Stock Market Reaction to Supply Chain Disruptions from the 2011 Great East Japan Earthquake
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Bibliographic record
Abstract
Problem definition: This paper provides empirical evidence on the effect of the 2011 Great East Japan Earthquake (GEJE) on the financial performance of firms. Academic/practical relevance: The GEJE was characterized as the most significant disruption ever for global supply chains. In its aftermath, there was a great deal of debate about the risks and vulnerabilities of global supply chains, and there were calls to redesign and restructure supply chains. Methodology: We empirically estimate the effect of the GEJE on the stock prices of firms. Our analyses are based on a global sample of 470 firms collected from articles and announcements in the business press that identify affected firms, as well as 382 firms that are not mentioned in the business press but are in industries potentially subject to contagion or competitive effects. Results: We estimate that firms experiencing supply chain disruptions as a result of the GEJE lost on average 5.21% of their shareholder value during the one-month period after the GEJE. For Japanese firms, the effect was much more severe with an average 9.32% loss in shareholder value. Non-Japanese firms averaged a 3.73% loss in shareholder value. We also find that upstream and downstream supply chain propagation effects from the GEJE are negative, and the contagion effect on firms related to the nuclear industry is very negative. For firms in the rebuilding industries or competitors to firms affected by the GEJE, the competitive effect from the GEJE is positive. Managerial implications: The loss suffered by both Japanese firms and non-Japanese firms experiencing supply chain disruptions as a result of the GEJE is economically significant. Although the loss is more severe for firms whose operations were directly affected by the GEJE, it is also significant for firms who experienced indirect effects from their upstream and downstream supply chain partners, further confirming the importance of supply chain risk mitigation strategies.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 0.016 |
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 it