Table 8

Robustness tests

Panel A: Alternative measure of CSD
Dep. Var. = DECILE_DISVOL
(1)(2)(3)(4)
GENDIV−0.074   
(−0.237)   
1WOMAN −0.015  
 (−0.121)  
2WOMEN  −0.148** 
  (−2.118) 
≥3WOMEN   0.167**
   (2.084)
BDSIZE0.053***0.052***0.042***0.037**
(3.303)(3.218)(2.682)(2.232)
INDPDIR−0.336−0.350−0.400−0.436
(−0.993)(−1.057)(−1.206)(−1.306)
COMPRN0.295***0.295***0.293***0.291***
(2.743)(2.750)(2.802)(2.798)
AUDCOMIND0.2380.2350.2320.247
(0.502)(0.491)(0.494)(0.525)
CYBERPOLICY0.0420.0430.0280.031
(0.538)(0.545)(0.366)(0.394)
InterceptYesYesYesYes
Control variablesYesYesYesYes
Year FEYesYesYesYes
Industry FEYesYesYesYes
Cluster byFirmFirmFirmFirm
Observations630630630630
Pseudo R20.1260.1260.1280.129
ModelPoissonPoissonPoissonPoisson
Panel B: Alternative measures of board gender diversity
Dep. Var. = DISVOL
(1)(2)
BLAUIDX0.427 
(0.574) 
SHANIDX 0.165
 (0.257)
InterceptYesYes
Other variables and controlsYesYes
Year FEYesYes
Industry FEYesYes
Cluster byFirmFirm
Observations630627
Adjusted R20.3900.377

Note(s): The table presents the results of robustness tests. Panel A presents the results of Poisson regressions, where the dependent variable is categorized by deciles of DISVOL. Panel B shows the results of OLS regressions, where board gender diversity (GENDIV) is alternatively measured using the Blau Index (BLAUIDX) and Shannon Index (SHANIDX), respectively. The definitions of variables are given in  Appendix. Robust two-tailed t-statistics clustered by firm are presented in parentheses. Superscripts ***, **, and * denote significance at the 1%, 5%, and 10% levels, respectively

Source(s): Authors’ own work

or Create an Account

Close Modal
Close Modal