Table 5 Results of intermediary effect regression 1: energy consumption scale

From: From data to decarbonization: the digital economy’s role in reducing carbon emissions intensity and advancing environmental justice

 

(1)

(2)

(3)

(4)

(5)

(6)

 

EC

DIGIT

EC

EC

DIGIT

EC

DIGIT

0.1098

 

−0.6718**

0.0865

 

−0.5091*

 

(0.0794)

 

(0.2678)

(0.0641)

 

(0.2442)

IV

 

0.0064***

  

0.0062***

 
  

(0.0014)

  

(0.0013)

 

Ind

   

−0.0504*

0.0648***

−0.0200

    

(0.0219)

(0.0176)

(0.0304)

Pop

   

0.0143

−0.0070

0.0082

    

(0.0173)

(0.0096)

(0.0204)

Urban

   

0.0463

0.0297

0.0610*

    

(0.0268)

(0.0182)

(0.0286)

Fis

   

−0.0300

−0.0162

−0.0661**

    

(0.0189)

(0.0213)

(0.0250)

Ele

   

−0.0002

−0.0017

−0.0004

    

(0.0065)

(0.0023)

(0.0063)

Open

   

−0.0791***

−0.0131

−0.0845***

    

(0.0194)

(0.0099)

(0.0204)

Tech

   

0.0002

0.0004

0.0005

    

(0.0008)

(0.0007)

(0.0008)

_cons

−0.0035

0.1238***

 

0.1479

−0.1037

 
 

(0.0230)

(0.0352)

 

(0.1902)

(0.0935)

 

City Fixed Effect

YES

YES

YES

YES

YES

YES

Year Fixed Effect

NO

YES

YES

YES

YES

YES

Kleibergen–Paap rk LM statistic

  

5.079

  

5.081

   

{0.0242}

  

{0.0242}

Cragg-Donald Wald F statistic

  

75.112

  

68.680

   

[8.96]

  

[8.96]

N

2216

2280

2208

2216

2280

2208

Root MSE

0.0106

0.0090

.01193

0.0099

0.0088

.01051

  1. *, **, *** represent the statistically significant at 10%, 5%, and 1% levels, respectively. Standard errors in () are adopted 2-way robust clustered at year and city levels. The figures in {} is the P statistics of Kleibergen–Paap rk LM test with the null hypothesis is the IV cannot be fully identified. The figures in [] is the critical value of Cragg-Donald Wald F test at 15% maximal IV size, proposed by Stock-Yogo (2005)112. MSE is shortened for Mean Square Error.
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