Vertical Integration, Institutional Determinants and Impact: Evidence from China
Bibliographic record
Abstract
Where legal systems and market forces enforce contracts inadequately, vertical integration can circumvent these transaction difficulties.But, such environments often also feature highly interventionist government, and even corruption.Vertical integration might then enhance returns to political rent-seeking aimed at securing and extending market power.Thus, where political rent seeking is minimal, vertical integration should add to firm value and economy performance; but where political rent seeking is substantial, firm value might rise as economy performance decays.China offers a suitable background for empirical examination of these issues because her legal and market institutions are generally weak, but nonetheless exhibit substantial province-level variation.Vertical integration is more common where legal institutions are weaker and where regional governments are of lower quality or more interventionist.In such provinces, firms led by insiders with political connections are more likely to be vertically integrated.Vertical integration is negatively associated with firm value if the top corporate insider is politically connected, but weakly positively associated with public share valuations if the politically connected firm is independently audited.Finally, provinces whose vertical integrated firms tend to have politically unconnected CEOs exhibit elevated per capita GDP growth, while provinces whose vertically integrated firms tend to have political insiders as CEOs exhibit depressed per capita GDP growth.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".