On the Stock Market's Reaction to Major Railroad Accidents
Bibliographic record
Abstract
This study examines the impact of train accidents on the stock price performance of the involved railroad companies. We employ a sample of 26 accidents involving trains operated by publicly traded U.S. and Canadian railroad companies between January 1993 and December 2003. Event study methodology is used to measure the abnormal performance of the involved railroad firms to these accidents. In addition, a series of univariate tests and cross-sectional regression analysis is employed to determine the factors that drive the abnormal returns for the firms in the sample. The magnitude of the initial price decline appears to be driven by various characteristics of both the firm and the accident itself. Specifically, there is strong evidence that suggests that one of the main determinants of the abnormal returns is expected legal liability claims against the railroads. Abnormal performance is negatively related to firm size and the number of injuries and fatalities resulting from the accident. In addition, accidents that result in hazardous material spills cause significantly larger stock price drops in the days following the event. Finally, investors appear to differentiate between accident causes. Accidents caused by reckless or illegal behavior on behalf of one or more of the railroad company's employees result in particularly large price declines. Accidents caused by mechanical failures or signal malfunctions, on the other hand, only cause small stock price drops.
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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 | 0.007 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.004 |
| 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 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".