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Figure/Table detail

Examining the impacts of network position on urban carbon emissions efficiency in China
SHENG Kerong, LI Xiaorui, SUN Wei, WANG Chuanyang
Acta Geographica Sinica, 2023, 78(11): 2864-2882.   DOI: 10.11821/dlxb202311014

(1) (2) (3) (4) (5) (6)
Degree UCEE Between UCEE Eigen UCEE
Distport -0.04160***
(0.009)
-0.0846***
(0.018)
-0.4362***
(0.097)
Degree 0.6723***
(0.163)
Between 0.3307***
(0.081)
Eigen 0.0641***
(0.016)
控制变量 是 是 是 是 是 是
AR test 65.30*** 65.31*** 65.30***
Wald test 16.94*** 16.53*** 16.64***
Tab. 7 Robustness test results of two-step IV-Tobit models
Other figure/table from this article
  • Fig. 1 Mechanisms and characteristics of network position affecting urban carbon emissions efficiency
  • Tab. 1 Indicators for measuring the total factor carbon emissions efficiency of cities
  • Tab. 2 Control variables and their definition methods
  • Fig. 2 The coupling patterns of carbon emissions efficiency and degree centralities of Chinese cities in 2005 and 2020
  • Tab. 3 The baseline regression results of panel Tobit model
  • Tab. 4 Robustness test results for replacing carbon emissions efficiency measurement methods
  • Tab. 5 Robustness test results of spatial lag models
  • Tab. 6 Robustness test results of lagged variable models
  • Tab. 8 Test results of chain multiple mediation models
  • Tab. 9 Results of spatial heterogeneity test
  • Tab. 10 Results of type heterogeneity test

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