SHORT- AND LONG-TERM EFFECTS OF THE 9/11 EVENT: THE INTERNATIONAL EVIDENCE
Bibliographic record
Abstract
This paper analyzes the short- and long-term effects of the September 11, 2001 terrorist attacks on a comprehensive sample of stock market indices from 33 industrial and emerging economies. From a finance-theoretic point of view, we employ the international capital asset pricing model (ICAPM) to analyze the incidence of the 9/11 event. Consistent with expectations, we document statistically negative short-term stock market reactions to the 9/11 event for 28 countries. More importantly, we find increases in the level of systematic risk for 10 stock markets which attest to the presence of negative permanent effects emanating for the 9/11 event. However, a great many capital markets (including the US, Canada, Japan, China, Russia, and the largest European economies) did not experience statistically significant increases in systematic risk in the post-9/11 period. The decisiveness of the evidence clearly points in the direction of resilience and flexibility of the world capital markets.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".