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Table 3 The regression results regarding the direct effectiveness of the relevant variables with respect to industrial energy consumption in China

From: The impact of relative energy prices on industrial energy consumption in China: a consideration of inflation costs

Variables

C1

C2

C

–

–

−8.351 (−4.834***)†

−12.283 (−6.91***)

Y

−1.148 (−1.780*)

0.892 (11.644***)

−0.870 (−3.856***)

–

S

3.423 (6.083***)

1.649 (11.526***)

−0.128 (−0.410)

−0.857 (−3.18***)

E

–

–

3.058 (9.122***)

3.869 (10.63***)

T

1.045 (3.118***)

–

0.355 (−3.117***)

–

P

−0.761 (−2.523**)

−0.337 (−5.159***)

−0.108 (−0.934)

−0.250 (−6.04***)

 

R2 = 0.953

DW = 0.582

R2 = 0.996

DW = 1.903

R2 = 0.990

DW = 1.878

R2 = 0.981

DW = 1.969

  1. *, **, *** Rejection of the null hypothesis at the 10, 5 and 1 % confidence levels, respectively. For the regression model C1, which includes Y, S and P, the iterative estimation method is used because the regression results that use OLS are not sound
  2. †The values in parentheses are t value
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