Creditor Nations’ Equity Indexes and the U.S. Debt Downgrade
Bibliographic record
Abstract
On Friday, August 5, 2011 Standard and Poor’s rating agency downgraded long-term U.S. Treasury debt from AAA to AA+ for the first time in history. In this study, the impact of this downgrade on world stock markets is examined. We analyze the immediate effect of this downgrade on leading stock indices of 31 nations owning U.S. Treasury debt. We find that the downgrade had a marked effect on the first trading day following the announcement. It truly was a macroeconomic event. We further examine whether return differentials were partially explained by the level of U.S. debt that each country possessed (both on an absolute and relative basis). We find no evidence of this relationship, which suggests equity markets in countries owning considerable Treasury securities suffered no more or less than equity markets in countries with less U.S. Treasury debt.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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".