Data platform openness and corporate greenwashing: empirical evidence from listed companies in China

Abstract

Given the global low-carbon transition, the rapid diffusion of ESG practices has been accompanied by growing concerns about corporate greenwashing and the credibility of sustainability disclosures. This study examines whether public government data platform openness constrains measured greenwashing. I exploit the staggered rollout of city-level platforms in China and construct a panel of A-share listed firms from 2009 to 2023. The empirical design combines two-way fixed effects with event study diagnostics, a Borusyak-Jaravel-Spiess imputation estimator, a stacked event study estimator, placebo tests, alternative greenwashing measures, matching, city-specific trends, and controls for concurrent policies. Although the coefficient becomes less precise under the saturated province-by-year and industry-by-year fixed effects, the estimates are consistently negative in the baseline and the most robust specifications. Therefore, the evidence supports a governance effect conditional on identifying assumptions, rather than unconditional policy exogeneity. Theoretical analysis bridges the individual-level Fraud Triangle to organizational disclosure strategy. Managers translate pressure, opportunity, and rationalization into firm-level reporting routines, while public data raise detection risk, improve cross-checkability, and weaken shared justifications for symbolic disclosure. Channel-consistent heterogeneity is stronger when government coordination, data infrastructure, and regulatory conditions are more developed. However, these subgroup patterns are not interpreted as formal mediation. Additional tests show no material differences in regional economic development, and the effect is concentrated in non-resource-based cities. This study provides evidence that public data transparency complements environmental governance and improves the credibility of corporate sustainability claims.