Table 5 Baseline regression results.

	Model 1	Model 2
Main variable
GRI	−0.65***	−0.40***
	[−6.39]	[−2.65]
Company-specific characteristics
FL		0.000055
		[1.43]
ROE		0.00191
		[0.13]
CR		0.000071**
		[2.29]
DPS		−0.0017**
		[−2.06]
ID		−0.0075***
		[−8.01]
ACM		−0.0068
		[−0.93]
CEO		−0.52***
		[−6.69]
WOB		−0.0042
		[−1.49]
CS		−0.011***
		[−15.8]
T		−0.33***
		[−5.17]
IOP		1.31***
		[40.6]
P		0.000014
		[0.53]
OP		−0.000012***
		[−2.82]
D		0.0021***
		[14.1]
F		0.013**
		[2.26]
B		−0.36***
		[−12.8]
VC		0.27***
		[8.17]
R		0.0063
		[0.29]
Market-specific characteristics
V		10.0***
		[5.84]
PAR		−1.61***
		[−10.9]
H		0.19***
		[8.51]
VOL		−0.0016***
		[−23.6]
Country-specific characteristics
EL		0.35***
		[11.6]
CL		0.38***
		[7.96]
FDI		0.045***
		[6.55]
GDP		−0.030***
		[−5.93]
I		−0.013***
		[−6.11]
Dummy Effect	YE & IR & CE	YE & IR & CE
Constant	−2.08***	−3.34***
	[−69.8]	[−46.8]
Observations	33,536	33,536
Adjusted R-squared	0.059	0.27
VIF check^a	1.85	1.91

All variables are defined in Table 2. Every model uses robust Z-statistics adjusted for heteroscedasticity, indicating ***P < 0.01, **P < 0.05, and *P < 0.1 for two-tailed testing.
^aThe variance inflation factor (VIF) check is applied to confirm the lack of multicollinearity in the regression models utilised in the models. Alidarous (2024a) indicates that a mean VIF value below 5 in a regression model signifies the absence of multicollinearity among the independent variables.

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