Bibliographic record
Abstract
Purpose – The purpose of this paper is to illustrate and examine the effects of ultimate ownership, institutionality and their interactions on capital structure in a unified framework, based on evidence from China. Design/methodology/approach – Using six years of panel data of Chinese non-financial listed firms between 2004 and 2009, this paper estimates with correlation analysis and multiple regression analysis. Findings – This paper finds that debt financing facilitates the ultimate owner's expropriation behavior. The separation of control rights and cash flow rights is positively related to capital structure, while cash flow rights negatively affect it. Compared with private ultimate owners, state ultimate owners have less incentive to reap the benefits of expropriation, implying that the separation of control rights and cash flow rights has a smaller effect on the capital structure of state-owned firms. The improvement of institutionality can restrain ultimate owners' expropriation behavior, and regional institutional development is negatively related to capital structure. The separation of control rights and cash flow rights has a smaller positive effect on capital structure in regions with better-developed institutionality. Originality/value – This paper incorporates ultimate ownership and institutionality into a unified analytical framework of capital structure. It not only enriches related studies on capital structure, but also helps us understand the institutional roots of irrational capital structure behaviors in China. This paper also provides further evidence on ultimate owners' expropriation of minority shareholders through debt financing.
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".