Audit committee characteristics and earning management of insurance companies in Ethiopia

Figures & data

Figure 1. Conceptual frame work.

Table 1. Study sample.

Total number of insurance companies	18
Number of insurance companies with missing data	1
Final study sample	17

Table 2. Variables and their measurement.

Variables	Symbol	Measurement
Dependent variable
Earning management (Ratio)	EM	Discretionary Accruals (DA) measured by the modified Jones model. EM = $\frac{\mathit{\text{Total company accuta}}}{\mathit{\text{Total asset at t}}-1}$
Independent variables
Audit committee size (Continuous variable)	ACS	It is a total number of audit committee members.
Audit committee independence (Ratio)	ACI	The percentage of number of independent director over the total number of directors in the audit committee. ACI = $\frac{\mathit{\text{Independent director}}}{\mathit{\text{Total number of audit committee}}}$
Audit committee meeting (Continuous variable)	ACM	Number of meetings of audit committees per year
Audit committee expertise (Ratio)	ACE	The percentage of members with accounting or financial expertise on the audit committee. ACE = $\frac{\mathit{\text{Number of financial expert}}}{\mathit{\text{Total number of audit commitees}}}$
Audit committee gender (Ratio)	ACG	The percentage of female members in audit committee. ACG = $\frac{\mathit{\text{Number of female in audit committee}}}{\mathit{\text{Total number of audit commitee}}}$

Table 3. Descriptive statistics.

Variables	Obs	Mean	Std. Dev	Min	Max
EM	136	16.657	13.754	1.256	56.321
ACS	136	4.7647	1.521	3	7
ACI	136	0.4241	0.2031	0.026	0.965
ACE	136	0.2101	0.0803	0.012	0.3985
ACG	136	0.0814	0.0933	.012	0.3265
ACM	136	15.5	6.2598	2	36

Table 4. Correlation matrix.

	EM	ACS	ACI	ACE	ACG	ACM
EM	1.0000
ACS	0.1679	1.0000
ACI	0.1713	0.2253	1.0000
ACE	0.1127	0.1623	0.2830	1.0000
ACG	0.1604	−0.1754	−0.1966	−0.0325	1.0000
ACM	0.0151	−0.1478	−0.0094	0.0723	−0.0274	1.0000

Table 5. The two–step system GMM estimation results.

	Coef	Std. Err	z	P>|z|	[95% Conf. Interval]
Emit-1	0.542	0.236541	1.32	0.025**	0.1265321 6.54561
ACS	0.9755	1.994095	0.49	0.062*	−2.932846 4.883863
ACI	12.270	3.946041	3.11	0.002***	4.536822 20.00502
ACE	14.779	10.4114	1.42	0.046*	−5.626431 35.18552
ACG	1.562	7.995064	−0.20	0.084*	−17.23246 14.10761
ACM	0.048	.1276955	−0.38	0.005***	−.298597 .2019602
Cons	4.574	10.37868	0.44	0.059*	−15.76691 24.91676
Wald stat	13.254
AdjR^2	0.446
AR^2(p-value	0.014

***, **,* indicates significant at 1%, 5% and 10% significance level, respectively.

Table 6. Multicollinearity test for explanatory variables.

Variables	VIF	1/VIF
ACI	1.16	0.861675
ACS	1.12	0.894974
ACE	1.11	0.899563
ACG	1.07	0.938883
ACM	1.04	0.965663
Mean VIF 1.10

Table 7. Normality test.

Variable	Obs	W	V	z	Prob>z
EM_hat	136	0.91206	9.411	5.056	0.2132