Business Groups and the Big Push: Meiji Japan's Mass Privatization and Subsequent Growth
Bibliographic record
Abstract
Paul Rosenstein-Rodan argues that economic development requires coordinated investment in many interdependent industries, and prescribes a flood of state-controlled investment across all sectors—a so-called big push. Widespread government failure defeated twentieth-century ‘big push’ schemes. But spillovers across firms and industries, and from public goods, hold-up problems, and capital market limitations are real, and justify coordinated growth across sectors if it can be done without government failures. Large, extensively diversified pyramidal business groups of listed firms dominate the histories of developed economies and the economies of developing economies. Arguing that such groups provided this coordination in prewar Japan after a state-run big push failed, we propose that pyramidal business groups are private-sector mechanisms for coordinating big push growth, and that competition between rival groups induces efficiency unattainable in a state-run big push. We postulate that a successful business-group led big push requires economic openness, basic public goods, rule of law, separation of the state from business, and a timely demise of business groups when the big push phase is complete.Where these criteria are not met, growth stalls and oligarchic families become too powerful to dislodge.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.006 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.000 | 0.005 |
| Research integrity | 0.001 | 0.001 |
| 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".