstract
In this paper we investigate the relationship between generational socioemotional wealth (SEW) and debt maturity structure in private family firms of GIPSI countries for the period 2010-2018. This appears to be quite an important issue to study, given that SEW is a peculiar aspect of family firms and its impact on the debt maturity structure, still relatively unexplored, is likely to change according to the generation running the family business. We show that the importance attached to SEW decreases when moving from the firms’ founder to the subsequent generations, with a negative effect on the amount of long-term debt. The forward-looking orientation of first-generation family firms favours long-term credit by banks in order to expand a healthy business which can be inherited by future generations. These businesses are hence perceived as less risky and more value-creating by external creditors, compared to later-generation family firms. Alternatively, SEW preservation is often less of a target in later-generation family firms, because some descendants consider the firm simply as a source of extra finance and conflicts of interest often arise between multiple generations or different family branches entering the business. Short-term debt may then be employed as a signaling effect of the quality of the firm. At the same time, borrowing long-term capital may become difficult if lenders question the creditworthiness of these businesses. This issue emerged dramatically during the sovereign debt crisis, when a significant contraction of credit to firms was observed throughout the GIPSI countries.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".