Características y delimitación del universo

The results of control variables are presented in Tables 9 and 10. From These tables, we find that LNTA, which measures bank size in terms of total asset is insignificant and positively correlated with both ROA and ROE. The positive impact of bank size on performance indicates that the economies of scale enjoyed by larger banks enable them to reduce cost and make more profit. A reduction in cost help the banks to improve their performance. The positive correlation between bank size and performance can also mean that a rise in total asset absorbs the rise in net income. Moreover, the positive coefficient could also suggest that the bigger banks in Africa get benefits through diversification of the activities of their loan portfolios which leads to higher bank performance. However, the banks in Africa are not able to utilise the advantages that bigger bank size brings to make profit. Therefore, the positive effect of size on performance is insignificant. The insignificant nature of this result may come from measurement error or multicollinearity. Although this issue were resolved before the analyses, issues like multicollinearity might not be removed completely. This finding is consistent with the finding of Bougatef (2017) who finds insignificant association between bank size and bank performance in Tunisia. However, the finding is inconsistent with the findings of prior literature which report a significant positive correlation between bank size and performance (e.g. Sakawa and Watanabel, 2018; Rahman et al., 2015; Tan et al., 2017; Shawtari, 2018; Hasanov et al., 2018). The insignificant positive relationship between bank size and performance is also not consistent with the findings of Tan (2016), Al-

Shammari (2013), Dietrich and Wanzenried (2011), Elyasiani and Zhang (2015) and Doumpos et al (2015) who report significant negative correlation between bank size and performance. The inconsistence of this result with other empirical results may come from differences in sample size and study time frame.

Equity to asset ratio (EQTA), which measures bank capitalisation is significant and positively correlated with ROA at 1% level of significance but insignificant and negatively correlated with ROE. The inconsistent result of ROA and ROE may come from the fact, that the behaviour of equity and debt holders (ROA) may be different from the behaviour of equity holders (ROE), hence the results of ROA and ROE can be different. For instance, debt and equity holders (ROA) may accept certain level of losses whiles equity holders (ROE) may not accept any losses at all, they only demand their returns from the bank whether the bank incurs loss or makes profit. The positive correlation between equity to asset ratio and bank performance implies that banks with higher degree of capitalisation perform better in Africa. The findings can also be explained by the fact that well capitalised banks in Africa can change their funds to higher income earnings to make them more profitable. The finding supports the theoretical argument by Djalilov and Piesse (2016) and Athanasoglou et al., (2008) who argue that, the ratio of equity to total asset is expected to have positive impact on bank performance because it represents the amount of available funds to back operations of the bank, and for that matter serves as safety net in case of adverse events, which could increase bank performance. This finding is in line with the findings of some past empirical findings (e.g. Bougatef, 2017; Djalilov and Piesse, 2016; Hasanov et al., 2018). However, this finding is not in line with the negative correlation between equity to asset ratio and bank performance recorded by prior empirical literature (e.g. Dietrich and Wanzenried, 2011). The differences in the findings may be due to different time frame of the studies and different ways in which the variables were measured.

Contrary, the negative correlation between equity to assets ratio and bank performance suggests that less capitalised banks are able to increase their profitability compared to a well-capitalised banks. It also suggests that high capital protection is penalised with low profit in Africa, but this is not significant in the case of Africa, which may be due to measurement error and extreme values within the data.

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Loans to asset ratio (NLTA), which assesses the liquidity of banks, is highly significant and negative related to both ROA and ROE at 5% and 1% significance levels respectively. This indicates that when the ratio of loans to assets decreases, banks in Africa have enough liquidity to cater for any unforeseen fund requirement. This gives confidence to their depositors to deposit more funds. When more funds are deposited, the banks get opportunity to invest some of the deposits, which help the banks to earn more profit. The negative coefficient on net loans to assets also suggests that African banks have the ability to manage, control and monitor their loans very efficiently, they do not have a record of more bad loans, and subsequently reduce cost leading to higher bank performance. The findings are not in line with the findings of Daly and Frikha (2017), Dong et al., (2017), Mollah and Zaman (2015) who document a positive relationship between net loans to assets ratio and bank performance. This may be due to differences in the study time frame and differences in measuring the variables.

Cost to income ratio (COST) is found to be significant and negatively associated with ROA and ROE at 1% level of significance. The result indicates that banks with low cost-to-income ratio perform better in Africa than those with high cost-to-income ratio. The negative coefficients on ROA and ROE imply that banks in Africa have good management team who are experts and skilled in managing their operations efficiently and for that matter making good profit. This findings lend some support to the theoretical argument which states that, the higher the ratio of cost-to-income ratio the less efficiency of the management, which could reduce bank performance and vice versa (see for example, Rahman et al, 2015). The significant negative association between cost to income ratio and bank performance is in line with the findings of some previous empirical studies (e.g. Rahman, 2015; Syafri, 2012; Dietrich and Wanzenried, 2011; Goddard, 2013).

We find that GDP (LNGDP) has significant and positive impact on both ROA and ROE. The higher GDP growth which is positively related to bank performance indicates that higher growth causes a higher demand for lending which ultimately leads to higher bank profitability. On the other hand, this result means that there is a high probability of higher demand for lending during a period of cyclical upswing which may result to higher bank performance. The positive impact of GDP on bank performance supports the theoretical statement by Boateng et al., (2015) who suggest that higher GDP growth results to a higher demand which encourages firms

to borrow more to produce more goods and services to meet the higher demand for goods and, subsequently increase banks performance. The significant and positive impact of GDP on bank performance lend empirical support to some previous empirical findings of Albertazzi and Gambacorta (2009), Shawtari (2018). Contrary, this findings do not lend empirical support to Boateng et al., (2015), Safrali and Gumus (2010), Rashid and Jabeen (2016) who record significant negative impact of GDP on bank performance. In addition, the findings do not lend empirical support to the findings of Mollah et al (2017) and Ariyadasa (2017) who document no significant impact of GDP on bank performance. The inconsistent of this result and other previous empirical results may come from differences in measuring the variables and differences in sample size.

In terms of control of corruption (COR), there is significant and positive relationship between COR and bank performance based on both ROA and ROE at 5% significant levels. The positive sign means an increase in Corruption Perception Index (CPI), which is a reduction in corruption. This means that when Corruption Perception Index (CPI) increases (a reduction in corruption), banks performance significantly increases. The result shows that an increase in corruption within the institutions including banks in Africa is not good for improvement of performance of banks in Africa. Therefore, a reduction in corruption will help improve the performance of African banks. The result is consistent with Bougatef (2017) and contrary to Aburime (2009) and Arshad and Rizvi (2013) who find a significant negative relationship between corruption and bank performance.

For the impact of financial crisis, we find insignificant and positive correlation between CRISIS and bank performance based on ROA but significant and positive correlation between CRISIS and bank performance based on ROE at 1% significance level. The insignificant result of ROA may be due to measurement error, multicollinearity and extreme values. The positive coefficient on financial crisis may indicate that, the crisis hit more in the developed countries with a very little or no impact on African countries. As a result, the banks in Africa were still able to embark on their business activities to make profit during the crisis period.

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6.2 Empirical result of bank risk and bank performance using LLRGL as