Green finance reform, multifaceted collaborative governance, and corporate greenwashing: Evidence from double/debiased machine learning method.
Journal:
Journal of environmental management
PMID:
40288126
Abstract
In order to promote the economic structure's green transformation and identify replicable and generalizable practices in green financial development, the Chinese government has established pilot zones for green finance reform and innovation (PZGFRI) to lead the investment of financial resources in green and low-carbon fields. However, corporates may engage in greenwashing to obtain environmental legitimacy and financial support. This research adopts the double/debiased machine learning model to investigate the influence of green finance reform (GFR) on corporate greenwashing from a multifaceted collaborative governance perspective. The findings document that the green finance reform exacerbates corporate greenwashing. The heterogeneity analysis demonstrates that firms are more inclined to greenwash in samples of firms without bank connections, small-scale firms, low-competition industries, capital-intensive industries, and low fintech areas. Additionally, government environmental attention, media attention, and corporate information opacity diminish the impact of GFR on corporate greenwashing. The findings not only offer valuable guidance for financial institutions and policymakers to understand the impact of GFR on corporate greenwashing and its differentiated effects, but also present new insights for corporate greenwashing governance.