Descriptive statistics for the annual panel data

In this section, the summary statistics of the variables used in the estimations for the entire sample of the banks were considered in this research. Eight liquidity measures were used in this study, and using pooled estimations, the descriptive statistics for the liquidity measures are presented in Table 6.1.

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Table 6.1: Summary statistics for liquidity variables in the pooled estimation model

Variable Obs Mean SD Minimum–Maximum

L1 132 0.91 0.12 0.28–0.99 L2 132 1.42 0.31 0.82–2.74 L3 132 0.75 0.12 0.24–0.92 L4 132 1.17 0.26 0.65–2.30 LCR 132 7.32 156.16 -313.15 – 1733.28 NSFR 132 1.04 0.23 0.86–2.52 BLMI 132 0.15 0.11 0.09–0.47 ALMI 132 0.16 0.05 0.06– 0.21

Notes: Obs = Number of observations; SD = Standard deviation

Source: Author’s computation

From the summary of descriptive statistics in Table 6.1, the total observations for each liquidity (dependent) variable were 132. The descriptive statistics were drawn from the calculated standard liquidity measures (L1, L2, L3, & L4), the Basel III liquidity measures (LCR & NSFR), and the MLMI measures (BLMI & ALMI).

The data showed that the average liquid assets to total assets ratio was close to 1, an indication that the greater portion of a bank’s balance sheet is made up of liquid assets. The mean for the L1 liquidity measure was 0.91 for the period under review, and the SD was 0.12. The minimum liquid assets to total ratio was 0.28, while the maximum was 0.99. This shows that some of the banks can hold as little as 28% of their balance sheet in the form of liquid assets while on the other extreme end, banks could have 99% of their assets as liquid.

With regard to liquid assets to deposits plus short-term borrowings ratio, it was observed that the average was 1.42, and the SD was 0.31. On average, banks keep a higher level of liquid assets as compared to current liabilities. As the ratio is above 1, this was an indication that banks generally will be able to pay for their obligations as they fall due. Therefore, it was concluded that banks in South Africa, banks are minimally vulnerable to changes of shocks in different forms of funding. The minimum for the L2 liquidity measure was 0.82 while the maximum was 2.73. The lowest ratio of 0.82 shows that, at the time

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of this research, banks were prepared to take the risk of keeping fewer liquid assets relative to short-term liabilities probably because in time of shocks they may have a better borrowing capacity and thereby have to rely on interbank or open market operation borrowings.

The descriptive statistics indicated that, for the period under review, the mean of loans to total assets ratio was 0.75. Banks on average hold 75% of their assets in the form of loans. This is expected in the banking sector since loan issuance is the core business of commercial banks. The SD for L3 was 0.12, the minimum ratio was 0.24 and the maximum standing was 0.92. There was a significant difference between the minimum and the maximum values and an indication that banks followed different business models where other banks could afford to loan out almost 92% of their assets while other had to be content with 24%. Since the loans to total assets ratio showed the proportion of loans relative to total assets, this indicated the portion of assets of the bank that were tied up in illiquid loan assets, and the lower the ratio the more attractive the bank is with regard to this liquidity measure.

The loans to customers and short-term funding ratio indicated in general the proportion of banks’ illiquid assets to liquid liabilities. The mean of 1.17 indicated the South African banks on average could afford to fund the illiquid loans with short-term liquid liabilities. Kosmidou (2008) argues that the higher the proportion of loans relative to short-term funding, the more illiquid the bank is and therefore the higher its vulnerability to liquidity shocks.

The averages LCR and NSRF for the period under review were 7.32 and 1.04, respectively. The average LCR ratio for the banks showed that banks held a huge portion of high-quality liquidity assets even when the funding gap was anticipated to be positive. However, some banks were risk-averse as they held more than 333% HQLA when they expect a negative gap in their funding structures. On the other hand, banks may hoard a huge volume of high-quality assets even when they look forward to a favourable funding position.

The average BLMI as a ratio of total assets of the bank was 0.15 and as expected was very close the ALMI ratio, which was 0.16. The liquidity mismatch index is an index that

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captures the funding and assets liquidity of the bank. The LMI measures the mismatch between the market liquidity of assets and the funding liquidity of liabilities (Bai et al., 2014). The higher the ratio the healthier is the bank and vice versa. According to Brunnermeier et al. (2013), the LMI is a liquidity measure that is important as a key response indicator as it can help in detecting the build-up of systemic risk before crisis. The variance for BLMI is almost four times that that for the ALMI, an indication of a well- diversified portfolio when it comes to ALMI.

The liquidity measures discussed here were then regressed against the following set of independent variables:

 the capital ratio (CR) is measured by equity as a percentage of total assets;

 deposits (Dep) are defined as total retail deposits over total assets;

 size is the natural logarithm of total assets of the bank;

 loan growth (LG) is the expansion or contraction of a bank’s loan portfolio;

 non-performing loans (NPL) are loans that are outstanding both in principal and interest for a long time contrary to the terms and conditions in the loan contract;

 EFD is the ratio of external funding to total liabilities,

 economic growth measured by GDP is the growth rate of the real domestic product;

 interest rate is represented by the interbank lending rate(ILR);

 inflation, i.e. the consumer price index (CPI) is the increase in the general price of goods and services, over a period of time, in an economy;

 profits (ROA) are calculated as the operating profit divided by total assets; and

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Table 6.2: Summary statistics for independent variables in the pooled estimation model

Variable Obs Mean SD Minimum–Maximum

CR 132 0.15 0.12 0.04–0.64 Dep 132 0.66 0.14 0.32–0.90 SIZE 132 17.19 2.59 12.94–20.96 LG 132 1.19 0.23 0.65–2.01 NPL 132 -0.01 0.03 -0.16–0.01 EFD 132 0.82 0.12 0.48–0.99 GDP 132 0.03 0.02 -0.02 –0.06 IBLR 132 0.07 0.02 0.05–0.11 FC 132 -0.04 0.03 -0.18– -0.00 CPI 132 0.06 0.02 0.03–0.12 ROA 132 0.03 0.03 0.00–0.19

Notes: Obs = Number of observations; SD = Standard deviation

Source: Author’s computation

In this section, we discuss descriptive statistics for few variables as most of the variables here are presented in ratio format and may not provide meaningful information. A summary statistics for independent variables in Table 6.2 revealed that South African banks on average had a capital ratio of 14.96% at the time of this research. This shows that the banking sector was adequately capitalised over the period of investigation. The statistics also indicate that, over the period of investigation, there were banks that were poorly capitalised as the minimum of 3.72% indicates. However, most of the capital ratio of the banks was around the mean as the SD was 11.91%. From Table 6.2, it is clear that the bank loans in South Africa on average grew by 119% from 2005 to 2015. This is significant growth, which is in line with the increase in bank size as indicated by growth in asset base. The South African economy grew by 2.88% on average over the period between 2005 and 2015 while the inflation rate was 5.9% on average over the same period. Bank performance as measured by ROA was lower than the rate at which prices were increasing. Bank ROA were 3% on average although some of the banks recorded as high as 19.21% and others as low as 0.00%.

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The standard, Basel III and MLMI liquidity measures, were regressed against the regressors presented in Table 6.2. The next section discusses the construction of the new liquidity measures, namely the BLMI and the ALMI.