Table 1 Statistical description
Variable
|
Obs
|
Mean
|
Std
|
Min
|
25%
|
Median
|
75%
|
Max
|
AB_NET_HIRE
|
19,513
|
0.208
|
0.355
|
0.002
|
0.050
|
0.109
|
0.212
|
2.575
|
POLICY
|
19,513
|
0.655
|
0.476
|
0.000
|
0.000
|
1.000
|
1.000
|
1.000
|
GCRES×POLICY
|
19,513
|
0.048
|
0.214
|
0.000
|
0.000
|
0.000
|
0.000
|
1.000
|
GCRES
|
19,513
|
0.074
|
0.261
|
0.000
|
0.000
|
0.000
|
0.000
|
1.000
|
SIZE
|
19,513
|
22.090
|
1.304
|
19.120
|
21.200
|
21.950
|
22.850
|
25.940
|
ROA
|
19,513
|
0.032
|
0.061
|
-0.243
|
0.010
|
0.031
|
0.059
|
0.206
|
LEV
|
19,513
|
0.483
|
0.217
|
0.063
|
0.318
|
0.484
|
0.640
|
1.100
|
TANGIBILITY
|
19,513
|
0.244
|
0.179
|
0.002
|
0.103
|
0.208
|
0.352
|
0.750
|
AGE
|
19,513
|
2.780
|
0.319
|
1.946
|
2.565
|
2.833
|
2.996
|
3.401
|
SOE
|
19,513
|
0.561
|
0.496
|
0.000
|
0.000
|
1.000
|
1.000
|
1.000
|
STD_NET_HIRE
|
19,513
|
0.278
|
0.446
|
0.006
|
0.053
|
0.117
|
0.274
|
2.119
|
LABOR_INTENSITY
|
19,513
|
0.010
|
0.009
|
0.000
|
0.004
|
0.007
|
0.013
|
0.051
|
STD_CFO
|
19,513
|
0.050
|
0.045
|
0.003
|
0.021
|
0.037
|
0.064
|
0.253
|
STD_SALES
|
19,513
|
0.331
|
0.453
|
0.014
|
0.098
|
0.185
|
0.343
|
2.360
|
Notes: This table indicates statistical description on labor investment efficiency, green credit policy and control variables used in our study. The sample period is 2007-2017. The unit of observations is the firm-year. We winsorize all consecutive variables at the 1st and 99th percentiles. Please see Appendix for detailed variable definitions.
Table 2 Correlation matrix (Spearman for the upper-right, Pearson for the bottom-left)
|
A
|
B
|
C
|
D
|
E
|
F
|
G
|
H
|
I
|
J
|
K
|
L
|
M
|
N
|
(A)AB_NET_HIRE
|
1
|
-0.051***
|
-0.026***
|
-0.002
|
-0.025***
|
0.072***
|
0.036***
|
-0.132***
|
0.002
|
-0.036***
|
0.359***
|
-0.080***
|
0.092***
|
0.242***
|
(B)POLICY
|
-0.034***
|
1
|
0.163***
|
-0.002
|
0.190***
|
-0.041***
|
-0.147***
|
-0.120***
|
0.320***
|
-0.207***
|
0.01
|
-0.162***
|
-0.119***
|
-0.088***
|
(C)GCRES×POLICY
|
-0.039***
|
0.163***
|
1
|
0.796***
|
0.184***
|
-0.040***
|
0.109***
|
0.070***
|
0.093***
|
0.103***
|
-0.058***
|
-0.150***
|
-0.041***
|
-0.015**
|
(D)GCRES
|
-0.018**
|
-0.002
|
0.796***
|
1
|
0.192***
|
-0.030***
|
0.142***
|
0.135***
|
0.026***
|
0.158***
|
-0.064***
|
-0.135***
|
-0.034***
|
0.003
|
(E)SIZE
|
0.004
|
0.186***
|
0.210***
|
0.215***
|
1
|
0.054***
|
0.349***
|
-0.015**
|
0.142***
|
0.192***
|
-0.030***
|
-0.323***
|
-0.126***
|
-0.019***
|
(F)ROA
|
0.046***
|
-0.022***
|
-0.020***
|
-0.005
|
0.097***
|
1
|
-0.378***
|
-0.114***
|
-0.083***
|
-0.107***
|
0.041***
|
0.109***
|
-0.032***
|
-0.071***
|
(G)LEV
|
0.043***
|
-0.151***
|
0.100***
|
0.131***
|
0.301***
|
-0.364***
|
1
|
0.026***
|
0.103***
|
0.265***
|
0.006
|
-0.136***
|
0.120***
|
0.111***
|
(H)TANGIBILITY
|
-0.092***
|
-0.121***
|
0.102***
|
0.176***
|
0.045***
|
-0.121***
|
0.077***
|
1
|
-0.108***
|
0.146***
|
-0.166***
|
0.255***
|
-0.167***
|
-0.162***
|
(I)AGE
|
0.017**
|
0.291***
|
0.086***
|
0.025***
|
0.114***
|
-0.067***
|
0.112***
|
-0.074***
|
1
|
0.102***
|
-0.019***
|
-0.192***
|
0.015**
|
0.01
|
(J)SOE
|
-0.013*
|
-0.207***
|
0.103***
|
0.158***
|
0.203***
|
-0.079***
|
0.257***
|
0.175***
|
0.115***
|
1
|
-0.133***
|
-0.044***
|
-0.018**
|
-0.049***
|
(K)STD_NET_HIRE
|
0.508***
|
0.012*
|
0.001
|
0.007
|
0.057***
|
0.044***
|
0.040***
|
-0.089***
|
0.047***
|
-0.018**
|
1
|
-0.030***
|
0.113***
|
0.303***
|
(L)LABOR_INTENSITY
|
0.103***
|
-0.187***
|
-0.108***
|
-0.082***
|
-0.265***
|
0.067***
|
-0.058***
|
0.116***
|
-0.149***
|
-0.036***
|
0.084***
|
1
|
-0.057***
|
-0.172***
|
(M)STD_CFO
|
0.107***
|
-0.113***
|
-0.039***
|
-0.037***
|
-0.152***
|
-0.038***
|
0.131***
|
-0.186***
|
0.043***
|
-0.006
|
0.086***
|
-0.044***
|
1
|
0.249***
|
(N)STD_SALES
|
0.319***
|
-0.038***
|
0.001
|
0.008
|
-0.015**
|
-0.001
|
0.098***
|
-0.142***
|
0.083***
|
-0.027***
|
0.409***
|
-0.018**
|
0.257***
|
1
|
Notes: This table presents the correlation coefficients of main variables used in this study. ***, **, * indicates significance levels of 0.01, 0.05 and 0.10 respectively.
Table 3 Green credit policy and firms’ labor investment efficiency
Panel A The effect of green credit policy on abnormal net hiring
Variable
|
AB_NET_HIRE
|
AB_NET_HIRE
|
POLICY
|
-0.046***
|
0.024
|
|
(-3.48)
|
(0.72)
|
GCRES×POLICY
|
-0.120***
|
-0.077***
|
|
(-4.65)
|
(-3.34)
|
GCRES
|
0.037
|
-0.022
|
|
(0.82)
|
(-0.56)
|
SIZE
|
|
0.010
|
|
|
(1.44)
|
ROA
|
|
0.261***
|
|
|
(4.38)
|
LEV
|
|
0.086***
|
|
|
(3.24)
|
TANGIBILITY
|
|
-0.135***
|
|
|
(-4.03)
|
AGE
|
|
-0.022
|
|
|
(-0.46)
|
SOE
|
|
-0.019
|
|
|
(-0.49)
|
STD_NET_HIRE
|
|
0.307***
|
|
|
(25.93)
|
LABOR_INTENSITY
|
|
11.291***
|
|
|
(12.25)
|
STD_CFO
|
|
0.271***
|
|
|
(3.18)
|
STD_SALES
|
|
0.076***
|
|
|
(6.42)
|
Constant
|
0.247***
|
-0.186
|
|
(22.00)
|
(-0.99)
|
Firm FE
|
Yes
|
Yes
|
Year FE
|
Yes
|
Yes
|
Observations
|
19,513
|
19,513
|
Adjusted R2
|
0.053
|
0.271
|
Notes: This table reports the baseline results of this study, with the first column without firm-level controls and the second column with all the controls. The dependent variable is AB_NET_HIRE. The independent variable is GCRES×POLICY. Firm fixed effects and year fixed effects are also included. The t values reported in parentheses are clustered by firm, where *, **, and *** denote significance levels of 0.01, 0.05 and 0.10 respectively. All variables are defined in Appendix.
Panel B The effect of green credit policy on over- and underhiring (and firing)
Variable
|
Overinvestment
|
Underinvestment
|
|
Total
|
Over-hiring
|
Under-firing
|
Total
|
Under-hiring
|
Over-firing
|
Policy
|
0.072
|
0.049
|
0.027
|
-0.031
|
-0.023
|
-0.020
|
|
(0.79)
|
(0.44)
|
(0.36)
|
(-1.21)
|
(-0.58)
|
(-0.50)
|
GCRES×POLICY
|
-0.184**
|
-0.247***
|
0.017
|
-0.040***
|
-0.025
|
-0.052*
|
|
(-2.46)
|
(-2.62)
|
(0.56)
|
(-2.77)
|
(-1.58)
|
(-1.94)
|
GCRES
|
-0.024
|
-0.076
|
0.023
|
0.011
|
-0.000
|
0.013
|
|
(-0.22)
|
(-0.61)
|
(0.39)
|
(0.36)
|
(-0.01)
|
(0.26)
|
SIZE
|
0.038**
|
0.048**
|
-0.023*
|
-0.023***
|
0.022*
|
-0.013
|
|
(2.13)
|
(2.04)
|
(-1.74)
|
(-3.73)
|
(1.75)
|
(-1.33)
|
ROA
|
-0.195
|
-0.273
|
-0.250***
|
0.530***
|
0.681***
|
0.676***
|
|
(-1.29)
|
(-1.12)
|
(-3.59)
|
(9.53)
|
(6.08)
|
(8.75)
|
LEV
|
-0.081
|
-0.099
|
0.048
|
0.125***
|
0.092*
|
0.129***
|
|
(-1.19)
|
(-1.10)
|
(1.15)
|
(5.02)
|
(1.81)
|
(3.61)
|
TANGIBILITY
|
-0.041
|
-0.045
|
-0.014
|
-0.105***
|
-0.082*
|
-0.168***
|
|
(-0.46)
|
(-0.39)
|
(-0.22)
|
(-3.77)
|
(-1.79)
|
(-4.20)
|
AGE
|
-0.193
|
-0.200
|
-0.024
|
-0.026
|
-0.048
|
-0.113*
|
|
(-1.44)
|
(-1.24)
|
(-0.21)
|
(-0.68)
|
(-0.89)
|
(-1.76)
|
SOE
|
-0.021
|
0.063
|
0.037
|
0.038
|
0.096
|
0.018
|
|
(-0.18)
|
(0.40)
|
(0.70)
|
(1.07)
|
(1.03)
|
(0.37)
|
STD_NET_HIRE
|
0.705***
|
0.724***
|
-0.004
|
0.002
|
-0.034***
|
0.019
|
|
(20.01)
|
(17.74)
|
(-0.25)
|
(0.22)
|
(-2.98)
|
(1.55)
|
LABOR_INTENSITY
|
16.008***
|
17.451***
|
-0.836
|
-4.507***
|
1.010
|
-5.396***
|
|
(9.08)
|
(7.83)
|
(-1.00)
|
(-7.46)
|
(1.05)
|
(-5.47)
|
STD_CFO
|
0.293
|
0.237
|
0.101
|
0.112
|
0.084
|
0.171
|
|
(1.25)
|
(0.82)
|
(1.09)
|
(1.56)
|
(0.63)
|
(1.54)
|
STD_SALES
|
-0.089***
|
-0.102***
|
0.012
|
0.145***
|
0.130***
|
0.169***
|
|
(-2.92)
|
(-2.71)
|
(0.89)
|
(13.61)
|
(7.90)
|
(9.13)
|
Constant
|
-0.397
|
-0.619
|
0.545
|
0.695***
|
-0.385
|
0.767***
|
|
(-0.85)
|
(-1.04)
|
(1.27)
|
(4.36)
|
(-1.30)
|
(2.91)
|
Firm FE
|
YES
|
YES
|
YES
|
YES
|
YES
|
YES
|
Year FE
|
YES
|
YES
|
YES
|
YES
|
YES
|
YES
|
Observations
|
6,841
|
5,704
|
1,137
|
12,672
|
5,243
|
7,429
|
Adjusted R2
|
0.496
|
0.507
|
0.309
|
0.269
|
0.414
|
0.294
|
Notes: This table reports the results based on decomposing labor investment efficiency. The first three columns present the impact of green credit policy on overinvestment in labor, in which we further decompose overinvestment into over-hiring and under-firing. The last three columns present the impact of green credit policy on underinvestment in labor, in which we further decompose underinvestment into over-hiring and under-firing. Firm fixed effects and year fixed effects are also included. The t values reported in parentheses are clustered by firm, where *, **, and *** denote significance levels of 0.01, 0.05 and 0.10 respectively. All variables are defined in Appendix.
Table 4 Robustness checks
Panel A Parallel trends analysis
Variable
|
AB_NET_HIRE
|
GCRES×Pre5
|
-0.023
|
|
(-0.50)
|
GCRES×Pre4
|
-0.016
|
|
(-0.32)
|
GCRES×Pre3
|
-0.004
|
|
(-0.08)
|
GCRES×Pre2
|
-0.060
|
|
(-1.56)
|
GCRES×Current
|
-0.155***
|
|
(-4.02)
|
GCRES×Post1
|
-0.118***
|
|
(-3.21)
|
GCRES×Post2
|
-0.120***
|
|
(-3.80)
|
GCRES×Post3
|
-0.093***
|
|
(-2.91)
|
GCRES×Post4
|
-0.063**
|
|
(-2.11)
|
GCRES×Post5
|
-0.050*
|
|
(-1.71)
|
SIZE
|
0.010
|
|
(1.50)
|
ROA
|
0.263***
|
|
(4.42)
|
LEV
|
0.087***
|
|
(3.26)
|
TANGIBILITY
|
-0.137***
|
|
(-4.09)
|
AGE
|
-0.018
|
|
(-0.38)
|
SOE
|
-0.020
|
|
(-0.52)
|
STD_NET_HIRE
|
0.307***
|
|
(25.93)
|
LABOR_INTENSITY
|
11.279***
|
|
(12.23)
|
STD_CFO
|
0.273***
|
|
(3.20)
|
STD_SALES
|
0.076***
|
|
(6.44)
|
Constant
|
-0.203
|
|
(-1.08)
|
Firm FE
|
YES
|
Year FE
|
YES
|
Observations
|
19,513
|
Adjusted R2
|
0.271
|
Notes: This table presents the regression results of parallel trends analysis based on Eq. (3). The dependent variable is AB_NET_HIRE. The independent variable include interactions between green credit restricted industries (GCRES) and a series of time dummy variables that relative to the year of the implementation of the Guidelines. Firm fixed effects and year fixed effects are also included. The t values reported in parentheses are clustered by firm, where *, **, and *** denote significance levels of 0.01, 0.05 and 0.10 respectively. All variables are defined in Appendix.
Panel B Alternative model specifications
Variable
|
AB_NET_HIRE
|
POLICY
|
0.025
|
0.040
|
0.039
|
.
|
|
(0.77)
|
(1.19)
|
(1.15)
|
.
|
GCRES×POLICY
|
-0.071***
|
-0.075***
|
-0.070***
|
-0.076***
|
|
(-3.08)
|
(-3.26)
|
(-3.04)
|
(-2.74)
|
GCRES
|
-0.003
|
0.074
|
0.065
|
-0.006
|
|
(-0.09)
|
(1.47)
|
(1.23)
|
(-0.15)
|
SIZE
|
0.014*
|
0.015**
|
0.017**
|
0.012
|
|
(1.96)
|
(2.18)
|
(2.53)
|
(1.51)
|
ROA
|
0.273***
|
0.261***
|
0.272***
|
0.279***
|
|
(4.62)
|
(4.34)
|
(4.56)
|
(4.02)
|
LEV
|
0.086***
|
0.082***
|
0.081***
|
0.075***
|
|
(3.37)
|
(3.12)
|
(3.19)
|
(2.62)
|
TANGIBILITY
|
-0.133***
|
-0.139***
|
-0.136***
|
-0.161***
|
|
(-3.96)
|
(-4.12)
|
(-4.02)
|
(-4.01)
|
AGE
|
-0.023
|
-0.048
|
-0.045
|
-0.042
|
|
(-0.48)
|
(-0.97)
|
(-0.91)
|
(-0.73)
|
SOE
|
-0.022
|
-0.030
|
-0.029
|
-0.014
|
|
(-0.55)
|
(-0.77)
|
(-0.77)
|
(-0.33)
|
STD_NET_HIRE
|
0.306***
|
0.309***
|
0.309***
|
0.312***
|
|
(25.30)
|
(26.15)
|
(25.51)
|
(25.16)
|
LABOR_INTENSITY
|
11.533***
|
11.316***
|
11.585***
|
11.754***
|
|
(12.40)
|
(12.22)
|
(12.40)
|
(11.79)
|
STD_CFO
|
0.258***
|
0.279***
|
0.273***
|
0.337***
|
|
(2.91)
|
(3.28)
|
(3.11)
|
(3.46)
|
STD_SALES
|
0.078***
|
0.079***
|
0.080***
|
0.072***
|
|
(6.55)
|
(6.61)
|
(6.67)
|
(5.73)
|
Constant
|
-0.274
|
-0.228
|
-0.300
|
-0.170
|
|
(-1.45)
|
(-1.22)
|
(-1.60)
|
(-0.73)
|
Firm FE
|
YES
|
YES
|
YES
|
YES
|
Year FE
|
YES
|
YES
|
YES
|
NO
|
Industry FE
|
NO
|
YES
|
YES
|
NO
|
City FE
|
YES
|
NO
|
YES
|
NO
|
City × Year FE
|
NO
|
NO
|
NO
|
YES
|
Observations
|
19,504
|
19,513
|
19,504
|
18,160
|
Adjusted R2
|
0.266
|
0.274
|
0.268
|
0.255
|
Notes: This table reports the results of robustness checks for alternative model specifications. The t values reported in parentheses are clustered by firm, where *, **, and *** denote significance levels of 0.01, 0.05 and 0.10 respectively. All variables are defined in Appendix.
Panel C Other robustness checks
Variable
|
AB_NET_HIRE
|
|
(1) PSM-DID
|
(2) Alternative classification of treat group
|
(3) Controlling for time trend effects
|
POLICY
|
0.046
|
0.022
|
0.017
|
|
(0.33)
|
(0.65)
|
(0.52)
|
GCRES×POLICY
|
-0.071*
|
-0.023**
|
-0.155***
|
|
(-1.85)
|
(-2.11)
|
(-3.87)
|
GCRES
|
-0.159
|
-0.033*
|
-29.601***
|
|
(-1.32)
|
(-1.82)
|
(-2.62)
|
POLICY×Trend
|
|
|
0.015***
|
|
|
|
(2.62)
|
SIZE
|
-0.013
|
0.008
|
0.010
|
|
(-0.44)
|
(1.11)
|
(1.46)
|
ROA
|
0.293
|
0.260***
|
0.262***
|
|
(1.40)
|
(4.38)
|
(4.41)
|
LEV
|
0.137
|
0.088***
|
0.086***
|
|
(1.34)
|
(3.28)
|
(3.24)
|
TANGIBILITY
|
0.032
|
-0.134***
|
-0.136***
|
|
(0.30)
|
(-4.03)
|
(-4.07)
|
AGE
|
-0.063
|
-0.012
|
-0.020
|
|
(-0.32)
|
(-0.24)
|
(-0.42)
|
SOE
|
0.073
|
-0.025
|
-0.020
|
|
(0.88)
|
(-0.68)
|
(-0.52)
|
STD_NET_HIRE
|
0.218***
|
0.308***
|
0.307***
|
|
(5.65)
|
(25.94)
|
(25.93)
|
LABOR_INTENSITY
|
7.481*
|
11.383***
|
11.296***
|
|
(1.86)
|
(12.33)
|
(12.26)
|
STD_CFO
|
-0.112
|
0.273***
|
0.273***
|
|
(-0.34)
|
(3.20)
|
(3.20)
|
STD_SALES
|
0.050
|
0.075***
|
0.076***
|
|
(1.39)
|
(6.40)
|
(6.45)
|
Constant
|
0.508
|
-0.153
|
-0.189
|
|
(0.57)
|
(-0.81)
|
(-1.01)
|
Firm FE
|
YES
|
YES
|
YES
|
Year FE
|
YES
|
YES
|
YES
|
Observations
|
2,876
|
19,513
|
19,513
|
Adjusted R2
|
0.249
|
0.271
|
0.271
|
Notes: This table reports the results of several robustness checks. Column (1) shows the results of PSM-DID, column (2) reports the results of alternative classification of green credit-restricted industries, while column (3) presents the results of controlling for time trend effects of treatment group. The t values reported in parentheses are clustered by firm, where *, **, and *** denote significance levels of 0.01, 0.05 and 0.10 respectively. All variables are defined in Appendix.
Table 5 Mechanism analyses
Variable
|
SKILLED_LABOR
|
AB_NET_HIRE
|
AC
|
AB_NET_HIRE
|
SKILLED_LABOR
|
|
-0.088***
|
|
|
|
|
(-2.90)
|
|
|
AC
|
|
|
|
0.118**
|
|
|
|
|
(1.97)
|
POLICY
|
0.044**
|
0.025
|
0.014
|
-0.001
|
|
(2.36)
|
(0.75)
|
(0.97)
|
(-0.02)
|
GCRES×POLICY
|
0.042**
|
-0.074***
|
-0.012***
|
-0.073***
|
|
(2.17)
|
(-3.16)
|
(-2.62)
|
(-2.61)
|
GCRES
|
0.047*
|
-0.020
|
0.004
|
-0.044
|
|
(1.79)
|
(-0.50)
|
(0.43)
|
(-0.95)
|
SIZE
|
0.010***
|
0.011
|
-0.029***
|
0.030***
|
|
(2.67)
|
(1.57)
|
(-7.10)
|
(3.31)
|
ROA
|
0.030
|
0.262***
|
-0.239***
|
0.256***
|
|
(1.32)
|
(4.37)
|
(-8.73)
|
(3.59)
|
LEV
|
-0.022
|
0.085***
|
0.033**
|
0.072**
|
|
(-1.59)
|
(3.20)
|
(2.37)
|
(2.31)
|
TANGIBILITY
|
-0.039**
|
-0.135***
|
-0.020
|
-0.154***
|
|
(-2.43)
|
(-4.00)
|
(-1.21)
|
(-3.54)
|
AGE
|
-0.039
|
-0.020
|
0.021
|
0.001
|
|
(-1.41)
|
(-0.42)
|
(1.13)
|
(0.02)
|
SOE
|
-0.001
|
-0.023
|
-0.046**
|
0.008
|
|
(-0.04)
|
(-0.58)
|
(-2.30)
|
(0.18)
|
STD_NET_HIRE
|
-0.005
|
0.307***
|
0.009***
|
0.273***
|
|
(-1.18)
|
(26.02)
|
(3.91)
|
(18.64)
|
LABOR_INTENSITY
|
-0.594**
|
11.234***
|
-0.333
|
14.736***
|
|
(-2.10)
|
(12.12)
|
(-1.51)
|
(12.63)
|
STD_CFO
|
-0.022
|
0.277***
|
0.022
|
0.299***
|
|
(-0.65)
|
(3.24)
|
(0.63)
|
(2.97)
|
STD_SALES
|
-0.001
|
0.075***
|
-0.021***
|
0.078***
|
|
(-0.17)
|
(6.41)
|
(-5.84)
|
(5.44)
|
Constant
|
0.058
|
-0.195
|
0.699***
|
-0.714***
|
|
(0.56)
|
(-1.03)
|
(7.92)
|
(-2.90)
|
Firm FE
|
YES
|
YES
|
YES
|
YES
|
Year FE
|
YES
|
YES
|
YES
|
YES
|
Observations
|
19,338
|
19,338
|
15,924
|
15,924
|
Adjusted R2
|
0.653
|
0.272
|
0.661
|
0.272
|
Notes: This table reports the mediating effect of human capital structure and agency cost. We use number of technical employees divided by total number of employees (SKILLED_LABOR) to proxy human capital structure, and use administrative expenses divided by total operating income to proxy agency cost. Firm fixed effects and year fixed effects are also included. The t values reported in parentheses are clustered by firm, where *, **, and *** denote significance levels of 0.01, 0.05 and 0.10 respectively. All variables are defined in Appendix.
Table 6 Cross-sectional analysis
Variable
|
AB_NET_HIRE
|
|
ELP1
|
ELP2
|
LI1
|
LI2
|
Moderator×GCRES×POLICY
|
-0.091**
|
-0.091**
|
0.087*
|
0.115**
|
|
(-2.01)
|
(-2.04)
|
(1.90)
|
(2.43)
|
Moderator×POLICY
|
0.021*
|
0.006
|
0.030***
|
0.018
|
|
(1.87)
|
(0.51)
|
(2.63)
|
(1.62)
|
Moderator×GCRES
|
0.036
|
0.036
|
-0.077*
|
-0.069
|
|
(0.70)
|
(0.91)
|
(-1.81)
|
(-1.61)
|
GCRES×POLICY
|
-0.022
|
-0.019
|
-0.121***
|
-0.135***
|
|
(-0.64)
|
(-0.52)
|
(-3.56)
|
(-3.68)
|
Moderator
|
-0.036***
|
-0.019*
|
-0.053***
|
-0.041***
|
|
(-2.69)
|
(-1.67)
|
(-4.81)
|
(-3.80)
|
POLICY
|
0.020
|
0.028
|
0.012
|
0.018
|
|
(0.58)
|
(0.78)
|
(0.37)
|
(0.55)
|
GCRES
|
-0.042
|
-0.045
|
0.018
|
0.012
|
|
(-0.80)
|
(-0.85)
|
(0.40)
|
(0.25)
|
SIZE
|
0.011
|
0.011
|
0.008
|
0.009
|
|
(1.53)
|
(1.54)
|
(1.16)
|
(1.32)
|
ROA
|
0.244***
|
0.248***
|
0.228***
|
0.241***
|
|
(3.92)
|
(4.01)
|
(3.79)
|
(4.02)
|
LEV
|
0.086***
|
0.086***
|
0.085***
|
0.083***
|
|
(3.08)
|
(3.07)
|
(3.20)
|
(3.12)
|
TANGIBILITY
|
-0.137***
|
-0.135***
|
-0.131***
|
-0.133***
|
|
(-3.89)
|
(-3.80)
|
(-3.93)
|
(-3.99)
|
AGE
|
-0.038
|
-0.036
|
-0.015
|
-0.023
|
|
(-0.77)
|
(-0.72)
|
(-0.31)
|
(-0.48)
|
SOE
|
-0.020
|
-0.019
|
-0.020
|
-0.019
|
|
(-0.51)
|
(-0.48)
|
(-0.52)
|
(-0.52)
|
STD_NET_HIRE
|
0.309***
|
0.309***
|
0.310***
|
0.307***
|
|
(25.63)
|
(25.56)
|
(26.34)
|
(25.90)
|
LABOR_INTENSITY
|
11.342***
|
11.303***
|
12.028***
|
11.561***
|
|
(11.93)
|
(11.89)
|
(12.50)
|
(12.42)
|
STD_CFO
|
0.297***
|
0.295***
|
0.257***
|
0.272***
|
|
(3.37)
|
(3.34)
|
(3.01)
|
(3.19)
|
STD_SALES
|
0.073***
|
0.073***
|
0.070***
|
0.073***
|
|
(6.01)
|
(6.01)
|
(5.93)
|
(6.18)
|
Constant
|
-0.145
|
-0.164
|
-0.146
|
-0.148
|
|
(-0.74)
|
(-0.84)
|
(-0.77)
|
(-0.78)
|
Firm FE
|
YES
|
YES
|
YES
|
YES
|
Year FE
|
YES
|
YES
|
YES
|
YES
|
Observations
|
18,560
|
18,560
|
19,513
|
19,513
|
Adjusted R2
|
0.270
|
0.270
|
0.273
|
0.272
|
Notes: This table presents the results of whether the environmental law enforcement and labor intensity affects the association between green credit policy and labor investment efficiency. The first two columns report the results of environmental law enforcement, in which the moderators are ELP1(A dummy variable equals to one if the sewage charge of the province is greater than the annual median, and zero otherwise) and ELP2(A dummy variable equals to one if the number of administrative penalty cases of the province is greater than the annual median, and zero otherwise). The last two columns report the results of labor intensity, in which the moderators are LI1 (A dummy variable, based on the number of employees at the end of the year divided by the operating income of the year for the firm) and LI2(A dummy variable, based on the natural logarithm of "cash paid to employees and paid for employees" divided by the natural logarithm of sales revenue). Firm fixed effects and year fixed effects are also included. The t values reported in parentheses are clustered by firm, where *, **, and *** denote significance levels of 0.01, 0.05 and 0.10 respectively. All variables are defined in Appendix.
Table 7 Additional analysis
Variable
|
AVEROA
|
AVETOBINQ
|
AB_NET_HIRE
|
-0.004**
|
-0.065**
|
|
(-2.12)
|
(-2.37)
|
SIZE
|
-0.018***
|
-0.614***
|
|
(-8.36)
|
(-14.15)
|
ROA
|
0.059***
|
0.405
|
|
(4.41)
|
(1.42)
|
LEV
|
0.020**
|
0.591***
|
|
(2.42)
|
(4.13)
|
TANGIBILITY
|
0.040***
|
-0.250*
|
|
(4.13)
|
(-1.73)
|
AGE
|
-0.026*
|
0.083
|
|
(-1.69)
|
(0.36)
|
SOE
|
0.002
|
0.186
|
|
(0.16)
|
(0.78)
|
STD_NET_HIRE
|
-0.000
|
0.024
|
|
(-0.18)
|
(0.90)
|
LABOR_INTENSITY
|
0.383**
|
-3.127
|
|
(2.54)
|
(-1.23)
|
STD_CFO
|
0.007
|
0.042
|
|
(0.40)
|
(0.13)
|
STD_SALES
|
0.001
|
-0.021
|
|
(0.63)
|
(-0.63)
|
Constant
|
0.436***
|
14.886***
|
|
(7.91)
|
(14.67)
|
Firm FE
|
YES
|
YES
|
Year FE
|
YES
|
YES
|
Observations
|
19,361
|
17,767
|
Adjusted R2
|
0.485
|
0.675
|
Notes: This table presents the impact of labor investment efficiency on the firm's financial performance. The dependent variable is AB_NET_HIRE. The independent variable is AVEROA (the average value of ROA over the next three years) and AVETOBINQ (the average value of TOBINQ over the next three years). Firm fixed effects and year fixed effects are also included. The t values reported in parentheses are clustered by firm, where *, **, and *** denote significance levels of 0.01, 0.05 and 0.10 respectively. All variables are defined in Appendix.