X. Li and Y. Li Finance Research Letters 32 (2020) 101320 Table 3 Results of the effect of female chairpersons on financial irregularities. (1) (2) VIO DEGREE GENDER -0.317-* -0.373.* (-1.981) (-2.253) SIZE -0.246-* -0.299- (-5.385) (-4.138) GROWTH 0.246+* 0.266-* (4.711) (5.139) ROA -2.271-* -2.193- (-2.498) (-2.358) TOP1 0.004 0.004 (0.749) (0.777) BOARD 1.737. 1.219 (2.104) (1.311) IDSIZE -1.067 -1.300 (-0.806) (-0.856) STATE -0.096 -0.055 (-0.577) (-0.313) VOL -12.623- -12.895- (-2.089) (-2.070) EXCH LIQ 0.000 0.000 (1.141) (1.075) ANALYST -0.044- -0.039- (-4.239) (-3.665) Year-fixed Control Control Firm-fixed Control Control Log likelihood -2031.865 -2187.328 Wald Chi 765.092 83.627 N 12,559 12,515 Table 3 shows results of measures of VIO (DEGREE) in the subsequent year t + 1, on GENDER and control variables in the current year t, regressing by panel logit model (panel ordered logit model). The number of samples used in Column (2) is less than that in Column (1) because the information about the penalty was missing. The sample period is 2007 to 2016. All continuous variables are winsorized at the 1% and 99% level. Z-values are reported in parentheses. *, ** and *** denote significance levels at 10%, 5%, and 1%, respectively