Sistemas y operadores de cierre en pre ´ordenes difusos

This subsection of the research provides detailed information on the descriptive statistics on all the variables used for achieving the research aims and objectives. The descriptive statistics is shown in table 8 below.

Table 8: Summary descriptive statistics of all variables.

Variables Mea n Media n Std. Dev. Minimu m Maximu m Skewne ss Kurtos is Observatio ns Panel A: Performan ce variables ROA 1.77 1.71 2.74 -6.91 9.30 -0.35 5.72 7439 ROE 13.9 6 14.03 19.5 4 -49.36 60.33 -0.65 5.33 7439 Panel B: Risk variables LLPNR 21.4 1 12.43 29.5 5 -16.94 134.88 2.14 8.06 5990 LLRGL 6.65 4.17 7.02 0.25 31.50 1.93 6.59 5743

121 Panel C: Corp. governanc e variables BSIZE 10.4 9 10.00 3.49 2.00 23.00 0.72 3.24 2027 INDEP 4.89 4.5 3.18 0.00 18 0.82 3.31 1020 DUAL 0.16 0 0.37 0.00 1.00 1.83 4.33 2032 FEMALE 1.49 1 1.45 0.00 9 1.14 4.64 2013 MEETING S 6.26 5 4.20 0.00 38.00 3.59 20.94 1447 Panel D: Control Variables LNTA 3.56 3.17 1.71 -1.70 9.65 0.28 2.92 7515 COST 62.6 7 58.99 28.3 8 14.46 159.21 1.23 5.41 6815 EQTA 16.3 3 11.76 14.5 1 2.70 72.91 2.45 9.10 7498 NLTA 47.6 0 48.85 21.3 9 2.77 90.01 -0.16 2.50 7243 LNGDP 6.74 7.32 2.46 -0.81 11.15 -0.24 2.16 10773 COR 35.3 9 32.70 22.2 2 0.48 85.85 0.25 1.87 10141 CRISIS7_ 8 0.12 0 0.32 0 1 2.37 6.63 10795

Notes: ROA represents return on asset, ROE represents return on equity, LLPNR denotes loan loss provision/net interest revenue, LLRGL represents loan loss reserve/gross loan, BSIZE represents board size of the bank, INDEP denotes percentage of independent directors, DUAL represents role duality, FEMALE denotes the percentage of female directors on bank board, MEETINGS represents the number of board meetings per year, LNTA denotes the size of the bank, COST denotes cost to income ratio, EQTA denotes equity/total asset, NLTA represents net loans/total assets, LNGDP

represents Gross Domestic product, COR denotes corruption, CRISIS7_8 represents 2007/2008 financial crisis

Panel A of table 8 shows that the first measure of performance, ROA ranges from a minimum of -6.91% to a maximum of 9.30%, with an average of 1.77%. The second performance measure, ROE on the other hand has a minimum value -49.36% and a maximum of 60.33% with an average value of 13.96%. ROA and ROE have a

standard deviation of 2.74% and 19.54% respectively. The negative signs on the minimum values of ROA and ROE means that the shareholders of some of the African banks are losing instead of gaining, because those banks are not making profit. However, since the mean values are positive, it can be concluded, that on average the banks in Africa are making profit. Panel B shows the two risk measures, Loan loss provision to net interest revenue (LPNR) and Loan Loss Reserve to Gross Loan (LLRGL). The minimum values of LPNR and LLRGL are -16.94 and 0.25 respectively and their maximum values are 134.88 and 31.50 respectively. While LLPNR has an average value of 21.41 with a standard deviation of 29.55, LLPGL has average value of 6.65% and a standard deviation of 7.02%.

Panel C of table 8 presents all the independent corporate governance variables. The Board size of African banks ranges from a minimum of 2 and a maximum of 23. On average the board size of African banks is 10.49 and a median number of 10. This value is within the board size (i.e. between 8 and 10) recommended by Lipton and Lorsch (1992), for efficiency of a board. Jensen (1993) also argue that any board bigger than seven to eight members is not beneficial to the effective function of the board due to high chances for animosity and retribution between the board members. The standard deviation of the board size is 3.49. The number of independent directors on African bank board ranges from a minimum of 0 to a maximum of 18 with a standard deviation of 25.30. The average number of independent directors on African bank board is about 4.89. This value portrays that the number of independent directors who suppose to scrutinise the executives’ decision during board meetings is less than the executive directors. This can pose a problem for the independent non -executive directors in scrutinising the executive decisions when a particular decision has to go on voting.

The next corporate governance variable is role duality which is a dummy variable with minimum number of 0 and a maximum number of 1, with a mean value of 0.16 and a standard deviation of 0.37. This means, on average the 16% of the sample banks have a combined role of CEO/Chairman position. The next variable to DUAL on the table is female directors on African boards with a minimum value of 0% and a maximum value of 9. The number of female directors has an average value of 1.49 and standard deviation of 1.45. This means the average number of female directors on the banks board is only 1.49 which is very small number compare to average board size of 10.49. The last but not the least independent corporate

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governance variable on the table is board meetings. The board meeting has a minimum value of 0 and a maximum value of 38 with a standard deviation of 4.20. The average number of board meetings which is held by African banks within a year is around 6 (6.26).

Apart from the independent variables, there are other factors which can also affect bank risk and bank performance in Africa. As a result, we control for a number of these factors. Panel D of table 8 shows all the control variables used in this study. The first control variable is the bank size which is the natural log of the total assets of the banks. The minimum banks size is -1.70 and the maximum is 9.65 with a standard deviation of 1.71. The mean value of total asset (LNTA) of the African banks is 3.56. The second control variable is cost-to income ratio. Cost-to income ratio has a minimum value of 14.46 and a maximum value of 159.21 with a standard deviation of 28.38. The mean value of cost-to-income ratio is 62.67%. The lower the value of cost to income ratio the higher the efficiency of the bank. Equity/total asset is the third control variable. 2.70% represents the minimum value while 72.91% represents the maximum value and has a standard deviation of 14.51. It has a mean or average value of 16.33 %. The fourth control variable is net loan/total asset. This ratio is used to assess the liquidity of a bank. The banks have a minimum net loan/total asset of 2.77% and a maximum value of 90.01% with a standard deviation of 21.39. The average net loans to total asset ratio is 47.60%. If this ratio is very high it implies that it may not be possible for the bank to have enough liquidity in the event of unforeseen fund requirements.

GDP is the fifth control variable. The minimum GDP recorded from the 48 countries selected for this study is -0.81 and a maximum of 11.15 with a standard deviation of 2.46. The average GDP of all the countries is 6.74. The sixth control variable is corruption. A high number means very clean while a low number means very corrupt. The minimum corruption figure is as low as 0.85 and a maximum of 85.85 with a standard deviation of 22.22. The average corruption value in the 48 countries selected for this study is 35.39. This value suggest that corruption is very prevalent in Africa which can affect their bank risk and performance. Finally, financial crisis of 2007/2008 is a dummy variable with a minimum number of 0 and a maximum number of 1. Financial crisis has a mean of 0.12 and a standard deviation of 0.32.

5.4 Chapter summary

This chapter has focused on research design and methodology. The chapter first describe the sample selection and sources of data. In this regard, all the banks were selected from BankScope database. The selected banks come from 48 countries in Africa and from different bank specialisation and the majority of the sample banks are commercial banks. The data of the banks specific information are obtained from BankScope and Orbis bank focus databases provided by Bereau van Dijk. The data on the internal corporate governance variables were obtained from the annual reports of the sampled banks. These annual reports were downloaded direct from the website of the sampled banks. However, there are corporate governance information of some few banks which were obtained from Boardex database. Corruption and GDP data were obtained from the World Bank website.

The sample and sample selection criteria have been explained in this chapter. The study cover a seventeen year period from 2000 to 2017. The study uses a panel data analysis and 635 banks are used as the final sample for the study. The data on these banks have been used to analyse and test the relationship between bank risk and performance, bank risk and corporate governance, corporate governance and bank performance, and the moderating effect of corporate governance on the relationship between bank risk and performance. All the variables and how they are measured have been explained in this chapter in addition to the justification for control variables. One of the main things this chapter focused is the OLS assumptions. Under this, the various OLS assumptions that must be met before the actual analysis is carried out have been discussed. Finally, the chapter presented and discussed the summary statistics of all the variables used in this study.

125 CHAPTER SIX

EMPIRICAL RESULTS OF THE RELATIONSHIP BETWEEN BANK RISK AND BANK PERFORMANCE

6 Introduction

The aim of this section of the research is to investigate the relationship between bank risk and performance. In order words, the main research aim is to find out the impact of bank risk on the performance of African banks. As mentioned earlier, we follow previous studies (e.g. Tan, 2016) and use GMM as our main statistical model and OLS, fixed effect and 2SLS for our robustness analyses. GMM is used as our main estimator because of the number of advantages which are derived from such technique including resolving the problems of endogeneity, unobserved heterogeneity, autocorrelation and profit persistence, which other techniques may not be able to resolve (see for example, Tan, 2016). We use two bank risk measures in our analyses, Loan Loss Provision to Net Interest Revenue (LLPNR) and Loan Loss Reserve to Gross Loan (LLRGL); and two bank performance measures, Return on Assets (ROA) and Return on Equity (ROE). Discussions and robustness analyses which test the relationship between bank risk and performance are presented in this section. This section relates to hypothesis one.

6.1. Empirical result of bank risk and bank performance using LLPNR as