1290 This question is particularly relevant in the mining industry, where firms often share similar operational risks, regulatory environments, and reputational exposure. If investors perceive environmental risk as partially shared across firms, a negative event affecting one company could trigger a reassessment of the entire sector. This mechanism is consistent with the idea of reputational spillovers and sectoral contagion in financial markets. The objective of this paper is to evaluate whether major mining-related environmental events generate (i) statistically and economically significant impacts on responsible firms, and (ii) spillover effects on related peer companies. The analysis is based on a sample of ten well-documented events involving major global mining firms and applies a standard event-study methodology. The contribution of this study is twofold. First, it provides a comparative analysis across multiple mining events rather than focusing on a single case. Second, it explicitly evaluates spillover effects using aggregated measures across peer firms, allowing for a more robust interpretation of sectoral contagion. 2. METHODOLOGY 2.1 Event study framework The empirical analysis is based on the event study methodology originally developed by Fama et al. (1969) (Fama et al., 1969), which is widely used to evaluate how financial markets react to new information. Abnormal returns (AR) are estimated using the Fama–French three-factor model (Fama & French, 1993): V),> −V3,> =–) +G!)(V-,> −V3,>)+G#)JX—> +GZ)õX:> +“),> where V),>is the return of firm T, V3,>is the risk-free rate, V-,>is the market return, and SMB and HML represent size and value factors, respectively. Abnormal returns are computed as: }V),> =(V),> −V3,>)−ÖVt,>−V3,> ” Ü Cumulative abnormal returns (CAR) are then calculated over the event window: s}V),[>#,>2] =C} >2 >/># V),> Statistical significance is evaluated using standard t-tests. 2.2 Event windows To capture both immediate and delayed market reactions, four symmetric event windows are analyzed; [-3, +3], [-7, +7], [-14, +14], [-21, +21]. This allows assessing whether the impact is instantaneous or evolves over time as additional information becomes available. 2.3 Sample selection The study considers ten major environmental or environmental-regulatory events involving large mining companies: VALE S.A. – Brumadinho dam collapse (2019), BHP Group – Samarco/Mariana tailings
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