🤖 AI Summary
This study examines how firms engage in AI-related greenwashing—leveraging “AI narratives” to gain financing advantages and distort resource allocation. Exploiting China’s 14th Five-Year Plan as a quasi-natural experiment, the paper pioneers the linkage between macro-level policy shocks and corporate AI greenwashing behavior. Using text analysis and residuals from patent output, the authors construct a proxy for AI greenwashing and employ difference-in-differences, joint estimation, and external validation strategies to identify causal effects. Findings reveal that, following the policy shock, AI greenwashing firms experience a significant 12.5-basis-point increase in debt financing costs. Market discipline is amplified by higher managerial ownership and analyst attention, while supply chain concentration and geographic proximity to banks mitigate this penalty, highlighting how policy interventions can activate debt-market discipline in emerging economies.
📝 Abstract
The rapid development of artificial intelligence motivates firms to engage in AI washing. This study examines whether strategic policy shocks increase debt financing costs for such firms. Leveraging China's 14th Five Year Plan as a quasi natural experiment, we identify AI washing through the residual between AI narrative intensity and patent output. External validation confirms this decoupling reflects strategic deception evidenced by subsidy extraction and future regulatory violations rather than benign ambition, supporting its validity as an AI washing proxy. Difference in differences estimations reveal that AI washing firms experience a 12.5 basis point relative increase in debt financing cost afterward. Joint estimation confirms simultaneous adjustments across financing and innovation margins. Management shareholding and analyst attention amplify the penalty while supply chain concentration and bank proximity attenuate it. Results remain robust across checks. Our findings illuminate how macro level policy shocks activate market discipline in emerging market debt markets.