Relationship between corporate governance and firm performance in Ghana: does compliance to national governance frameworks matter?

Figures & data

Figure 1. The moderating role of NGQ in the CG-firm performance relationship.

Table 1. Sample size determination.

Sample criteria		Number of companies
Companies listed on the GSE as of 2022		37
Less:	Firms with more than 5 years of missing data from 2013 to 2022	(6)
Final sample		31
Firm-year observations available for analysis		310

Source: African’Xchanges (2023).

Table 2. Variable description and measurements.

Variable	Measurement	Data source
Dependent variable
ROA Return on assets	Earnings after tax over book value of total assets	Annual reports of firms
Independent variable (Corporate governance)
CGI Corporate governance index	This is measured as an index constructed from rotated principal component analysis for firm i in year t, based on firm-level disclosure on corporate governance	Security and Exchange Commission (SEC) Corporate Governance Codes for Ghana, Annual reports of firms
Moderator:
NGQI National governance quality index	This is measured as an index constructed from rotated principal component analysis for firm i in year t, based on firm-level disclosure of Ghana’s laws, business regulations, and institutional frameworks	World Governance Indicators (WGIs) for Ghana, Annual reports of firms
Control variables:
SIZE Firm size	Natural logarithm of total assets	Annual reports of firms
LEV Leverage	Book value of total liabilities over book value of total assets	Annual reports of firms
AGE Firm age	Current year minus the year of incorporation in Ghana	Annual reports of firms

Table 3. Descriptive statistics.

Variables	N	Mean	Std. Dev	Min	Max
ROA	280	0.0211	0.1119	−0.5200	0.4938
CGI	280	0.5615	0.2689	0.0000	0.9230
NGQI	280	0.3333	0.2210	0.0000	0.9166
SIZE	280	5.4215	1.0985	3.1251	7.3323
LEV	280	0.6759	0.2739	0.0337	1.5402
AGE	280	34.0500	18.0488	1.0000	71.0000

Note: This table reports descriptive statistics based on the aggregate sample used in the research.

Table 4. Correlation matrix.

Variables	ROA	CGI	NGQI	SIZE	LEV	AGE
ROA	1.0000
CGI	−0.0175	1.0000
NGQI	0.1754***	0.6723***	1.0000
SIZE	0.2272***	0.3967***	0.2928***	1.0000
LEV	−0.3809***	0.2019***	−0.0038	0.3867***	1.0000
AGE	0.0784	0.1956***	0.0264	0.2203***	0.0556	1.0000

Note: This table reports the pair-wise correlation coefficients of the study variables. The triple stars (***) represent significance at 1%, double stars (**) represent significance at 5%, and a single star (*) refers to significance at 10%. The notations in this table are as defined and measured in Table 2.

Table 5. Results of unit root test.

	ADF – Fisher		LLC test
Variables	Level	First difference	Level	First difference
ROA	68.4991*	90.3422***	−5.6860***	−9.0305***
CGI	83.7041**	140.411***	−639.8730***	−295.2270***
NGQI	57.4614*	105.491***	−23.9934***	−8.2541***
SIZE	29.9429	76.6047**	−1.1382	−2.4959***
LEV	61.8503	90.6283***	−4.6253***	−4.6995***
AGE	5.10681*	0.0001**	−4.5653***	−4.6337**

Notes. This table reports the stationarity of the study variables. The triple stars (***) represent significance at 1%, double stars (**) represent significance at 5%, and a single star (*) refers to significance at 10%. The notations in this table are as defined and measured in Table 2.

Table 6. Diagnostic tests.

Multicollinearity test:
Variable	VIF	Tolerance (1/VIF)
CGI	2.14	0.4676
NGQI	1.97	0.5067
SIZE	1.41	0.7108
LEV	1.25	0.8023
AGE	1.10	0.9103
Heteroscedasticity Test:	χ^2	Prob > χ^2
Breusch-Pagan/Cook-Weisberg test	7.52***	0.0061
Normality Test:
Jarque-Bera test	211.2734***	0.0000
Skewness	−0.3886
Kurtosis	7.1839

Note. This table reports the diagnostic tests of the regression assumptions used in the study. The triple stars (***) represent significance at 1%, double stars (**) represent significance at 5%, and a single star (*) refers to significance at 10%. The notations in this table are as defined and measured in Table 2.

Table 7. Effect of CG on firm performance (ROA), with firm-level characteristics as the control variables.

Variables/model	(1)
CGI	−0.0297* (0.0161)
Controls:
SIZE	0.0327*** (0.0042)
LEV	−0.1578*** (0.0156)
AGE	0.0002 (0.0002)
Intercept	−0.0372* (0.0202)
Observations	280
F-statistic	127.4132
p-value	.0000
R-squared	0.3566
S.E. of regression	0.0950

Note: This table reports regression results on the effect of corporate governance on firm performance. Standard errors are presented in parentheses. The R-squared value of 0.3566 suggests that the independent variables included in the regression model can account for about 35.66% of the variation in firm performance. This indicates a moderate level of explanatory power. The triple stars (***) represent significance at 1%, double stars (**) represent significance at 5%, and a single star (*) refers to significance at 10%. The notations in this table are as defined and measured in Table 2.

Table 8. The moderating effect of NGQ on the relationship between CG and firm performance (ROA), with firm-level characteristics as the control variables.

Variables/model	(2)
CGI	−0.0920*** (0.0245)
NGQ	−0.0427 (0.0611)
Controls:
SIZE	0.0298*** (0.0045)
LEV	−0.1528*** (0.0162)
AGE	0.0002 (0.0002)
Moderator:
CGI × NGQI	0.1502** (0.0772)
Intercept	−0.0108 (0.0260)
Observations	280
F-statistic	146.7665
p-value	.0000
R-squared	0.3942
S.E. of regression	0.0938

Notes: This table reports regression results on the moderating effect of NGQ on the relationship between CG and firm performance. Standard errors are presented in parentheses. The R-squared value of 0.3942 suggests that the independent variables included in the regression model can account for about 39.42% of the variation in firm performance. This indicates a moderate level of explanatory power. The triple stars (***) represent significance at 1%, double stars (**) represent significance at 5%, and a single star (*) refers to significance at 10%. The notations in this table are as defined and measured in Table 2.

Table 9. The moderating effect of NGQ on the relationship between CG and firm performance (Tobin Q), with firm-level characteristics as the control variables.

Variables/model	(3)
CGI	−0.0369 0.0811)
NGQI	0.6555*** (0.2019)
Controls:
SIZE	−0.0862*** (0.0150)
LEV	0.6961*** (0.0535)
AGE	0.0037*** (0.0007)
Moderator:
CGI x NGQI	0.5986** (0.2549)
Intercept	0.7772*** (0.0859)
Observations	280
F-statistic	196.4416
p-value	.0000
R-squared	0.4606
S.E. of regression	6.4987

Note: This table reports regression results on the moderating effect of NGQ on the relationship between CG and firm performance (Tobin Q). Standard errors are presented in parentheses. The R-squared value of 0.4606 suggests that the independent variables used in the regression model can account for about 46.06% of the variation in firm performance. This indicates a moderate level of explanatory power. The triple stars (***) represent significance at 1%, double stars (**) represent significance at 5%, and a single star (*) refers to significance at 10%. The notations in this table are as defined and measured in Table 2.

African’Xchanges. (2023). https://afx.kwayisi.org/gse/

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Data availability statement

Data for the study is obtained from publicly available sources and can also be made available upon request.