Understanding how firms interpret and respond to carbon price signals based on their strategic priorities is crucial for aligning climate policies with corporate financial and environmental objectives. We propose a novel composite financial–environmental performance index that adjusts the emphasis on each dimension. Using a machine learning model, we evaluate the sensitivity of this index to carbon emissions allowance prices for a large sample of firms under the European Union Emissions Trading System (EU ETS) from 2008 to 2022, while controlling for a comprehensive set of potential competing predictors. Results suggest that prioritizing financial performance induces negative responses to rising carbon prices, whereas emphasizing environmental performance, without strong profitability incentives, shows limited sensitivity. By examining how carbon price signals can shape firms’ financial–environmental priorities, these findings offer actionable insights for designing policies that better balance profitability and sustainability in the low-carbon transition.

中文翻译：

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收到信号？欧盟 ETS 公司的碳价和财务环境绩效优先级

了解公司如何根据其战略重点解释和响应碳价格信号，对于使气候政策与公司财务和环境目标保持一致至关重要。我们提出了一种新的综合财务-环境绩效指数，该指数调整了对每个维度的强调。使用机器学习模型，我们评估了 2008 年至 2022 年欧盟排放交易体系 （EU ETS） 下大量样本公司的该指数对碳排放配额价格的敏感性，同时控制了一组全面的潜在竞争预测因子。结果表明，优先考虑财务绩效会引起对碳价格上涨的负面反应，而强调环境绩效，而没有强大的盈利能力激励，则显示出有限的敏感性。通过研究碳价格信号如何影响公司的财务环境优先事项，这些发现为设计在低碳转型中更好地平衡盈利能力和可持续性的政策提供了可作的见解。