The Effects of Corporate Governance on Financial Performance of Commercial Banks in a Turbulent Economic Environment

Newman Wadesango¹, Charity Mhaka², Blessing Mugona³, Hilja I. Haufiku⁴

Abstract: This study sought to investigate the effects of corporate governance on the financial performance of commercial banks in a turbulent economic and political environment. Board size, board composition, audit committee and leverage ratios and how they affected the financial performance of commercial banks in Zimbabwe during different economic and political landscapes were examined. Return on equity (ROE) was used as a measure of bank performance. An explanatory research design was used to investigate the relationship between corporate governance and financial performance of commercial banks in a hostile political and economic landscape. The population of study was 13 commercial banks regulated by the central bank of Zimbabwe. The sample size was 5/13 of the total population. Secondary data was collected from the annual reports of the 5 commercial banks. The data was gathered exclusively by analyzing the annual reports of the commercial banks for the period 2010 to 2017 and the data was analyzed using EViews 08. The period of study was split into two periods (2010–2013) being a relatively stable economic and political environment and (2014–2017) a period of high political and economic volatility to capture the difference in the political and economic environment. The study found that the employed measures of corporate governance were significant predictors of financial performance of commercial banks in Zimbabwe. The board size, board composition, the subcommittees and leverage were found to be significant in explaining the profitability of commercial banks in Zimbabwe in both periods (stable and turbulent environments). Based on the findings, another study encompassing all corporate governance tenets in different environments should be conducted to assess the full impact of the environment on corporate governance and performance of banks.

Keywords: Corporate governance; financial performance; turbulent economic environment

JEL Classification: G34

1. Background of the Study

The causes of the slowing economy of Zimbabwe after introduction of the multicurrency system can be attributed to two main factors, being corporate mismanagement and government policymaking (Cain, 2015). Through the indigenization policy, the Zimbabwean government eroded business and investor confidence (Masaka, 2012). The government of Zimbabwe introduced the policy to empower the previously disadvantaged black local populace by reserving for them at least 50% ownership of locally operating companies but the continuous changes in the implementation of the policy created uncertainty within the investor and business community (Cain, 2015). Institutional weaknesses such as inadequate investor protection, relaxed regulatory systems, poor contract enforcement, high levels of corruption in private and public sectors and unstable political institutions are critical elements in the quality of corporate governance (Adegbite, et al., 2012). The formation of a new and leaner cabinet by His Excellency, the President in November 2017 briefly rekindled hope and confidence, through the crafting of new policies, specifically the withdrawal of the indigenization policy on specific industries (RBZ, 2018) perceived to have a positive effect on corporate governance and firm performance.

According to (Masaka, 2012), trade sanctions imposed on Zimbabwe have mainly spoilt the economy by preventing the opening of credit lines to the country and have also affected the activities and operations of some critical government personnel, institutions, and business organizations that are key for the economic well-being of the country. Export competitiveness have crumbled under negative perceptions which has led to the shrinking of the country’s exports (RBZ, 2016).

The Reserve Bank of Zimbabwe, henceforth (RBZ) introduced the bond notes through depositors’ foreign currency accounts (Dube & Mkumbiri, 2014). In July 2018, RBZ temporarily froze disbursing US dollars to banks for onward withdrawal by individual customers (Sunday News, 2018). A special purpose vehicle, Zimbabwe Asset Management Corporation (Private) Limited, henceforth (ZAMCO) was created to clean up commercial banks’ balance sheets and to assist distressed borrowing business entities with a new lease of life (ICAZ, 2017). By 31 December 2016, ZAMCO had already acquired NPLs to the tune of $812.52 million (RBZ, 2016). Corporate governance is violated in that there is lack of adequate disclosure on Non-Performing Loans (NPLs) as they are taken off the banks’ financial statements. In Zimbabwe, there has been a late identification of failures in banks and this phenomenon increases fragility in the financial sector considering that the sector is the hub of financial activities (Dzingirai & Katuka, 2014). The banking sector in Zimbabwe has been so dynamic over the recent years. From the year 2001, the country witnessed the birth of financial institutions such as Kingdom Bank, Renaissance Merchant Bank, Royal Bank, Trust Bank, CFX Bank to mention but a few. However, six of the banks collapsed during the period under study. These banks are Trust Bank Limited in 2013, Interfin Bank Limited and Capital Bank (formerly ReNaissance Merchant Bank) in 2014 and AFRASIA Bank Zimbabwe Limited, Allied Bank and Tetrad Investment Bank (Tetrad) in 2015. (Chokuda, et al., 2017) concluded that corporate governance factors contributed significantly to the failure of banks and suggested that banks need to put more focus on corporate governance factors to avert more future failures. Apart from collapse of banks, loan portfolio performance of banks has not been satisfactory as the level of NPLs have been in excess of the RBZ benchmark of 5% a factor signaling danger. A lot of studies in corporate governance and firm performance have focused mainly on the manufacturing and other sectors with the exclusion of the financial sector, notably, (Hannifa and Hudaib, 2006, Mangena, et al.;2012) The current study focusses on this neglected sector in the assessment of the effect of corporate governance on performance of commercial banks in a turbulent economic and political environment.

Moreso, Extant studies in the corporate governance and firm performance area have mostly concentrated on the affluent developed nations (for instance, Gompers and Metrick, 2003; Bekiris and Doukakis, 2011; Felicio et al.; 2014; Drakos Bekiris, 2010; Schooley,Renner and Allen, 2010) a phenomenon seemingly peripheral to their developing and emerging politically and economically unstable counterparts lacking in advanced and progressively reviewed NCCG and NCGI. The studies addressing developing nations have mostly viewed corporate governance under an agency theory lens mainly focusing on the agency driven conflicts but ignoring the institutional national cultures obtaining in each of these developing and emerging economies and the inherent external pressures exerted on firms by such environments, (see Pamburai et al (2015) South Africa, Ehiokioya, 2009 Nigeria), with the exception of one Mangena and Chamisa, (2008) Zimbabwe (to my knowledge). Chamisa and Mangena (2008) is very profound in this current study which seeks to extend on Mangena’s findings but focusing on the banking sector and the effect of the now in existence NCCG in Zimbabwe.

2. Methodology

The objectives of a research determine the choice of the research design (Creswell, 2014). The current study’s objectives are mainly focused on establishing a relationship between corporate governance and financial performance of commercial banks hence the quantitative research method was employed. (Creswell, 2014) notes that, a research that examines the causes and effects relationship amongst variables (independent and dependent) is referred to as an explanatory research design hence the study adopted an explanatory design.

The target population for the study was all the 13 commercial banks in Zimbabwe (RBZ, 2018). The banks include , Bancabc bank Limited, Barclays Bank, CBZ Bank Limited ,Eco bank, FBC Bank Limited, Nedbank Zimbabwe Limited (formerly MBCA Bank Limited) ,Metbank Limited, NMB Bank Limited, Stanbic Bank Zimbabwe Limited, Standard Chartered Bank Zimbabwe Limited, Steward Bank Limited and ZB Bank. The commercial banks were selected for the study because they play a key role in financing other key sectors that include agriculture, mining and manufacturing. The justification of restricting attention to commercial banks i.e. focusing on a single industry helped to substantially reduce inter-industry heterogeneity. In his empirical study of banking firms, (Zhang, 2016) argued that industry-specific factors account for a large proportion of performance variability in a sample of firms, and may obscure the relation between board structure and firm performance.

Due to the challenges of getting financial and corporate governance data of some commercial banks, commercial banks that fully disclosed their corporate governance data on their websites were used as a sample. The study utilised a judgemental sampling technique based on availability of data. The five commercial banks were studied for a period of eight years from 2010 to 2017 to ensure that the results are not biased and to allow for employment of appropriate econometric methods to control for endogeneity as observed by (Zhang, 2016). The study period has been split into two distinct structural breaks; low political and economic volatility environment (2010-2013) and high political and economic volatility environment (2014-2017). This data panelling was also picked deliberately as periods before the Zimbabwean NCCG and the period after NCCG promulgation in Zimbabwe.

The selected commercial banks represent the top banks in Zimbabwe and are likely to possess greatest potential to attract and employ skilled and competent individuals in their Board of Directors henceforth (BODs). These banks also have good access to capital and other resources necessary not only for survival but also for improving their performance and competitive position.

The five commercial banks selected represent 5/13 (38%) of the target population of 13 commercial banks. (Creswell, 2014) argued that a sample size that exceeds 5% of the target population is enough to warranty the validity of the research findings. Therefore, the researcher is guaranteed of valid research findings.

1. 2.1. Econometric Model Specification

Estimation of a regression equation was done through the adoption of Classical Linear Regression Model (CLRM) panel data technique. Below is the model specification which was used for the study;

lnROE = α + β₁lnBODSZ + β₂lnBODIN + β₃lnACZ + β₄lnLEVR

Where;

ROE= Return on equity

BODSZ= Number of directors on the Board

BODIN = Percentage of Non- Executive directors on the Board

ACSZ = Number of directors on the Audit Committee

LEVR = Debt Structure (Leverage) - Debt / Total Assets

α= y-intercept

β = Coefficient

μ = the error term

Both liner and logarithmic specifications were experimented on but adopted the linear form because unlike logarithmic form, it gave superior performance in terms of explanatory power and general significance. The research employs Ordinary Least Squares approach. The use of OLS is due to the fact that it has the advantages such as consistency, unbiasedness, minimum variance and sufficiency and also reduces the error sum of square.

2.2. Tests for the Classical Linear Regression Model (CLRM) Assumptions

In the descriptive statistics part, the study shows the mean, standard deviation, minimum and maximum values of the dependent and explanatory variables including the number of observation for each variable during the period under consideration, that is from 2010-2017. However, this section provide test for the classical linear regression model (CLRM) assumptions such as normality, heteroscedasticity, autocorrelation and multicolinearity tests. The linearity of the parameter is assumed since the model applies linear ordinary least square (OLS). The objective of the model is to predict the strength and direction of association among the dependent and independent variables. Thus, in order to maintain the validity and robustness of the regression result of the research in CLRM, it is better to satisfy basic assumption CLRM.

2.2.1. Diagnostic Tests

This study will conduct panel data diagnostic tests that were aimed at detecting situations where the assumptions have been violated to produce robust regression results.

Multicollinearity Tests

Multicollinearity exists if the explanatory variables are highly correlated with each other. These strong interrelationships make it difficult to disentangle the individual effects of independent variables on the dependent variable. The VIF approach was used to detect the presence of severe multicollinearity where a zero order correlation coefficient is high if it is in excess of 0.8.

2.2.2. Unit Root Tests

The Augmented Dickey-Fuller (1981, ADF) test the null hypothesis that points to the existence of a unit root in panel data:

: δ = 0 (there is a unit root),

Against the alternative hypothesis that.

: δ <0 (that there is no unit root).

This null hypothesis would be rejected when δ is significantly negative. If the calculated value of ADF statistics is greater than the McKinnon’s critical values, then the null hypothesis would not be rejected and it can be concluded that the panel data is non-stationary or not integrated of order zero I (0). Failure to reject the null hypothesis would mean that differencing of the series is required. Unit root tests need to be done make sure that all series are integrated of the same order.

The hypotheses (for null hypothesis against alternative hypothesis respectively) to be tested is as follows

: =0 (the variable has a unit root or is non stationary)

: 0 (the variable is stationary or has no unit root)

Tests for the presence of the trend and the constant in the model are subsequently are done.

Decision Rule: Reject Null Hypothesis if p-value from E-VIEWS output is significant, i.e. p is less than 0.05 at 5% level of significance.

1. 2.2.3. Cointegration Test

Cointegration is used to test for the existence of a long-run equilibrium relationship between the variables. The cointergration test is conducted by running a unit root test on the error term. If the variables are cointegrated, that is the error term is stationary, it means that there is a long run relationship between the variables and that the model is rendered fit for prediction. The study will conduct the Johansen’s Cointegration test to establish the nature of the relationships between the variables in the long run. Johansen’s methodology takes its starting point in the vector autoregression (VAR) of order p given by;

Where y_t is an nx1 vector of variables that are integrated of order one – commonly denoted I(1) – and ε_t is an nx1 vector of innovations.

2.2.4. Testing for Autocorrelation

Autocorrelation (sometimes called serial correlation) occurs when one of the Gauss-Markov assumptions fails and the error terms are correlated. i.e. . This can be due to a variety of problems, but the main cause is when an important variable has been omitted from the regression. In the presence of autocorrelation, the estimator is no longer BLUE, as the estimator is not the best. In this case the t-statistics and other tests are no longer valid.

To test for first order autocorrelation, we use the Durbin-Watson (DW) d statistic. Given the following 1^st order process:

The d statistic is roughly: d = 2 - 2ρ , where ρ lies between +1 and -1. This statistic lies between 0 and 4.

When autocorrelation is present, Cochrane-Orcutt and Unrestricted models are for remedying autocorrelation as follows;

Given the following model, suffering from first order autocorrelation

Lag the first equation and multiply by ρ:

2.2.5. Normality Tests

Normality tests are used to determine if a data set is well-modelled by a normal distribution and to compute how likely it is for a random variable underlying the data set to be normally distributed. Testing for Normality, a fairly simple test that requires only the sample standard deviation and the data range. Based on the q statistic, which is the ‘studentized’ (meaning t distribution) range, or the range expressed in standard deviation units. It tests kurtosis

q = w/s

where q is the test statistic, w is the range of the data and s is the standard deviation.

The null and the alternative hypothesis of this tests are as following:

: The series in the data set are normally distributed

: The series in the data set are not normally distributed.

3. Statististical Results

3.1. Descriptive Statistics of the Data

Table 1 provides a summary of the descriptive statistics of the data used in the study after log transformation. After observing that the mean and median of each corresponding data series are close to each other, there is evidence that the variables being analysed closely follow the normal distribution, which is a critical attribute in the modelling of panel data. As widely used by various scholars (Coulibaly, 2015), log transformations are used to partially reduce data asymmetries due to the wide variations among the variables.

Table 1. Summary of Descriptive Statistics

Source: Secondary data computation using E-Views 8 (2018)

Table 1 shows the summary statistics of the dependent and independent variables. The return on equity has a mean of 0.15 with a standard deviation of 0.10. The highest value of the return on equity is 0.37 while its lowest value is -0.09. The board size has a mean of 11.23 with a standard deviation of 2.09. The highest value of the board size is 16 while its lowest value is 7. The highest value of board independence is 0.72 and the lowest value is 0.02. The mean of audit committee size is 3.98, with a standard deviation of 1.21. The mean of leverage ratio is 0.85 with a standard deviation of 0.05. The highest value of leverage ratio is 0.92 while its lowest value is 0.73.

Correlation Analysis

Table 2. Correlation Matrix

Source: Secondary Data Computation using E-Views 8 (2018)

The Table 2 clearly indicates that’s there is positive co-movement between return on equity with board size. The implication is that as the number of board members increased, ROE would also improve. The magnitude of the increase if 0.16 implying that a 1% increase in board size would result in a 0.16 positive change in ROE. Audit committee size also has a positive correlation with ROE. An increase in the number of members in the audit committee of banks result in an increase in ROE. The magnitude of the increase of ACSZ to performance is 0.08. Leverage had the highest impact on performance at a magnitude of 0.30. It had a positive co-movement with performance implying that the more leveraged a bank was, the more the ROE for the bank.

However, there is negative correlation between return on equity and board independence of -0.09. The implication was that boards with more independent directors produced less in terms of performance. Board independence, audit committee size and leverage ha co-movements of -0.23, 0.28 and -0.32 with board size respectively. Leverage has co-movement of 0.24 with independence and audit committee size.

Variables Trend Analysis

The overtime behaviour of the variables was checked so as institute consistency with the statistical findings coming out of the regression model. The following graphs clearly shows directional behaviour of the variables 2017-2017. The trend analysis was done for all the variables under study. This was done to give a picture of how the boards of the banks under study have evolved over the period of study. This helps to clearly analyze the trend so as to explain the likely causes of the changes in the performance of the banks under study.

Figure 1. Return on Equity

Source: Secondary Data Computation (2018)

Figure 1 above indicates shows a trend analysis of ROE for the 5 selected commercial banks over the period of the study. The general trend is that ROE rose for the period up to 2012 then declined sharply in 2013 with NMB’s performance taking a nosedive from 24.5% to a negative 9%. From the year 2013, performance of the banks began to improve slightly. Over the period, Stanbic bank outperformed the other banks, recording a maximum of 37% in 2012 and maintained the top position until 2016 when Barclays performed slightly above it. In 2010, Barclays was the worst performer recording a negative ROE of 4.1%, which improved significantly over the period through to 2017. The rest of the banks recorded moderate returns on equity that were increasing progressively over the period under study. The period of study was divided into two phases being 2010 to 2013, a phase regarded as having been politically and economically stable. This is the period where the best performance was recorded for the majority of banks. During the other phase 2014 to 2017, the banks managed to stabilize but did not perform as well as they had done in the first phase.

Figure 2. Number of Directors on the Board

Source: Secondary Data Computation Using E-Views 8 (2018)

Over the period 2010-2017, FBC bank had the biggest board with an average of 13 directors, followed by CBZ whose board size averaged 12 directors. FBC board size declined over the 2-year period 2017 to 2017 from 16 to 11 members. Barclays bank and Stanbic had the least constituted board in 2010 with Barclays remaining the bank with the least number of directors on their board over the period. For the period under study, the banks have generally maintained their boards stable with the outliers CBZ and Barclays changing their boards in the last 2 years.

Figure 3. Percentage of Non- Executive Directors on the Board

Source: Secondary Data Computation Using E-Views 8 (2018)

NMB bank has generally maintained a large proportion of Non-Executive directors over the whole period of study attaining the maximum of 91.7% in 2013.The proportion declined steadily until 2015 when the decline was steep with the board being constituted of 77.8% NEDs in 2017. In 2010, FBC bank had the lowest proportion of Non-Executive directors in their board and have maintained the least position as compared to the other banks. The general trend amongst the 5 banks is that the proportion was stable from 2010, then rose steeply in 2013. It then declined from 2013 to 2015with the exception of Barclays which rose gently from 62.5 % in 2012 ending at 90% in 2017.

Figure 4. Number of Directors on the Audit Committee

Source: Secondary Data Computation Using E-Views 8 (2018)

From the Figure 4 above, the majority of banks maintained a stable number of audit committee members. CBZ had the biggest size of audit committee in 2010 and have throughout the period reduced the number but maintained the top position as at the end of 2017. The minimum number of members on the audit committees of the banks have been persistently maintained at 3 over the period. Stanbic bank has over the period maintained the minimum of 3 before increasing the number to 4 in 2017. This implies that banks have managed to maintain the minimum required audit committee size according to the King 3 Report.

Figure 5. Leverage

Source: Secondary Data Computation Using E-Views 8 (2018)

From the graph above, it can be noted that there was no much changes on the levels of debt-assets proportions amongst all the banks. The trend has been stable over the period of study with FBC being the least leveraged.

Diagnostic Tests

Since, present study appears to be initial attempt to identify the links between corporate governance and financial performance of a bank with special emphasis on the relationship during the periods of high political and economic volatility in Zimbabwe, the researcher have empirically estimated whether a statistically significant relationship exists between corporate governance and performance of a bank measured by return on equity, in the long-run (2010-2013) as well as in the short-run (2014-2017), to enable adjustment of major structural changes.

Table 3. Unit-Root Estimation

Source: Secondary Data Computation Using E-Views 8 (2018)

The results in Table 3 show that the return on equity, board independence, board size, size of the audit committee and leverage are I(1). Both tests confirm the stationarity of variables at 1^st difference.

7. Granger Causality Test

After determining that the variables are cointegrated, an analysis of the causal links among the variables is tried out using the granger causality test. The F-statistics and the P-values are used in the test.

Table 4. The Results for Granger Causality Test

Source: Secondary data computation using E-Views 8 (2018)

According to table 4, the null hypothesis that ROE did not granger cause BODSZ was rejected. The implication was that the past value of ROE did not contribute to the forecasting of corporate governance levels. Furthermore, ROE did not granger-cause BODIN as the test failed to reject the null hypothesis at the 95% confidence level. BODIN did not granger-cause ROE and therefore no linear relation existed between ROE and BODIN. BODSZ did not granger cause ROE and therefore there was no linear relationship between BODSZ and ROE in the context of Zimbabwe for the period spanning from 2010 to 2017. Finally, no linear relation existed between ROE and ACSZ and ROE did not granger cause ACSZ, test failed to reject the null hypothesis. The opposite held true as the latter did not granger cause the former.

2. Bank Performance and Corporate Governance During Periods of Low Political Volatility 2010-2013

To observe the partial impact of corporate governance on Bank performance in the period of low political and economic volatility (2010-2013), the study turned to ARDL for long run relationships as mentioned in Table 5. The main assumption of ARDL is that included variables in model are having co-integrating order I(0) or I(1) or mutually. This lends support for the implementation of bounds testing, which is a three step procedure; in the first step we selected lag order on the basis of SBC because computation of F-statistics for co-Integration is very much sensitive with lag length, so lag order of 2 is selected on lowest value of SBC. The total number of regressions estimated following the ARDL method in equation 1 is 2187. Given the existence of a long run relationship, in the next we used the ARDL co-Integration method to estimate the parameters of equation (1) with a maximum order of 2 to minimize the loss of degrees of freedom.

The results of bounds testing approach for long run relationship represent that the calculated F- statistic is 4.68(see Table 5) which are higher than the upper level of bounds critical value of 4.61 and lower bounds value of 3.88, implying that the null hypothesis of no co-integration cannot be accepted indicating that there is indeed a co-integration relationship among the variables at 5% level of significance.

Table 5. Lag Length and ARDL Results

ource: Secondary data computation using E-Views 8 (2018)

An analysis of the sensitivity of data used was conducted and the results of these tests were shown at in table 5. Sensitivity analysis done confirmed that there was no serial correlation in the data. Confirmation that the model was properly specified, normal distribution of the regressors and the absence of conditional heteroscedasticity in the residuals distribution was done using sensitivity analysis. The adopted model in 4.6 showed positive and significant association between corporate governance and enhancement of bank performance in Zimbabwe. This demonstrated that corporate governance was crucial in contributing towards bank performance through different channels. The activities of banks are also improved through casual channels as demonstrated in literature by improvements in corporate governance principles and banks’ levels of leverage. Where there was instability in corporate governance practices, there was weakening of bank’s growth which directly impacted performance negatively.

Table 6. Estimated Long. Run. Coefficients. ARDL. Approach-Period of Low Political Volatility (2010-2013)

Source: Secondary data computation using E-Views 8 (2018)

From the above Table 6, the following regression model was deduced;

0.017

Board size, board independence and size of the audit committee have positive significant relationship with return on equity. However, leverage had positive insignificant impact on the performance of a bank. This indicates that corporate governance development stimulates the bank performance through spill-over effects, proper risk management and adherence to proper banking practices. The researcher also discovered that banking performance improve the long run growth. The ADL-ELM version was then applied to examine the dynamic relationships in the short run. The short run model formulated for the investigation of the impact of corporate governance was as follows;

+

The ECM results are reported in table 4.6. Indication from the results are that corporate governance results in enhanced performance and is positive and significant at significant levels of 10% and 5% and the impact of the lag of differenced terms of leverage had positive insignificant association with bank performance but enhanced the banking development in future periods. Board independence positively and significantly at 5% level of significance influenced growth. The speed of adjustment of restoration of equilibrium is measured by the error correction term CE_t-1. The correction error had a negative sign and was found to be statistically significant at a level of 1% which implied that attainment of a long run equilibrium was possible. Over each year, the coefficient of CE(-1) was found to be 80.1%. The AIC and SBC was used in the determination of the lag length of the short run model.

Table 7. ECM Short Run Dynamic Version- Economic and politically unstable environment (2014-2017)

Source: Secondary data computation using E-Views 8 (2018)

From the Table 7 above the following model was deduced

+

In the short run (the political and economic volatile period), board size, board independence, size of audit committee and leverage all have positive significant impact on the level of bank performance as measured by return on equity. This is in line with a study carried out by (Sheik & Wang, 2012) who found a positive significant relationship between board size and bank performance. (Gondrige, et al., 2012) also produce the same results in their empirical study in Brazil. Contrary to the current study results, (Zabri, et al.; 2015, Shukeri, et al.; 2012, Ongore, et al.; 2015) found a negative relationship between board size and performance. The difference in the results produced could be attributed to the different operating environments. The Zimbabwean environment, which is politically and economically unstable requires large boards so as to enhance bank performance. Large boards consolidate skills and ideas to drive banks towards better performance as indicated in literature.

The results produced by the current study on board independence are the same as those produced by (Nawafly & Alarussi, 2016) in Malaysia. Different results have been produced by (Bansal & Sharma, 2016, Das, 2017) who submitted a negative relationship between board independence and performance. The size of audit committee was found to be positively related to performance during the current study. Other researchers who produced the same results are (Arslan, et al.; Bouaziz, 2012). However, (Mendez, et al., 2017) produced different results when they carried out their research in Spain. It should be noted that the difference in environments could have led to the submission of different results. The other reason could be that other countries where these studies were carried out are developed countries whereas Zimbabwe is still developing. Data integrity could also have influenced the difference in results that were submitted. In the Zimbabwean context, data may not have integrity as much as it does in other developed countries.

Both short run and long run models have R² > 50%, that is 78.39% and 71.73% respectively, indicating that with the data provided in this research both short run and long run models are robust enough to be adopted as the best predictors of return on equity. Based on the these provided results in table 6 and table 7, during periods of high political volatility, corporate governance plays a pivotal role in stabilizing a bank than during times when political risk is too low.

This study investigated the impact of corporate governance on bank performance in an economic and political turbulent environment, specifically Zimbabwe for the period 2010 to 2017. Unit root presence in the variables under study were inspected through the use of Augmented Dickey Fuller test. Panel data on the variables was used as a basis of the test. One unique cointergration factor existed according to the test results. This implied that one long relationship which was unique existed amongst the variables.

An examination of casual relationship was then tested using the Granger causality test among the considered series. According to the results, corporate governance and bank performance had no causal relationship. The null hypothesis, ‘Corporate governance has no impact on bank performance in a turbulent economic and political environment’ could not be rejected as a result of this test. Positive effects of corporate governance were guaranteed as indicated in the literature. The ability of Zimbabwean banks to meet some of the conditions required to ensure success through corporate governance embracement as noted in literature could have caused a positive effect of corporate governance on bank performance.

The aim of this study was to establish the effect of corporate governance on the financial performance of commercial banks in Zimbabwe, 2010-2017 using structural break approach to take into account political volatility. In this study, the researcher adopted an exploratory research design which assisted to investigate the relationship between corporate governance and the financial performance of commercial banks in Zimbabwe. The population of the study was 13 commercial banks, but a sample size of 5 banks listed on ZSE was used. The data was gathered exclusively by analyzing the annual reports of commercial banks from 2010 to 2017 and the data was analyzed using Eviews 08.

The descriptive statistics revealed that the average ROE for the five commercial banks for the eight years is 15% suggesting that there was an average profit. The Pearson correlation analysis revealed a positive linear correlation between the return on equity and the independent variables: Board size, board composition, sub-committees and leverage. The board size, board composition, board sub-committees and leverage are significantly related to the financial performance of the eight commercial banks.

The researchers found that there is a significant connection between board size, proportion of non-executive directors, size audit committee and leverage, with financial performance of commercial banks measured by return on equity. This can be attributed to the fact that the bank’s business relies heavily on trust that clients have in the management of the bank and the more transparent they are, the more the disclosures the more trust they earn from their clients and the better a bank’s management manages the risk, translates into growth and better financial performance. It was also found out that political risk has more negative impact during on bank performance and it requires a more proactive board to manage the bank during times of political upheavals.

The study findings on size of audit committee were that the members of the board make known if they have any interest in any matter concerning the company and financial statements of the company are audited by competent auditors among the responses were positive. Further the study found that the information about board and top management pay package is available to all shareholders and other stakeholders. Information about board member’s qualification and the retention rates of the employees is made available for organization boards’ members. Articles of association, board charters, committee structures and charters are all disclosed to board members as many respondents indicated which also promotes organization transparency in all dimensions.

On the Board’s operation, board members make informed decisions and exercise a lot of care since majority of respondents strongly agreed to this. All shareholders are treated fairly by applying high ethical standards. The board takes into consideration the interests of all shareholders. The board monitors implementation of major plans of action and corporate performance. It was also found that, it is the board’s mandate to oversee major capital expenditures, acquisitions, divestiture and debt structures, and the company carries out performance review of individual boards members. Internal auditor has authority to contact to the board directly as the board oversees the succession plan.

Based on the these provided results in table 4.6 and table 4.7, during periods of high political volatility, corporate governance plays a pivotal role in stabilizing a bank than during times when political risk is too low.

6. Conclusion

Corporate governance improves a firm’s corporate competitiveness and positively impacts its profitability level when the political risk is very low as noted during the period 2009-2013. However, the results were different during times of high political risk, when corporate governance must change from being reactive to being proactive, managing political risk and political relations, absorbing political shocks. The study reveals that during times of high political volatility, the board of directors could try to make profit maximization the main goal in order to drive the bank towards making profits as the chances of making losses will be very high. This comes from the fact that the board is expected to manage all the bank’s forms of risks, through both the risk management committee and the audit committee.

The study scrutinized the effect of corporate governance on the performance of commercial banks quoted on the ZSE in Zimbabwe. It is evident that corporate governance performs a major function in the overall growth and success of banks. The results from the investigation indicate that the rights of shareholders, transparency and disclosure and board operation enhance performance and eventually improve shareholders’ value.

The results of the research give a strong support to the idea that good governance framework is crucial in the financial sector as it positively influences firm performance. The findings of this study advocate and support good corporate governance practices in commercial banks as a tool of curbing bank collapsing. This yields an overall effect of promoting economic growth and development of a country since the financial sector plays a key role in the nation’s GDP.

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