BUSINESS GROUPS IN THE UNITED STATES: A REVISED HISTORY OF CORPORATE OWNERSHIP, PYRAMIDS AND REGULATION, 1930-1950
Bibliographic record
Abstract
The extent to which business groups ever existed in the United States and, if they did exist, the reasons for their disappearance are poorly understood. In this paper we use hitherto unexplored historical sources to construct a comprehensive data set to address this issue. We find that (1) business groups, often organized as pyramids, existed at least as early as the turn of the twentieth century and became a common corporate form in the 1930s and 1940s, mostly in public utilities (e.g., electricity, gas and transportation) but also in manufacturing; (2) In contrast with modern business groups in emerging markets that are typically diversified and tightly controlled, many US groups were focused in a single sector and controlled by apex firms with dispersed ownership; (3) The disappearance of US business groups was largely complete only in 1950, about 15 years after the major anti-group policy measures of the mid-1930s; (4) Chronologically, the demise of business groups preceded the emergence of conglomerates in the United States by about two decades and the sharp increase in stock market valuation by about a decade, so that a causal link between these events is hard to establish, although there may well be a connection between them. We conclude that the prevalence of business groups is not inconsistent with high levels of investor protection; that US corporate ownership as we know it today evolved gradually over several decades; and that policy makers should not expect policies that restrict business groups to have an immediate effect on corporate ownership.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.002 | 0.004 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".