Rent and financial accumulation: locating the profitability of American finance
Bibliographic record
Abstract
American finance has grown immensely profitable in the past four decades, but the precise reasons for this tremendous and sustained growth have not been sufficiently understood. The primary purpose of this paper is to explain the immense profitability of US finance by systematically examining how its sources of profit and types of profit-generating activities have changed since the onset of financialisation in the 1980s. Conceptually, the paper develops a typology of financial profit-generating activities, drawing a separation between credit intermediation, market mediation, and rentierism. Empirically, it examines the changing accumulation dynamics witnessed in US finance since the 1960s using the IRS Statistics of Income, BEA National Income and Product Accounts, and Federal Reserve Flow of Funds data. The paper identifies primary income sources for the sector as a whole and its most profitable subsectors, finding strong evidence that financial profit-making has shifted from lending to ownership and management of capital. It is argued that this transformation has fundamentally changed finance’s relationship with the real economy.
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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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.000 | 0.002 |
| 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".