Regional environmental regulation efficiency: spatiotemporal characteristics and influencing factors

  • Yu TuEmail author
  • Benhong PengEmail author
  • Guo Wei
  • Ehsan Elahi
  • Tongrui Yu
Research Article


Research regarding the regional environmental regulation efficiency (ERE) and influencing factors can provide theoretical guidance for regions to improve their ERE effectively. By employing a two-step approach, the data envelopment analysis (DEA) CCR-BCC model is built with the inclusion of scale changes, and a Tobit model is developed to explore the influencing factors for the regional ERE, followed by an application to analyze the spatiotemporal variations of ERE in Jiangsu province from 2005 to 2015. It is found that in time dimension, the ERE lies generally in a weak effective interval of [0.5, 1) and displays a shock upward trend. In the spatial dimension, the ERE presents an obvious “bilateral effect”, namely, the efficiency is high for both the southern and northern of Jiangsu province but lower for the middle area. Besides, GDP per capital, industrial structure, trade openness, and population growth are among the main influencing factors of ERE. The findings revealed that temporary short-term policies have noticeable impact on the regional ERE, and “matching effect” between the ERE and regional economic development does not present.


Environmental regulation efficiency CCR-BCC model Spatiotemporal analysis Tobit model 



The thesis was financially supported by HRSA, US DHHS (No. H49MC00068), the National Natural Science Foundation of China (No. 71850410541, No. 71263040), the Key Project of National Social and Scientific Fund Program (No. 18ZDA052), the Project of National Social and Scientific Fund Program (No. 17BGL142), the Key Meteorological Soft Science Projects of China Meteorological Administration (No. 2019ZDIANXM25), the Postgraduate Research & Practice Innovation Program of Jiangsu Province (No. KYCX18_1041), the Practical Innovation Training Program for College Students in Jiangsu Province (No. 201810300063Y). Authors highly acknowledged to Associate Professor Ehsan Elahi who helped for technical review and data analysis of the thesis.


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Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2019

Authors and Affiliations

  1. 1.Binjiang CollegeNanjing University of Information Science & TechnologyWuxiChina
  2. 2.School of Economics and ManagementTsinghua UniversityBeijingChina
  3. 3.School of Management Science and EngineeringNanjing University of Information Science & TechnologyNanjingChina
  4. 4.Department of Mathematics & Computer ScienceUniversity of North Carolina at PembrokePembrokeUSA
  5. 5.School of BusinessNanjing University of Information Science & TechnologyNanjingChina

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