Is the Net Worth of Financial Intermediaries More Important than That of Non-Financial Firms?
Bibliographic record
Abstract
To explore the relative macroeconomic importance of financial intermediaries' (FIs') net worth to that of non-financial firms (entrepreneurs), we extend the financial accelerator model of Bernanke, et al. (1999), such that both FIs' and entrepreneurs rely on costly external debt. Our model, which is calibrated to the U.S. economy, highlights two features of the FIs' net worth. First, the relative size of FIs' net worth as compared to entrepreneurial net worth, namely, the net-worth distribution in the economy, is important for the financial accelerator effect. Second, a shock to the FIs' net worth has greater aggregate impact than that to entrepreneurial net worth. The key reason for these findings is the low net worth of FIs' in the United States. Our results imply that the ongoing regulatory reforms that protect banks' net worth from irrational exuberance or foster its accumulation are beneficial for macroeconomic stability.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".