Network Effects in Corporate Emissions: Evidence from a Data‐Dependent Spatial Panel Model

Abstract We study spillover effects in corporate toxic emissions using a heterogeneous panel of U.S. industrial facilities from 2000 to 2023. Rather than imposing a network structure a priori , we uncover an unobserved web of influence directly from the data using recent advances in high‐dimensional network econometrics. Indirect effects transmitted through the estimated network account for roughly 28% of the total impact of key firm balance‐sheet characteristics on emissions. By contrast, distance‐based networks generate no statistically discernible spillovers, while a priori firm‐ or industry‐based networks substantially overstate within‐group spillins relative to the data‐driven network. These findings show that the structure and strength of interfirm linkages matter critically for assessing systemic environmental risk and designing targeted regulation. Methodologically, the paper provides a flexible framework for quantifying facility‐level emissions spillovers and their consequences in financial and policy settings.