🤖 AI Summary
This study investigates whether improvements in ecological efficiency foster collaborative environmental governance between local governments and the public. Using provincial-level panel data from China, the authors integrate NLP-based analysis of administrative complaint texts with regression discontinuity design and difference-in-differences estimation. They identify, for the first time, a statistically significant threshold effect of ecological efficiency: once this threshold is crossed, the probability of government–public co-responses to environmental complaints increases by 24 percentage points. The findings demonstrate that ecological efficiency functions not merely as an environmental performance metric but also as a critical catalyst for participatory governance, establishing a causal “efficiency–participation” mechanism. The results provide quantifiable policy levers and rigorous causal evidence for green governance transformation, while advancing theoretical understanding of how institutional incentives interact with public behavior in environmental governance.
📝 Abstract
We examine whether higher eco-efficiency encourages local governments to co-produce environmental solutions with citizens. Using Chinese provincial data and advanced textual analysis, we find that high eco-efficiency strongly predicts more collaborative responses to environmental complaints. Causal inference suggests that crossing a threshold of eco-efficiency increases co-production probabilities by about 24 percentage points, indicating eco-efficiency's potential as a catalyst for participatory environmental governance.