Drivers and Policy Choices of Industrial Total-Factor Coal Productivity: Evidence From Eastern China

Identifying the critical factors of industrial total-factor coal productivity (TCP) and its promotion paths will help achieve goals regional energy conservation pollution reduction. Based on perspective productivity, this paper integrates methods stochastic frontier analysis (SFA), Kaya identity, STIRPAT model to systematically diagnose temporal spatial characteristics heterogeneous sources TCP in 11 provinces eastern China, it proposes some differentiated regulatory policies for different provinces. The results show that is increasing year by tends converge, which indicates more challenging. Further research shows there are significant differences impact economic development level (EDL), structure (IES), consumption intensity (ECI), (ECS) TCP. As original driving technological progress, R&D investment (RII) levels (RIL) relatively consistent regions. former has a negative congestion effect due imbalance structure, while latter positive Therefore, region should increase expenditure optimize as general way improve each adopt utilization according local conditions.