Conference Programme

Biodiversity loss is increasingly recognized as a material financial risk, yet little is known about how investors integrate spatial ecological exposure with firm-level financial information. We study whether corporate biodiversity exposure (CBE), measured by the proximity of a firm’s polluting facilities to protected or conservation-priority areas, affects investors’ responses to earnings announcements. We argue that biodiversity exposure makes it more costly for investors to assess how earnings news maps into future cash flows and firm value, thereby weakening the incorporation of earnings information into prices at the time of disclosure. Consistent with this argument, firms with higher CBE exhibit significantly weaker earnings responsiveness, indicating that earnings surprises receive less valuation weight when they are announced. This attenuation is accompanied by lower trading activity and reduced liquidity around earnings announcements. Using a stacked difference-in-differences design based on protected-area expansions, we show that earnings–return sensitivity declines when firms become newly exposed to biodiversity-sensitive areas. We also find no evidence that the lower ERC reflects anticipatory pricing or delayed adjustment. We further show that CBE is related to valuation-relevant fundamentals, including weaker future growth and a higher ex ante cost of equity. However, these fundamentals do not explain the attenuation in earnings responsiveness, which also remains robust to controls for earnings quality, general ESG orientation, and broader climate risks. The effect varies predictably with ecological and institutional transparency, disclosure, and external monitoring, supporting an information-processing interpretation. Overall, our findings identify biodiversity exposure as a spatial, firm-level source of valuation uncertainty and show that ecological complexity shapes how earnings news is incorporated into asset prices.

This study examines how euro area banks factor pollution-induced biodiversity risks into lending decisions, using data from 832 banks and 5,000 major polluters. Our results show that banks are increasingly pricing these risks by adjusting loan-to-value ratios and interest rates. Banks adjust lending conditions in line with EU pollution and biodiversity protection legislation, particularly for companies with large pollution footprints near biodiversity-protected areas or those contributing to Environmental Quality Standards failures of downstream surface waters. The former is driven primarily by banks’ adoption of biodiversity policies and public commitments to the Equator Principles, while the latter is a result of regulatory risks. Our findings inform financial supervisors on how banks manage risks associated with the EU’s zero pollution ambition, shed light on the interplay between biodiversity protection legislation and banks’ lending decisions, and offer actionable guidance on leveraging existing regulatory frameworks to address the climate-biodiversity-pollution nexus.

While investors increasingly view firm impacts on nature as financially material, quantifying corporate biodiversity footprints remains challenging due to the complex nature of biodiversity. We introduce an ecologically grounded, data-driven method for estimating firm-level biodiversity footprints. We showcase our method by applying a spatial difference-in-difference design to a data set combining 30m-resolution forest biodiversity data, water pollution data by U.S. facilities, and hydrological model results. We find that toxic water releases have an adverse effect on the downstream forest ecosystem, reducing the tree density and its species diversity. A standard deviation increase in toxic effluent is associated with a 7.5% decline in tree population in the immediate downstream area, with aggregate water pollution leading to a total loss of 18 million trees over the seven-year sample period. A facility's biodiversity footprint is driven more by its siting in heavily forested areas than by variations in effluent volume.