Table 4 Regression results Variables FD...

Table 4

Regression results

Variables	FD (REM)	CSR_ratio(REM)	FD(REM)	FD(REM)
Variables	Model 1	Model 2	Model 3	Model 4
CSR_ratio	0.022**			0.032*
CSR_ratio	(0.093)			(0.092)
CEO_comp		0.061***	0.051**	0.057*
CEO_comp		(0.000)	(0.000)	(0.000)
Fsize	0.056**	0.133**	0.294**	0.272*
Fsize	(0.133)	(0.031)	(0.144)	(0.141)
Lev	−1.901***	−0.0579	−1.891***	−1.917***
Lev	(0.160)	(0.042)	(0.159)	(0.159)
Tang	1.098	−0.094*	−1.021*	−1.064
Tang	(0.248)	(0.063)	(0.247)	(0.247)
Slack	3.722***	0.151	3.727***	3.735***
Slack	(0.388)	(0.101)	(0.384)	(0.385)
Sgth	0.0125*	0.018	0.012**	0.012*
Sgth	(0.005)	(0.001)	(0.005)	(0.005)
Constant	4.767***	1.243***	6.180***	6.071***
Constant	(0.934)	(0.212)	(0.994)	(0.978)
Industry effect	Yes	Yes	Yes	Yes
Years effect	Yes	Yes	Yes	Yes
Observations	1,680	1,680	1,680	1,680
Wald stat	314.53***	27.98***	328.70***	335.97***
R-square	0.337	0.103	0.332	0.331
Number of coid	140	140	140	140

Variables	FD (REM)	CSR_ratio(REM)	FD(REM)	FD(REM)
Variables	Model 1	Model 2	Model 3	Model 4
CSR_ratio	0.022**			0.032*
CSR_ratio	(0.093)			(0.092)
CEO_comp		0.061***	0.051**	0.057*
CEO_comp		(0.000)	(0.000)	(0.000)
Fsize	0.056**	0.133**	0.294**	0.272*
Fsize	(0.133)	(0.031)	(0.144)	(0.141)
Lev	−1.901***	−0.0579	−1.891***	−1.917***
Lev	(0.160)	(0.042)	(0.159)	(0.159)
Tang	1.098	−0.094*	−1.021*	−1.064
Tang	(0.248)	(0.063)	(0.247)	(0.247)
Slack	3.722***	0.151	3.727***	3.735***
Slack	(0.388)	(0.101)	(0.384)	(0.385)
Sgth	0.0125*	0.018	0.012**	0.012*
Sgth	(0.005)	(0.001)	(0.005)	(0.005)
Constant	4.767***	1.243***	6.180***	6.071***
Constant	(0.934)	(0.212)	(0.994)	(0.978)
Industry effect	Yes	Yes	Yes	Yes
Years effect	Yes	Yes	Yes	Yes
Observations	1,680	1,680	1,680	1,680
Wald stat	314.53***	27.98***	328.70***	335.97***
R-square	0.337	0.103	0.332	0.331
Number of coid	140	140	140	140

Note(s): Standard errors in parentheses. ***p < 0.01, **p < 0.05, *p < 0.1

Source(s): Author’s own work

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