Does the personal characteristics of the public offering committee members affect the issuance quality? An empirical study based on gender characteristics

Figures & data

Table 1. Descriptive statistics of variables.

Var	Observation	Mean	Min	P25	Middle	P75	Max
dependent variable
pass	2235	0.85	0	1	1	1	1
BHAR12	1642	0.12	−1.72	−0.27	−0.06	0.30	3.28
BHAR24	1642	0.11	−0.94	−0.31	−0.07	0.31	3.21
change_rev1	1642	0.82	−0.29	0.33	0.63	1.05	3.83
change_income1	1642	0.37	−1.58	−0.07	0.30	0.68	3.36
change_rev2	1642	1.27	−0.36	0.37	0.73	1.33	5.76
change_income2	1642	0.35	−1.63	−0.12	0.28	0.68	3.36
investigated variables
female	2235	0.56	0	0	1	1	1
female_fulltime	2235	0.51	0	0	1	1	1
female_parttime	2235	0.56	0	0	0	0	1
female_senior	2235	0.33
female_junior	2235	0.24
female_ncrsc	2235	0.42	0	0	0	1	1
female_crsc	2235	0.14	0	0	0	0	1
female_nlaw	2235	0.34	0	0	0	1	1
female_law	2235	0.22	0	0	0	0	1
female_nacct	2235	0.13	0	0	0	0	1
female_acct	2235	0.43	0	0	0	1	1
other variables
m_exp	2235	3.89	0.69	3.37	4.03	4.52	5.41
education	2235	0.33	0.00	0.14	0.29	0.43	0.86
ab_size	2235	−1.66	−4.22	−2.37	−1.82	−1.16	3.31
ab_lev	2235	−0.03	−0.60	−0.14	−0.01	0.12	0.43
ab_roa	2235	0.07	−0.05	0.04	0.08	0.13	0.34
ab_growth	2235	0.07	−1.70	−0.03	0.12	0.27	1.22
ab_vol	2235	−0.02	−0.18	−0.07	−0.04	0.02	0.40
Soe	2235	0.13	0	0	0	0	1
Cyb	2235	0.35	0	0	0	1	1
female_ceo	2235	0.07	0	0	0	0	1
female_chair	2235	0.05	0	0	0	0	1
female_board	2235	0.14	0	0	0.11	0.22	0.50
h_lev	2235	0.60	0	0	1	1	1
h_vol	2235	0.32	0	0	0	1	1
strcit	2235	0.58	0	0	1	1	1
Size	1642	21.21	19.77	20.51	20.95	21.58	26.35
Lev	1642	0.30	0.03	0.15	0.27	0.43	0.81
wbigshare	1642	0.38	0.10	0.28	0.37	0.48	0.76
Mb	1642	4.06	0.46	2.18	3.39	5.04	14.22
Indep	1642	0.37	0.33	0.33	0.33	0.43	0.57
idnustry_change1	1642	0.03	−0.27	−0.05	0.04	0.13	0.25
industry_chang2	1642	0.01	−0.24	−0.05	0.03	0.09	0.16

Table 2. Grouped T-test table.

	Female = 0		Female = 1
	Obv	Mean	Obv	Mean	Dif	T value
Pass	983	0.89	1252	0.82	0.07***	4.72
ab_size	983	−1.55	1252	−1.71	0.15***	2.97
ab_lev	983	−0.04	1252	−0.02	−0.02	−1.06
ab_roa	983	0.05	1252	0.09	−0.04	−0.83
Soe	983	0.13	1252	0.14	−0.01	−0.46
Cyb	987	0.21	1252	0.44	−0.23***	−12.46

Table 3. Pass rate of the examination with the participation of female committee member.

Dependent var = pass
	1	2	3	4	5
	Full sample	h_vol = 1	h_vol = 0	h_lev = 1	h_lev = 0
Female	−0.3489**	−0.9362***	−0.1498	−0.5258**	−0.1217
	(−2.03)	(−2.62)	(−0.70)	(−2.19)	(−0.42)
m_education	−1.4128***	−2.8099***	−1.1614**	−1.8470***	−1.2257*
	(−3.79)	(−3.80)	(−2.48)	(−3.80)	(−1.88)
m_exp	0.2828***	0.3143**	0.2559**	0.1513	0.6242***
	(3.25)	(2.08)	(2.17)	(1.34)	(3.59)
ab_size	0.7478***	0.8996***	0.8000***	0.8119***	0.5553***
	(7.05)	(3.84)	(6.13)	(6.53)	(2.62)
ab_lev	−1.9248***	−2.2618**	−1.6054***	−4.4934***	−0.1783
	(−3.88)	(−2.15)	(−2.69)	(−5.21)	(−0.63)
ab_roa	0.3028*	2.3987	0.0584	−1.5415	0.0451
	(1.89)	(1.10)	(0.26)	(−0.85)	(0.52)
ab_growth	0.1772**	0.0460	0.2726***	0.1465	0.3650*
	(2.27)	(0.23)	(2.93)	(1.64)	(1.75)
ab_vol	−2.4849***	−4.6505***	1.9730	−2.7037***	−1.7266
	(−3.69)	(−3.32)	(0.71)	(−3.01)	(−1.33)
Soe	−0.1430	−0.3264	−0.1567	−0.1869	−0.0823
	(−0.57)	(−0.64)	(−0.52)	(−0.58)	(−0.17)
Cyb	0.1934	0.1157	0.2638	−0.0366	0.3810
	(1.05)	(0.33)	(1.15)	(−0.15)	(1.22)
female_ceo	−0.3237	−0.6187	−0.1690	−0.7049*	0.4419
	(−1.09)	(−1.00)	(−0.45)	(−1.65)	(0.93)
female_chair	−0.8711**	−1.8844***	−0.6874	−1.0189**	−1.1985**
	(−2.54)	(−3.43)	(−1.56)	(−2.04)	(−2.50)
female board	4.6024***	3.9534***	5.4136***	6.8697***	2.3967**
	(6.70)	(3.39)	(5.56)	(6.69)	(2.30)
Year, Industry, Region	Control	Control	Control	Control	Control
Intercept	0.8861	1.5643	1.2943	2.1956*	−0.5920
	(0.93)	(0.64)	(1.12)	(1.84)	(−0.35)
N	2235	674	1519	1026	1124
Pseudo R2	0.1807	0.3131	0.1773	0.2367	0.2033

T values are in the brackets; *, **, and *** means being significant at the level of 10%, 5%m and 1% respectively; standard error of firm clustering.

Table 4. Influence of female committee members’ participation on the quality of listed companies.

	1	2	3	4
	change_rev1	change_income1	change_rev2	change_income2
Female	0.1397***	0.0952**	0.2157***	0.1188**
	(3.44)	(2.28)	(3.66)	(2.16)
Industry_change	0.3737**	0.7665***	0.1530	0.3047
	(2.26)	(4.51)	(0.69)	(1.47)
size	0.0798***	0.1785***	0.0929***	0.1546***
	(3.31)	(7.21)	(2.82)	(5.03)
lev	0.0218	−0.0618	0.1033	−0.0068
	(0.16)	(−0.44)	(0.53)	(−0.04)
mb	0.0416***	0.0902***	0.0692***	0.0929***
	(4.16)	(8.78)	(5.10)	(7.34)
indep	0.0149	−0.4712	0.1610	−0.1074
	(0.04)	(−1.17)	(0.29)	(−0.21)
bigshare	−0.2144	−0.1091	−0.3853*	−0.2124
	(−1.49)	(−0.74)	(−1.89)	(−1.12)
female_ceo	0.1766**	0.1576*	0.2245*	0.1656
	(2.04)	(1.77)	(1.85)	(1.46)
female_chair	0.0029	0.0229	0.0110	−0.0065
	(0.03)	(0.23)	(0.08)	(−0.05)
female_board	−0.4047**	−0.5054***	−0.5529**	−0.5317**
	(−2.38)	(−2.90)	(−2.20)	(−2.27)
Year	control	control	control	control
Intercept	−0.9613*	−3.5023***	−0.9556	−2.8937***
	(−1.87)	(−6.65)	(−1.36)	(−4.43)
N	1642	1642	1642	1642
adj. R-sq	0.023	0.073	0.026	0.045

T values are in the brackets; *, **, and *** means being significant at the level of 10%, 5%m and 1% respectively; standard error of firm clustering.

Table 5. Influence of female committee member’s participation in the examination on companies’ post-listing performance.

	1	2
	BHAR12	BHAR24
female	0.0675*	0.0797**
	(1.87)	(2.14)
size	−0.1072***	−0.1191***
	(−5.27)	(−5.67)
lev	1.1570***	1.0681***
	(8.20)	(7.34)
roa	1.6380**	2.2538***
	(2.51)	(3.34)
bigshare	−0.0002	−0.0171
	(−0.00)	(−0.15)
mb	0.0715***	0.0648***
	(8.02)	(7.04)
indep	−0.1833	0.0236
	(−0.61)	(0.08)
female_ceo	0.0436	0.0530
	(0.70)	(0.83)
female_chair	0.0143	0.0931
	(0.20)	(1.26)
female_board	0.1153	0.0942
	(0.90)	(0.71)
Industry, Year	control	control
Intercept	1.6694***	2.2015***
	(3.65)	(4.67)
N	1642	1642
adj. R-sq	0.336	0.246

T values are in the brackets; *, **, and *** means being significant at the level of 10%, 5%m and 1% respectively; standard error of firm clustering.

Table 6. Influence of female committee member’s status on the issuance examination.

dependent var = pass
	1	2	3
Female_parttime	0.4317
	(1.17)
Female_fulltime	−0.4052**
	(−2.35)
Female_ncrsc		−0.2760
		(−1.53)
Female_crsc		−0.5248**
		(−2.24)
Female_junior			−0.2249
			(−1.14)
Female_senior			−0.4797**
			(−2.45)
m_education	−1.2997***	−1.4091***	−1.4527***
	(−3.43)	(−3.69)	(−3.86)
m_exp	0.2794***	0.2504***	0.2891***
	(3.18)	(2.78)	(3.31)
ab_size	0.7564***	0.7504***	0.7434***
	(7.09)	(7.50)	(7.00)
ab_lev	−1.9166***	−1.9178***	−1.8964***
	(−3.85)	(−4.34)	(−3.82)
ab_roa	0.3191**	0.3016	0.2978*
	(2.02)	(0.99)	(1.86)
ab_growth	0.1694**	0.1755***	0.1744**
	(2.21)	(2.66)	(2.17)
ab_vol	−2.4613***	−2.4700***	−2.4902***
	(−3.65)	(−3.87)	(−3.68)
Soe	−0.1400	−0.1487	−0.1205
	(−0.55)	(−0.63)	(−0.48)
Cyb	0.1572	0.1133	0.2037
	(0.85)	(0.59)	(1.11)
female_ceo	−0.3241	−0.3209	−0.3434
	(−1.09)	(−1.10)	(−1.15)
female_chair	−0.8584**	−0.8849***	−0.8620**
	(−2.48)	(−2.75)	(−2.50)
female_board	4.6283***	4.6473***	4.6594***
	(6.72)	(7.15)	(6.77)
Year, Industry, Region	control	control	control
Intercept	0.8823	1.0964	0.8609
	(0.92)	(1.13)	(0.90)
N	2235	2235	2235
Pseudo R2	0.184	0.181	0.182

T values are in the brackets; *, **, and *** means being significant at the level of 10%, 5%m and 1% respectively; standard error of firm clustering.

Table 7. Impact of female committee members’ professional background on their influence.

dependent var = pass
	1	2
Female_nlaw	−0.3008
	(−1.61)
Female_law	−0.4141**
	(−1.99)
Female_nacct		−0.1377
		(−0.54)
Female_acct		−0.3998**
		(−2.25)
m_exp	0.2918***	0.3050***
	(3.32)	(3.44)
m_education	−1.4041***	−1.3347***
	(−3.75)	(−3.45)
ab_size	0.7467***	0.7516***
	(7.05)	(7.05)
ab_lev	−1.9213***	−1.9306***
	(−3.87)	(−3.87)
ab_roa	0.3032*	0.3006*
	(1.89)	(1.86)
ab_growth	0.1762**	0.1765**
	(2.27)	(2.37)
ab_vol	−2.5000***	−2.4679***
	(−3.70)	(−3.65)
Soe	−0.1463	−0.1424
	(−0.58)	(−0.57)
Cyb	0.2150	0.1760
	(1.14)	(0.96)
female_ceo	−0.3228	−0.3321
	(−1.08)	(−1.11)
female_chair	−0.8667**	−0.8733**
	(−2.53)	(−2.53)
female_board	4.6075***	4.5984***
	(6.68)	(6.71)
Industry, Year, Region	control	control
Intercept	0.8389	0.7582
	(0.88)	(0.78)
N	2235	2235
pseudo R-sq	0.181	0.181

T values are in the brackets; *, **, and *** means being significant at the level of 10%, 5%m and 1% respectively; standard error of firm clustering.

Table 8. Impact of applicant companies’ nature of property rights on female committee members’ influence.

dependent var = pass
	1	2
	SOE	NONSOE
female	−1.4438**	−0.2886*
	(−2.25)	(−1.91)
m_exp	0.7051**	0.2640***
	(2.35)	(2.85)
m_education	−1.0054	−1.6995***
	(−0.62)	(−4.06)
ab_size	1.8398***	0.7209***
	(3.99)	(6.12)
ab_lev	−4.4501***	−1.9843***
	(−2.70)	(−4.09)
ab_roa	0.7517	0.3666
	(1.61)	(1.01)
ab_growth	0.0528	0.2711***
	(0.20)	(2.85)
ab_vol	−6.5833**	−2.6919***
	(−2.21)	(−3.98)
cyb	1.4283	0.1532
	(1.31)	(0.80)
female_ceo	1.0669	−0.2884
	(0.46)	(−0.95)
female_chair	−3.5224	−0.9731***
	(−1.42)	(−2.88)
female_board	8.5608**	4.5626***
	(2.08)	(6.76)
Industry, Year, Region	control	control
Intercept	1.5511	0.7052
	(0.52)	(0.63)
N	323	1912
pseudo R-sq	0.445	0.187

T values are in the brackets; *, **, and *** means being significant at the level of 10%, 5%m and 1% respectively; standard error of firm clustering.

Table 9. Influence of the proportion of participating female committee members on the examination.

Dependent var = pass
	coefficient	T
Female_ratio	−1.0583**	−1.97
m_exp	0.2834***	3.21
m_education	−1.4324***	−3.85
ab_size	0.7540***	7.31
ab_lev	−2.0447***	−3.83
ab_roa	0.0180	0.59
ab_growth	0.1711**	2.32
ab_vol	−2.6115***	−3.94
Soe	−0.1602	−0.64
Cyb	0.1470	0.82
female_ceo	−0.3482	−1.19
female_chair	−0.8729**	−2.54
female_board	4.6321***	6.68
Industry, Year, Region	control
_cons	0.8911	0.94
N	2235
pseudo R-sq	0.180

T values are in the brackets; *, **, and *** means being significant at the level of 10%, 5%m and 1% respectively; standard error of firm clustering.

Table 10. Influence of the board on the examination.

Dependent var = pass
	1	2
cyb	0.1279	−0.2252
	(0.70)	(−0.85)
female		−0.5835***
		(−2.85)
Female*cyb		0.6299**
		(2.08)
m_exp	0.3241***	0.2694***
	(3.78)	(3.09)
m_education	−1.3978***	−1.4184***
	(−3.74)	(−3.78)
ab_size	0.7477***	0.7550***
	(7.01)	(7.10)
ab_lev	−1.9191***	−1.9030***
	(−3.89)	(−3.80)
ab_roa	0.2998*	0.2949*
	(1.87)	(1.82)
ab_growth	0.1793**	0.1746**
	(2.31)	(2.23)
ab_vol	−2.5135***	−2.4453***
	(−3.73)	(−3.62)
Soe	−0.1520	−0.1462
	(−0.60)	(−0.58)
female_ceo	−0.3213	−0.3183
	(−1.09)	(−1.08)
female_chair	−0.8591**	−0.8818**
	(−2.49)	(−2.57)
female_board	4.5389***	4.6318***
	(6.58)	(6.75)
Industry,Year.Region	control	control
Intercept	0.5416	1.0040
	(0.57)	(1.05)
N	2235	2235
pseudo R-sq	0.178	0.183

T values are in the brackets; *, **, and *** means being significant at the level of 10%, 5%m and 1% respectively; standard error of firm clustering.

Table 11. Influence of female committee members under issuance control with different strictness.

Dependent var = pass
	1	2
	Strict = 0	Strict = 1
Female	−0.3926*	−0.2339
	(−1.77)	(−0.74)
m_education	−1.6731***	−1.4695
	(−3.58)	(−1.40)
m_exp	0.3045***	0.1810
	(2.88)	(0.72)
ab_size	0.8030***	0.8379***
	(6.57)	(3.40)
ab_lev	−2.3671***	−1.6025
	(−3.79)	(−1.64)
ab_roa	0.3926*	1.1869
	(1.86)	(0.45)
ab_growth	0.2591**	1.0200
	(2.06)	(1.51)
ab_vol	−3.3883***	−1.8688
	(−4.50)	(−1.17)
Soe	−0.3435	0.3358
	(−1.07)	(0.76)
Cyb	−0.0477	0.4553
	(−0.20)	(1.17)
female_ceo	0.0460	−0.8440
	(0.12)	(−1.62)
female_chair	−0.4658	−1.3179**
	(−1.00)	(−2.46)
female_board	5.1428***	3.4326***
	(5.77)	(2.87)
Industry, Year, Region	control	control
Intercept	15.2396***	19.8227***
	(15.99)	(6.39)
N	1315	920
pseudo R-sq	0.206	0.212

T values are in the brackets; *, **, and *** means being significant at the level of 10%, 5%m and 1% respectively; standard error of firm clustering.

Table 12. Participation of female committee member and listed company’s violations.

dependent var = violate
	coefficient	T
female	−0.4445**	−2.17
size	−0.2965**	−2.40
lev	0.8880	1.11
roa	−9.0800**	−2.11
bigshare	−0.5988	−0.97
mb	−0.0955	−1.51
indep	1.8759	1.16
female_ceo	0.2491	0.78
female_chair	0.2227	0.61
female_board	0.0621	0.09
行业, 年份	control
Intercept	4.8716*	1.73
N	1642
pseudo R-sq	0.102

T values are in the brackets; *, **, and *** means being significant at the level of 10%, 5%m and 1% respectively; standard error of firm clustering.

Table 13. Whether there are female committee members.

Depend var = female
	coefficient	T
Size	−0.0980	−1.60
Lev	0.1912	0.46
Soe	0.2572	1.44
Roa	1.2624	0.93
growth	0.2658	1.14
Goods	−0.5495	−0.99
op_cash	−1.0153	−1.06
Fix	−0.3464	−0.85
bigshare	0.1407	0.47
Industry, Year	control
Intercept	1.4845	1.07
N	2235
Pseudo R2	0.2374

T values are in the brackets; *, **, and *** means being significant at the level of 10%, 5%m and 1% respectively; standard error of firm clustering.

Table 14. Examination participated by female committee members based in PSM.

Depend var = female
	coefficient	T
female	−0.3516**	−2.18
m_education	−1.6231***	−3.08
m_exp	0.3337***	2.93
ab_size	0.8192***	6.40
ab_lev	−1.5808**	−2.29
ab_roa	0.3682**	2.04
ab_growth	0.1939***	3.01
ab_vol	−2.9589***	−3.35
Soe	−0.3422	−1.06
Cyb	−0.0665	−0.26
female_ceo	−0.2437	−0.68
female_chair	−0.7003	−1.53
female_board	5.1823***	5.48
Industry, Year. Region	control
Intercept	0.8181	0.72
N	1966
pseudo R-sq	0.260

T values are in the brackets; *, **, and *** means being significant at the level of 10%, 5%m and 1% respectively; standard error of firm clustering.

Table 15. Post-listing performance of companies approved by female committee members based on PSM.

	(1)	(2)	(3)	(4)
	change_rev1	change_income1	change_rev2	change_income2
female	0.1504***	0.0907***	0.2142***	0.1051*
	(4.55)	(2.74)	(3.62)	(1.90)
Industry_change	0.4553***	0.6549***	0.1841	0.2958
	(3.39)	(4.87)	(0.83)	(1.43)
size	0.0930***	0.1476***	0.1061***	0.1652***
	(4.73)	(7.50)	(3.19)	(5.32)
lev	−0.1063	−0.0273	0.0708	−0.0016
	(−0.95)	(−0.24)	(0.37)	(−0.01)
mb	0.0421***	0.0738***	0.0720***	0.0941***
	(5.20)	(9.12)	(5.31)	(7.42)
indep	0.0128	−0.3087	0.2073	−0.1029
	(0.04)	(−0.97)	(0.38)	(−0.20)
bigshare	−0.2683**	−0.1205	−0.4201**	−0.2584
	(−2.27)	(−1.02)	(−2.04)	(−1.34)
female_ceo	0.1885***	0.1661**	0.2487**	0.1845
	(2.67)	(2.35)	(2.04)	(1.62)
female_chair	0.0116	0.0516	0.0218	0.0018
	(0.15)	(0.67)	(0.16)	(0.01)
female_board	−0.3377**	−0.3922***	−0.5524**	−0.5316**
	(−2.44)	(−2.83)	(−2.20)	(−2.26)
Year	control	control	control	control
Intercept	−1.2225***	−2.8811***	−1.2419*	−3.0995***
	(−2.92)	(−6.89)	(−1.76)	(−4.69)
N	1214	1214	1214	1214
adj. R-sq	0.044	0.082	0.030	0.047

T values are in the brackets; *, **, and *** means being significant at the level of 10%, 5%m and 1% respectively; standard error of firm clustering.

Table 16. Post-listing performance of companies approved by female committee members based on PSM.

	1	2
	BHAR12	BHAR24
female	0.0776**	0.0854**
	(2.14)	(2.26)
size	−0.0924***	−0.0994***
	(−4.71)	(−4.87)
lev	1.0120***	0.8652***
	(7.88)	(6.48)
bigshare	0.0246	−0.0059
	(0.22)	(−0.05)
mb	0.0826***	0.0782***
	(9.86)	(8.96)
indep	−0.1369	0.0935
	(−0.46)	(0.30)
female_ceo	0.0439	0.0590
	(0.70)	(0.91)
female_chair	0.0173	0.0944
	(0.24)	(1.26)
female_board	0.1438	0.1157
	(1.12)	(0.86)
Industry, Year	control	control
Intercept	1.4746***	1.9641***
	(3.25)	(4.16)
N	1214	1214
adj. R-sq	0.338	0.241

T values are in the brackets; *, **, and *** means being significant at the level of 10%, 5%m and 1% respectively; standard error of firm clustering.

Table

Variable	Variable Name	Definition
pass	Whether it passes the examination	If the application is approved, it is 1, otherwise it is 0.
female	Female committee member	If there are female committee members participating in the issuance examination, it is 1, otherwise it is 0.
female_ratio	Proportion of female committee member	Proportion of female committee members participating in the insurance examination
female_fulltime	Part-time female committee member	If the female committee member participating in the insurance examination is full time, it is 1, otherwise it is 0.
female_parttime	Full time female committee member	If the female committee member participating in the insurance examination is part time, it is 1, otherwise it is 0.
female_senior	Senior female committee member	If the insurance examination experience of the participating female committee member is greater than the average value, it is 1, otherwise it is 0.
female_junior	Junior female committee member.	If the insurance examination experience of the participating female committee member is smaller than the average value, it is 1, otherwise it is 0.
female_ncrsc	Female committee member from the CRSC	If the participating female committee member is from the CRSC, it is 1, otherwise it is 0.
female_crsc	Female committee member not from the CRSC	If the participating female committee member is not from the CRSC, it is 1, otherwise it is 0.
female_nlaw	Female committee members with lawyer background	If the participating female of committee member has the lawyer background, it is 1, otherwise it is 0.
female_law	Female committee members without lawyer background	If the participating female of committee member has no lawyer background, it is 1, otherwise it is 0.
female_nacct	Female committee members with accountant background	If the participating female of committee member has the accountant background, it is 1, otherwise it is 0.
female_acct	Female committee members without accountant background	If the participating female of committee member has no accountant background, it is 1, otherwise it is 0.
m_exp	Average insurance examination experience of participating committee members	The average value of natural logarithm of the number of times the committee members participating in the insurance examination
education	Average education level of participating committee members	The average education level of participating committee members: for each member, if he/she has Bachelors degree or above, it is 1, otherwise it is 0.
ab_size	Size	The natural logarithm of the average total assets of the company in the three years before listing minus the industry average value in the corresponding year
ab_lev	Debt ratio	The average total liabilities divided by average total assets minus the industry average value in the three years before listing
ab_roa	Probability	The average net profit of the three years before listing divided by the average total assets minus the industry average value of the corresponding year
ab_growth	Growth	The average growth rate of operating revenue in the three years before listing minus the industry average value of corresponding years
ab_vol	Earnings volatility	The standard deviation of the company’s earnings in the three years before listing divided by the average value minus the average value of the corresponding year
Soe	Nature of property rights	If the actual controller is state-owned, it is 1, otherwise it is 0.
cyb	Growth Enterprise Market	If the company is listed on the GEM, it is 1 m otherwise it is 0.
H_lev	High financial risk	If the debt ratio of the listed company is higher than the median debt ratio of the industry, it is 1, otherwise it is 0.
H_vol	High operating risk	If the standard deviation of the main business income of the applicant company in the past three years is greater than the median of the listed companies, it is 1, otherwise it is 0
Strict	Generally strict issuance examination	If the total pass rate of the year is greater than the median, it is one, otherwise it is 0.
BHAR12	Excess returns of buying and holding in 12 months	The company’s accumulated income of 12 months after the listing minus the accumulated market income of the corresponding period
BHAR24	Excess returns are buying and holding in 24 months	The company’s accumulated income of 24 months after the listing minus the accumulated market income of the corresponding period
wbigshare	Shareholding ratio of major shareholders	The number of shares held by major shareholders divided by the total number of shares in the company
mb	Market to book ratio	Market value divided by book value
indep	Proportion of independent directors	The number of Independent Directors divided by the number of board of directors
change_rev1	Changes of operating revenue in one year before and after listing	(Operating income of the year after listing – operating income of the year before listing)/operating revenue of the year before listing
change_income1	Changes of net income in one year before and after listing	(Net income of the year after listing – net income of the year before listing)/net income of the year before listing
change_rev2	Changes of operating revenue in two years before and after listing	(Operating income of two years after listing – operating income of two years before listing)/operating revenue of two years before listing
change_income2	Changes of net income in two years before and after listing	(Net income of two years after listing – net income of two years before listing)/net income of two years before listing
industry_change1	Changes of operating income of industry	(Average operating income of the industry in the current year – average operating income of the industry in the previous year)/average operating income of the industry in the previous year
industry_change2	Changes of net income of industry	(Average net income of the industry in the current year – average net income of the industry in the previous year)/average net income of the industry in the previous year