Establishing specialized environmental adjudication divisions within China’s intermediate courts reduces local air pollution by approximately 3.9%. We examine this governance innovation using satellite-derived PM2.5 data for 324 prefecture-level cities (2011–2023) and heterogeneity-robust difference-in-differences methods that address biases in conventional estimators under staggered treatment adoption. Under city-level clustering, which reflects the unit of treatment assignment, four complementary estimators (Callaway–Sant’Anna, Sun–Abraham, Borusyak–Jaravel–Spiess, and two-way fixed effects) consistently yield negative and statistically significant treatment effects (ATT ranging from −0.037 to −0.054, p<0.05). With the more conservative province-level clustering (31 clusters), significance attenuates for all estimators, with p-values ranging from 0.078 to 0.289; we interpret this as reflecting the small number of clusters rather than the absence of a true effect, although sensitivity to the clustering level remains a limitation. Event study analysis confirms parallel pre-treatment trends and persistent post-treatment effects. Heterogeneity patterns are directionally consistent but statistically inconclusive (n=12 cohorts): reductions appear larger in more industrialized and more polluted cohorts, though the precise mechanism remains unidentified. A spatial analysis finds no evidence of pollution displacement, but SUTVA is violated by concurrent court adoption in neighboring cities; once the neighbor pool is restricted to never-treated cities, the apparent negative spillover attenuates to non-significance, so the direction of bias in our main estimates cannot be determined. These results demonstrate that governance specialization can meaningfully complement regulatory instruments in advancing sustainability goals for air quality.
Chen et al. (Wed,) studied this question.