The moderating effect of the interaction between joint audit and accounting conservatism on the association between corporate governance and corporate performance

Figures & data

Table 1. Sample selection.

Panel A: the final sample
Total population			152
Excluding (–)
Financial firms			(32)
Firms whose reports were missing or unavailable			(19)
Firms whose shares were not listed or traded during the research period			(5)
Firms that didn’t submit their annual financial reports by December 31			(35)
The final sample			61
Panel B: industrial composition
No.	Sectors	Companies	Observations
			No.	%
1	Health care and pharmaceuticals	7	35	11.5
2	Real estate	13	65	21.3
3	Food, beverages and tobacco	8	40	13.1
4	Basic resources	6	30	9.8
5	Industrial goods, services and automobiles	3	15	4.9
6	Travel and leisure	5	25	8.2
7	Telecommunication services, media and information technology	4	20	6.6
8	Construction and materials	5	25	8.2
9	Trade and distributors	2	10	3.3
10	Contracting and construction engineering	5	25	8.2
11	Textile and durables	3	15	4.9
Total		61	305	100%

Table 2. Variables description.

Variable	Acronym	Measurement	Source
Dependent variable
Corporate performance (CP)	ROA	The net income to total assets ratio	(Boachie & Mensah, 2022; Mishra et al., 2021; Puni & Anlesinya, 2020; Tsafack & Guo, 2021)
	ROE	The net income divided by shareholders’ equity ratio	(Amer et al., 2014; André et al., 2015; Khatib & Nour, 2021; Tsafack & Guo, 2021; Wang et al., 2020)
	Tobin’s Q	The equity market value and total debt to the total asset book value ratio	(Amer et al., 2014; Black et al., 2015; Boshnak et al., 2023; Mishra et al., 2021; Tsafack & Guo, 2021; Wang et al., 2020)
Moderating variable
Joint audit	JA	A dummy variable that takes a value of 1 if the firm adopts voluntary JA and 0 otherwise	(Ittonen & Trønnes, 2014; Lobo et al., 2016; Zerni et al., 2012)
Accounting conservatism	MTB	The number of issued shares multiplied by their closing price to the book value of net assets	(Beaver & Ryan, 2005; Lobo et al., 2016; Marmousez, 2008; Velte & Azibi, 2015)
Independent variables
Board independence	BIND	The proportion of independent directors to total board members	(Ciftci et al., 2019; Haque, 2017; Haron et al., 2022; Karaibrahimoglu, 2013)
Board expertise	BEXP	The ratio of the number of members with financial experience to the total number of board members	(Alawaqleh et al., 2021; Alfraih, 2016; Alqadasi & Abidin, 2018; Das et al., 2020)
Audit committee independence	ACIND	The proportion of independent members to total AC members	(Abbott & Parker, 2000; Al Farooque et al., 2020)
Audit committee members experience	ACEXP	The ratio of the number of members with financial experience to the total number of AC members	(Alodat et al., 2022; J. Krishnan et al., 2011)
Audit firm size	AFSIZE	Measured as a dummy variable that takes a value of 1 if the audit firm is Big 4 and 0 otherwise	(Alawaqleh et al., 2021; Lawrence et al., 2011; Soliman & Elsalam, 2013; Velte & Azibi, 2015)
Corporate governance index	CGI	To calculate the CGI, each of the non-binary variables is converted to a binary form by assigning a 1 to the variable that is greater than or equal to the median for all samples and a 0 otherwise; the CGI is the sum of the five indicators, which ranges from zero to five, with five being the highest CGI	(Al-ahdal et al., 2021; Mishra et al., 2021; Nguyen & Dao, 2022)
Control variables
Firm size	LSIZE	Total assets, natural logarithm at the end of the year	(Amer et al., 2014; Antounian et al., 2021; Boachie & Mensah, 2022; Sheikh & Alom, 2021; Wang et al., 2020)
Leverage	LEV	Total liabilities to total assets ratio (another indicator of bankruptcy risk)	(Antounian et al., 2021; Boachie & Mensah, 2022; Tsafack & Guo, 2021; Wang et al., 2020)
Liquidity	LIQ	Total current assets to total current liabilities	(Aljifri, 2014; Antounian et al., 2021; Zerni et al., 2012)

Figure 1. Research framework.

Table 3. Descriptive statistics.

Variables	Mean	Std. dev	Minimum	Maximum
ROA	0.04	0.08	−0.17	0.49
ROE	0.01	0.78	−12.11	0.89
Tobin’s Q	1.05	1.53	0.04	17.23
JA	0.36	0.48	0	1
MTB	1.85	2.35	0.02	17.28
BIND	0.17	0.18	0	0.85
BEXP	0.17	0.13	0	0.8
ACIND	0.36	0.30	0	1
ACEXP	0.34	0.23	0	1
AFSIZE	0.69	0.56	0	1
CGI	3.82	0.64	2	5
LSIZE	21.97	1.74	17.29	25.49
LEV	0.76	1.75	0.00	20.16
LIQ	2.03	5.33	0.19	54.14

Table 4. Correlation matrix results.

Probability	Tobin’s Q	ROE	ROA	JA	MTB	BIND	BEXP	ACIND	ACEXP	AFSIZE	CGI	LSIZE	LEV	LIQ
Tobin’s Q	1
ROE	0.02	1
ROA	0.09	0.35***	1
JA	0.17***	−0.09	−0.06	1
MTB	0.10*	−0.10*	−0.02	0.13**	1
BIND	0.05	0.03	0.08	0.04	−0.03	1
BEXP	−0.04	−0.02	−0.01	0.13**	−0.05*	−0.04	1
ACIND	0.04	0.04	0.11**	0.06	−0.07	0.44***	0.17***	1
ACEXP	−0.05	−0.04	−0.14**	0.30***	−0.13**	−0.01	0.49***	0.27***	1
AFSIZE	−0.10*	−0.14**	−0.06	0.31***	0.10**	0.04	0.16***	0.29***	0.24***	1
CGI	−0.43***	0.51**	0.16***	0.15***	0.17**	0.14**	0.12***	0.15**	0.14**	0.12*	1
LSIZE	−0.20***	−0.09*	−0.08	0.20***	−0.08	0.18***	0.00	0.26***	0.20***	0.48***	−0.03	1
LEV	0.65***	−0.03	−0.13**	0.17***	−0.01	−0.02	−0.00	0.03	0.04	−0.08	0.12**	−0.04	1
LIQ	0.00	0.03	0.06	−0.11	−0.02	−0.09	0.04	0.11**	−0.00	−0.16***	0.15***	−0.35***	−0.07	1
VIF	1.11	1.23	1.20	1.07	1.14	1.19	1.29	1.07	1.17	1.11	1.23	1.14	1.23
Tolerance	0.903	0.813	0.833	0.933	0.874	0.842	0.778	0.932	0.855	0.897	0.813	0.875	0.807

Note: *, ** and *** are the significance levels at 0.1, 0.05 and 0.01, respectively.

Table 5. Direct effect regression results.

Variables	Model 1: ROA	Model 2: ROE	Model 3: Tobin’s Q
C	0.07	0.03	7.32***
	0.05	0.04	0.71
JA	−0.10***	−0.19***	−0.79
	0.03	0.05	0.65
MTB	−0.00***	−0.01***	0.02
	0.00	0.00	0.01
BIND	0.04**	0.18***	−0.08***
	0.02	0.03	0.03
BEXP	−0.45*	−0.69***	0.83***
	0.23	0.19	0.29
ACIND	0.07	0.09*	0.06
	0.05	0.05	0.07
ACEXP	−0.11***	−0.01	0.20
	0.03	0.03	0.23
AFSIZE	0.01	0.01	−0.15***
	0.02	0.02	0.02
CGI	0.15***	0.16**	−0.31***
	0.02	0.05	0.08
LSIZE	0.08***	0.19***	−0.30***
	0.03	0.02	0.03
LEV	0.01*	0.27***	0.60***
	0.01	0.00	0.07
LIQ	−0.00	−0.00**	0.01**
	0.00	0.00	0.00
R-squared	0.72	0.83	0.89
Adjusted R-squared	0.62	0.71	0.84
F-statistic	6.34	11.80	29.76
Prob (F-statistic)	0	0	0
Durbin-Watson stat	1.77	2.08	2.17

Note: *, ** and *** are the significance levels at 0.1, 0.05 and 0.01, respectively.

Table 6. Moderating effect regression result.

Variables	Model 4: ROA	Model 5: ROE	Model 6: Tobin’s Q
	Coefficient	Coefficient	Coefficient
C	0.26	2.28***	5.48***
	0.13	0.19	0.89
CGI	0.43***	0.31**	0.22*
	0.07	0.03	0.05
JA	−0.05***	−0.07*	−1.12*
	0.02	0.04	0.47
MTB	−0.02***	−0.04***	0.05
	0.01	0.00	0.04
CGI * JA * MTB	0.48**	0.26***	0.18***
	0.11	0.08	0.04
LSIZE	−0.01	−0.12***	−0.22***
	0.01	0.02	0.02
LEV	0.01	0.02	0.72***
	0.00	0.01	0.07
LIQ	−0.01***	−0.01***	0.02***
	0.00	0.00	0.00
R-squared	0.87	0.81	0.82
Adjusted R-squared	0.82	0.79	0.80
F-statistic	47.28	29.49	37.26
Prob (F-statistic)	0	0	0
Durbin-Watson stat	2.25	1.93	2.11

Note: *, ** and *** are the significance levels at 0.1, 0.05 and 0.01, respectively.

Table 7. Alternative moderating effect regression result.

Variables	Model 4: ROA	Model 5: ROE	Model 6: Tobin’s Q
C	0.093***	0.481***	0.123
	0.018	0.042	0.173
JA	−0.062***	−0.057***	−1.139*
	0.017	0.022	0.605
MTB	−0.001***	−0.015***	0.009
	0.000	0.002	0.006
BIND	−0.035***	−0.093***	−0.223***
	0.007	0.022	0.058
JA*MTB*BIND	0.023**	0.197***	−0.051**
	0.009	0.016	0.026
BEXP	−0.195**	−2.009***	6.144***
	0.089	0.494	1.680
JA*MTB*BEXP	−0.051**	−0.213***	0.328**
	0.021	0.044	0.138
ACIND	0.041***	0.008	0.509***
	0.009	0.045	0.060
JA*MTB*ACIND	−0.015***	−0.236***	−0.298***
	0.004	0.045	0.030
ACEXP	−0.025*	−0.262***	1.114***
	0.015	0.079	0.046
JA*MTB*ACEXP	0.006	0.062**	−0.155**
	0.005	0.027	0.074
AFSIZE	0.015***	−0.007	−0.219***
	0.003	0.012	0.020
JA*MTB*AFSIZE	0.008***	0.057***	0.058**
	0.002	0.017	0.028
LSIZE	0.045***	0.144***	0.141***
	0.004	0.019	0.049
LEV	0.004	0.016***	0.244***
	0.004	0.003	0.065
LIQ	−0.001***	−0.001***	0.016***
	0.000	0.000	0.005
R-squared	0.919	0.821	0.959
Adjusted R-squared	0.884	0.741	0.912
F-statistic	25.60	10.25	53.44
Prob (F-statistic)	0	0	0
Durbin-Watson stat	1.543	1.521	2.656

Note: *, ** and *** are the significance levels at 0.1, 0.05 and 0.01, respectively.

Table 8. Further regression results.

Variables	Single audit			Joint audit
	ROA	ROE	Tobin’s Q	ROA	ROE	Tobin’s Q
C	0.02***	0.05**	1.82***	−0.04***	−0.28	0.96***
	0.00	0.02	0.11	0.01	0.20	0.31
MTB	−0.00***	−0.01***	0.03**	0.00**	0.03*	0.09***
	0.00	0.00	0.01	0.00	0.02	0.02
BIND	0.05**	0.17**	0.37***	0.01	−0.23***	−0.67***
	0.02	0.07	0.07	0.01	0.07	0.20
BEXP	−0.41***	−0.47***	−0.63***	−0.12	0.36	2.52
	0.04	0.13	0.08	0.18	0.24	2.66
ACIND	0.01	0.01	−0.06	0.01	0.37***	0.25
	0.01	0.02	0.04	0.01	0.06	0.29
ACEXP	−0.04***	−0.04	−0.51***	−0.02***	−0.22**	−0.60***
	0.01	0.03	0.03	0.01	0.09	0.21
AFSIZE	0.01*	0.02***	0.03	−0.00	−0.17***	−0.13
	0.00	0.00	0.02	0.00	0.03	0.11
LSIZE	0.17***	0.47***	−0.04***	0.05***	0.005	−1.18***
	0.02	0.03	0.00	0.02	0.01	0.16
LEV	−0.21***	−0.78***	−0.16**	0.01**	−0.00	0.26
	0.02	0.06	0.06	0.00	0.00	0.23
LIQ	0.00***	0.00	0.01*	0.05***	0.20***	0.15
	0.00	0.00	0.00	0.00	0.02	0.13
R-squared	0.47	0.66	0.46	0.51	0.39	0.33
Adjusted R-squared	0.44	0.63	0.43	0.45	0.32	0.25
F-statistic	14.47	30.94	17.61	8.91	5.59	4.29
Prob (F-statistic)	0	0	0	0	0	0
Durbin-Watson stat	1.42	1.49	1.49	1.47	1.48	1.76

Note: *, ** and *** are the significance levels at 0.1, 0.05 and 0.01, respectively.

Table 9. Further moderating effect regression results.

Variables	Big firms			Small firms
	ROA	ROE	Tobin’s Q	ROA	ROE	Tobin’s Q
C	−0.316**	3.363	1.826**	0.083	−0.254	3.102*
	0.128	3.109	0.734	0.164	0.333	1.696
JA	−0.003	0.399	0.197***	−0.003	−0.014	−0.417*
	0.012	0.323	0.075	0.020	0.044	0.235
MTB	0.018***	0.199**	0.261***	−0.000	−0.015***	0.011
	0.004	0.102	0.024	0.000	0.002	0.007
BIND	−0.029	−0.301	−0.606***	0.031	−0.188**	1.122***
	0.035	0.844	0.191	0.043	0.092	0.424
JA*MTB*BIND	0.063	1.838	0.135	−0.021	−0.055	0.179
	0.058	1.155	0.174	0.037	0.084	0.287
BEXP	0.068	0.434	0.057	0.119*	0.336**	0.037
	0.051	1.139	0.303	0.066	0.161	0.743
JA*MTB*BEXP	−0.068**	−3.117*	−1.659***	−0.044	−0.206	2.673**
	0.029	1.734	0.262	0.056	0.159	1.096
ACIND	0.019	0.143	0.312**	0.062*	0.066	0.151
	0.023	0.613	0.151	0.034	0.066	0.335
JA*MTB*ACIND	−0.021	1.162***	−0.066	0.054***	0.291***	0.537***
	0.042	0.421	0.096	0.015	0.033	0.137
ACEXP	−0.049**	−0.039	−0.071	−0.119**	−0.438***	−0.998**
	0.024	0.733	0.139	0.052	0.113	0.506
JA*MTB*ACEXP	0.080**	−0.807	−0.243**	−0.002	0.089	−0.871**
	0.037	0.569	0.118	0.016	0.066	0.411
AFSIZE	−0.018	0.163	−0.045	−0.003	0.072*	0.247
	0.011	0.295	0.069	0.016	0.038	0.167
JA*MTB*AFSIZE	−0.017	−0.509***	0.125***	0.016	−0.121***	−0.127
	0.014	0.164	0.042	0.015	0.025	0.107
LSIZE	0.016***	−0.121	−0.032	−0.002	0.018	−0.127
	0.005	0.134	0.032	0.008	0.017	0.085
LEV	−0.088***	−1.429**	−0.681***	−0.004	0.003	0.783***
	0.030	0.677	0.159	0.003	0.007	0.030
LIQ	0.018**	−0.043	−0.224***	−0.000	0.013***	0.008
	0.008	0.194	0.044	0.001	0.003	0.011
R-squared	0.403	0.244	0.716	0.296	0.663	0.863
Adjusted R-squared	0.317	0.135	0.675	0.219	0.627	0.848
F-statistic	4.679	2.243	17.477	3.871	18.135	58.241
Prob (F-statistic)	0	0	0	0	0	0
Durbin-Watson stat	0.808	1.361	0.945	1.123	1.754	1.317

Note: *, ** and *** are the significance levels at 0.1, 0.05 and 0.01, respectively.

Table 10. Two stage Heckman test.

Variable	ROA	ROE	Tobin’s Q
C	0.019	0.086	3.762***
	0.026	0.098	0.217
JA	−0.011***	−0.044***	−0.165***
	0.004	0.018	0.034
MTB	−0.070***	−0.008***	0.030
	0.028	0.002	0.006
BIND	0.016***	0.059***	−0.529***
	0.012	0.042	0.095
BEXP	−0.012***	−0.154***	0.297***
	0.020	0.046	0.105
ACIND	0.030	0.082***	0.203
	0.007	0.030	0.054
ACEXP	−0.068***	−0.163	0.195
	0.007	0.038	0.055
AFSIZE	0.005	0.048	−0.083***
	0.004	0.012	0.025
LSIZE	0.001422***	0.044***	−0.162***
	0.001	0.004	0.010
LEV	0.007*	0.010***	0.675***
	0.002	0.003	0.035
LIQ	0.016	−0.002**	0.002***
	0.044	0.002	0.005
Wald chi2(12)	56.220	62.110	48.550
Prob > chi2	0.240	0.330	0.190

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