1294 Similarly, Mount Polley (Imperial Metals) shows an even larger CAR of -46.35% in the [−14,+14] window, also significant at the 1% level, representing the largest value destruction observed in the sample. Brumadinho (VALE) presents a CAR of -20.71% in the [−7,+7] window, significant at the 5% level, confirming that major tailings failures can lead to sharp and statistically robust market penalties. Second, economically large effects are more widespread than statistical significance alone would indicate. For instance, Newmont and Teck register CAR of -28.65% and -23.07%, respectively, yet without statistical significance at conventional levels (p-values > 0.10). This gap between magnitude and significance highlights the high volatility inherent in mining equities, where large valuation changes can occur but are not always estimated with sufficient precision to reject the null hypothesis. Importantly, these results indicate that investors may still experience substantial losses even in cases where statistical inference is inconclusive. Third, spillover effects on peer firms are generally smaller but economically meaningful and heterogeneous. The strongest case is Samarco, with an average peer CAR of -33.44% and 100% negative responses, indicating a sector-wide reassessment of risk. Other events show consistent but smaller negative effects, while Brumadinho exhibits a strong firm-specific impact without clear contagion, suggesting that investors distinguish between systemic and idiosyncratic shocks. Fourth, the temporal dimension of market reactions is non-trivial, as the magnitude of CAR often increases in longer event windows. For several firms, including BHP, Imperial Metals, and Newmont, the most negative CAR is observed in medium to long windows (e.g., [−14,+14]or [−21,+21]), rather than in short windows. This suggests that the market does not fully incorporate the implications of environmental events immediately, but instead adjusts valuations progressively as more information becomes available regarding legal liabilities, regulatory sanctions, and long-term reputational damage. Taken together, these findings indicate that environmental risk in mining has both high-impact firm-level consequences and measurable, though heterogeneous, sectoral spillovers. The magnitude of direct effects can reach losses of up to 46% in firm value, while peer effects, in extreme cases, can involve broad negative responses across 100% of comparable firms. From a broader perspective, these results have important implications. For investors, they suggest that environmental risk should be considered not only as a firm-specific factor but also as a potential source of systematic sectoral exposure. For mining companies, the scale of observed CAR losses underscores the financial materiality of environmental failures and the importance of proactive risk management. For regulators, the presence of spillover effects implies that major environmental events may affect market-wide perceptions of the industry, potentially influencing capital allocation and cost of capital beyond the directly responsible firm. Overall, this study provides quantitative evidence that environmental disasters in mining can generate large and statistically significant value destruction, as well as non-negligible spillover effects, whose magnitude and persistence depend on event severity, visibility, and the dynamics of information diffusion in financial markets. ACKNOWLEDGEMENTS The authors acknowledge the academic support provided by the Department of Mining Engineering at the University of Chile. REFERENCES Assis, T. P., Cordeiro, F. F., & Schiavon, L. C. (2023). How stock market reacts to environmental disasters and judicial decisions: A case study of Mariana’s dam collapse in Brazil. International Review of Law and Economics, 73, 106105. https://doi.org/10.1016/J.IRLE.2022.106105
RkJQdWJsaXNoZXIy MTM0Mzk2