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This study takes the central, provincial and municipal Environmental Protection Interviews (multi-hierarchical EPI) as a mechanism innovation for precise environmental regulation in Yangtze River Delta (YRD) and constructs a multi-cutoff regression discontinuity design to accurately measure the policy effects of multi-hierarchical EPI on air quality improvement in YRD. Overall, the findings demonstrate that EPI at all levels is correlated with improving the air quality for interviewed cities in the short term, which tends to weaken after 3–6 months and may even rebound to the initial level after a longer period. The improvement effect of EPI on air quality is primarily reflected in controlling the pollutant concentration of PM2.5, PM10 and NO2. Moreover, there were great differences in the policy effects of the multi-hierarchical EPI for air quality improvement amongst cities in YRD. The higher administrative level of EPI, the stronger policy effects of the corresponding EPI were. The provincial and municipal EPI are likely to involve initiative regulation and exert greater effects. Some cities under the provincial and municipal EPI could break through the hierarchical constraints and shift to stronger air quality improvement effects, providing new reference for China's precise environmental governance mechanism.

Low-carbon city pilot (LCCP) policy is a progressive pollution regulation policy. Besides its role in carbon emission reduction, it has a profound impact on green growth performance and green innovation efficiency. Based on the data of 12 pilot cities and 14 non-pilot cities in the Yangtze River Delta (YRD), this study applies the PSM-DID and spatial mediating model to investigate the multi-dimensional policy effects of LCCP policy on green growth performance and green innovation efficiency. First, the direct effect of LCCP policy on green growth performance has reached 1.46%, ever since its implementation in 2017. Second, considering the intercity innovation cooperation in YRD, LCCP policy has influenced green innovation efficiency by an increase of 12.6%. Furthermore, the time-spatial DID model and multiple mediating effect model identify that LCCP policies have significantly improved green innovation cooperation. Such policies act on the industrial structure upgrading path to achieve the ultimate objective of carbon emission reduction and green growth performance. Third, the green innovation cooperation and substantial transformation of industrial structure upgrading played an important role in realizing the LCCP policy's effect, with its mediating effect reaching 33.63%. [ABSTRACT FROM AUTHOR]

Reasonable adjustment of medical service price is of critical importance and remains puzzled in health reform in China. Previous literatures only present qualitative suggestions or implement quantitative analysis from the perspective of price adjustment itself. Innovatively, the research establishes a conduction mechanism measurement of medical care price from the perspective of joint investigation of other environmental factors through the bridge of production efficiency in complex reform. The conduction mechanism is identified by conduction style and conduction effect with the monthly data of 16 provincial public hospitals in Zhejiang Province during 200701-201107. First, the main conduction style is labor input during 201006-201107. Second, different environment factors exert different roles on conduction style. (1) Both personal expenditures and governmental fiscal inputs promote the production efficiency of labor input, with the conduction strengths reaching 2.55% and 16.58%. (2) Running cost and health price index hardly promote the production efficiency of labor input, with conduction strengths reaching -1.33% and -1.94%. (3) Jointly, the four environmental factors exert positive impact on production efficiency of labor input overall, with conduction strength reaching 12.48%, which presents strongly evidence that government should raise medical service price so as to adjust the price distortion due to different environmental factors. [ABSTRACT FROM AUTHOR]