Table 5

Multinomial logit regression results for high-level SDG disclosure

ModelDivMethodDiv0Div50DivYear
VariableCashStockCash–stock
SDG7.471**10.400***(3.040)(6.752)**0.966(22.418)*
4.0636.8850.2814.2500.0843.481
SIZE(0.618)**0.164(0.115)0.2610.223(0.636)
4.1060.2160.0761.0080.3521.437
LEV(0.105)(4.250)9.518*1.854(0.849)5.961
0.0021.7002.9130.6170.0571.046
TobinQ(0.051)0.7230.836(0.360)0.891*1.627**
0.0081.4301.0260.5243.0684.638
ROA24.972*(27.977)*36.281*(2.578)3.2222.620
2.9083.2163.3370.0480.0520.021
ROE0.44217.337**6.405(11.006)*3.8987.403
0.0046.2370.3833.7220.1250.366
AGE0.072***0.0510.064**(0.068)**0.003(0.054)
6.7962.6754.0376.5290.0301.357
BGD(0.010)0.045**(0.026)(0.003)(0.070)**0.010
0.4255.3401.2290.0655.1110.136
−2Log-likelihood (Intercept)396.348  174.61285.70657.765
−2Log-likelihood (Final)245.046***  121.858***66.923**40.266**
Pseudo R20.382  0.3020.2190.303
Observations163  163163163

Note(s): Significant at *p < 0.10; **p < 0.05; ***p < 0.01; Negative numbers are presented in parentheses; the italicised value below is the Wald value

Source(s): Authors' own work

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