Financial and Banking Stability Studies

Literature centred on banking stability indicates that numerous factors determine the soundness of banking systems. Below is a review of literature on bank stability and the various factors or elements that seem to derail financial stability and economic growth. Jokipii & Monnin (2013) explored the relationship between banking sector stability and the consequent evolution of real output growth and inflation in a sample consisting of 521 banks covering 18 OECD countries. Their study sought to capture the extent of stability by estimating the distance-to-default for the various banks involved in the sample. The adopted VAR model showed that banking sector stability is significant for GDP growth. Jokipii & Monnin also suggested that periods of stability are on the whole followed by an increase in real output growth, whereas instability translates to periods of reduced growth. More so, they opined that a stable banking sector reduces uncertainty in real output growth.

In relation to the recent global financial crisis, a host of scholars in addition to the various other causes of the crisis blamed the use of derivatives as one of the main sources. Keffala, (2015) investigated whether the use of derivative instruments was responsible for the magnification of the global financial crisis. Keffala measured the effect of the use of derivatives on the stability of banks from emerging countries within the period of 2003 – 2011. The study employed the use Generalised Methods of Movements (GMM) estimator

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technique and made use of the Z-score as the dependent variable. The results of the study showed that forwards and swaps are not disruptive factors, whereas futures and to a large extent options can contribute to bank instability in emerging countries. Keffala (2015) concluded that options and futures, and not forwards and swaps should be considered risky and partly responsible for the amplification of the global financial crisis.

Additionally, given the various takeovers and purchase assumptions agreements that ensued in most banking systems around the world in recent times, especially after the global financial crisis, Gomez (2015) examined the effect of failed banks takeovers on financial stability. Gomez presented two opposite views. First, Gomez (2015) asserted that incumbent takeover might enhance financial stability due to the incentive to be solvent to benefit from the failure of competitors. Secondly, the incumbent takeover of failed banks may derail financial stability by creating “Systemically Important Financial Institutions”.

Furthermore, regarding the relationship between market power and bank stability that focus on concentration, two views exist in literature: “concentration stability” and “Concentration fragility” (Bretschger, Kappel, & Werner, 2012; Fu, Lin, & Molyneux, 2014). Advocates of the “concentration-stability” view (e.g. Allen & Gale, 2004; Beck, Demirguc-Kunt, & Levine, 2006; Chang, Guerra, Lima, & Tabak, 2008) are of the opinion that larger banks in concentrated banking sectors scale down financial fragility through at least five (5) channels:

 Larger banks are more likely to increase their profits, thus building up high “capital buffers, which allow them to be less prone to liquidity or macroeconomic shocks;  Larger banks have the capacity to increase their charter value, and this consequently

dampens bank managers’ appetite of excessive risk taking;

 The monitoring of few large banks is easy and uncomplicated. This increases the efficiency of supervisory authorities, and consequently translates to a reduction in the risk of a system-wide contagion;

 Larger banks are equipped to provide credit monitoring services; and

 Given higher economies of scale and scope, larger banks have the capacity to efficiently diversify their loan portfolio geographically through their cross-border activities/operations.

Chang et al. (2008) examined the stability-concentration relationship in the Brazilian banking system. The Brazilian case aligns with the main intuition of the concentration-stability view

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that banks in largely concentrated banking system can diversify their loans, while also improving their risk-return trade-off. Likewise, Beck et al. (2006) using data from 69 countries over the period of 1980 – 1997 indicated that financial crises are less probable in more concentrated banking systems.

On the other hand, proponents of the “concentration-fragility” view (e.g. Boyd & De-Nicolo, 2005; Caminal & Matutes, 2002) are of the opinion that larger banks in a concentrated banking sector weaken stability through three channels:

 Larger banks are perceived to be too-big-to-fail institutions, which will be rescued through government guarantees, and consequently making the moral hazard problem more severe;

 Larger banks usually charge high loan interest rates by their market power, which may encourage increased risk-taking amongst borrowers to compensate for such high rates, and the repercussion could be increased default risk; and

 The managerial efficiency of a large bank in areas such as risk diversification in assets and liabilities may decline with time, and consequently resulting in high operational risk.

Uhde & Heimeshoff (2009) provided empirical evidence that national banking market concentration has a negative impact on the financial soundness of European banks over the period from 1997 to 2005 as measured by the Z-score technique while controlling for bank- specific, macroeconomic, regulatory, and institutional factors. The result of the analysis revealed that Eastern European banking markets that are characterised by a higher fraction of government-owned banks, fewer diversification opportunities, and lower levels of competitive pressure are more prone to financial instability, while capital regulations were found to support banking stability.

In addition to the above and with regards to the effect of market power, Nguyen, Skully, & Perera (2012) explored 151commercial banks from four South Asian countries (Bangladesh, India, Pakistan and Sri Lanka) within the period of 1998-2008. The findings indicated that South Asian Banks with greater market power performed better and were more stable when their activities transcend traditional banking activities. More so, Nguyen et al. (2012) further found that higher market concentration led to increased competitive pressure, which gave rise

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to increased lending to low-creditworthy customers that consequently materialised in higher non-performing asset ratios for less banking institutions.

Soedarmono, Machrouh, & Tarazi (2011) based on a sample of commercial banks from 12 Asian countries over the period of 2001 – 2007; found out that greater market power in the banking sector translates to higher instability. They suggested that although banks in less competitive markets were better capitalised, their default risk remained higher; however, they indicated that such behaviour is dependent on the economic environment.

Bornemann, Homolle, Hubensack, Kick, & Pfingsten (2014) examined the motives for the creation and usage of General Banking Risk (GBR) Reserves in German banks and assessed their role in financial stability. They found that GBR reserves are primarily created for the sole purpose of building up Tier 1 capital for the management of regulatory capital and earnings management. Additionally, the results indicated that banks using GBR reserves are less likely to experience financial distress or default events. Bornemann et al. (2014) further concluded that the existence of GBR reserves serves both as a convenient capital earnings management tool for bank managers and as a regulatory instrument for the enhancement of bank stability.

Maudos & Fernandez De Guevara (2011) analysed the relationship between bank size, market power and financial stability. They used data panel from banks in 25 EU countries, the US, Canada, and Japan in the period of 2001 – 2008. In relation to financial stability, Maudos & Fernandez De Guevara (2011) suggested that an increase in market power leads to greater stability. They hold that this view supports the traditional notion that excess competition in the banking sector can be harmful to financial stability. They also asserted that although size has a negative effect on financial stability, the corresponding relationship is not linear with respect to very big banks, as an increase in size decreases the probability of bankruptcy.

Creel, Hubert, & Labondance (2014) used the seminal work of Beck & Levine (2004) and adopted the same variables and econometric method to estimate the link between economic performance and financial stability in European countries, while also independently controlling for the level of financial depth. They tested how different measures of financial instability (microeconomic indicators, institutional index, and derived statistical index – principal component analysis) affect economic performance. And they found out that financial instability has a negative effect on economic growth.

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Swamy (2014) employed a robust panel of 56 Indian banks covering the period from 1996 to 2009 to measure the degree of volatility and soundness in the Indian banking sector. The study made use of a micro vector autoregressive (VAR) model and corroborated the significance of the interrelatedness of bank-specific variables such as capital adequacy, asset quality, liquidity and profitability. Swamy provided empirical evidence for the centrality of banking system stability for aiding financial stability in the context of banking dominated emerging economy (India). The results showed that within the period of 1996 to 2009, the Indian financial system and in particular the banking system demonstrated continued stability when compared to other countries.

Chiaramonte et al. (2015) investigated the accuracy of the Z-score on a sample of banks from 12 European countries over the period of 2001 – 2011. The study examined whether the Z- score is a valuable model for predicting bank distress relative to the CAMELS-related covariates, and if its ability to signal bank distress differs through the period, bank size, business model (shareholders/stakeholders oriented banks), and geographic region. Using probit and survival analysis models, the study found that the Z-score is largely a valuable and fewer data demanding measure of predicting bank distress. They opined that the ability of the Z-score to predict bank distress over the entire period of the study (2001 – 2011) and in the crisis years (2008 – 2011), is to some extent as good as more data demanding models, such as the CAMELS model. Additionally, Chiaramonte et al. (2015) suggested that the Z-score is a more effective predictor for commercial banks and in particular large banks. In particular, to the sample, the study indicated that the Z-score was relatively more successful in predicting distress and non-distress events in the European countries that were less affected by the financial crisis.

Conclusively, the views expressed by the financial and banking stability related studies indicate that several factors influence stability. Though the studies show that the Z-score is a popular indicator of stability, its determinants vary according to periods, business cycles, jurisdiction, type of banking institution (Conventional or Islamic), and customer base. In summary, the size of banking institutions, banking concentration levels, ownership structure, macroeconomic circumstances, earnings, liquidity levels, and management structure amongst others influence financial stability in the whole. To that end, studies to ascertain the changing and dynamic factors that influence stability must be regularly embarked upon. Thus, the various determinants highlight the rationale to ascertain the factors that determine the stability of Nigerian DMBs.

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