Why Size Matters Again for Banks

Public Interest Statement

The factors that influence stability of banks take been of immense interest to depository financial institution supervisors and regulators in their quest to ensure stability in the financial system. This newspaper examines the impact of bank size and bank funding risk on banking company stability with focus on the rural banking industry in Ghana. The results advise that size and funding gamble support banking concern stability.

1. Introduction

The issue of limiting depository financial institution size as a way of ensuring stability in the financial organization has always been at the middle of bank supervision and regulation. However, the result has gained much prominence since the 2007/2008 global financial crisis. This is considering show abounds that large banks accounted for the crisis that caused a meaning impairment to many economies across the globe. E'er since the world emerged from the crisis, the debate on the optimal size, organizational complexity and a range of activities of banks has heightened (Viñals et al., 2013). This contend has flourished against the properties of a financial landscape that has developed markedly over the past two decades, fuelled by financial innovation and deregulation (Laeven, Ratnovski, & Tong, 2014). Regulators in the U.s.a. (under the Dodd Act, 2010) and in the Eu [every bit in recommendations by the Liikanen (2012) implemented into EC law every bit well equally the recommendations by the Vickers Report (2011) implemented into UK police] are making strenuous efforts to constrain the size of banks past demanding more capital letter and liquidity in line with Basel III requirements and also restricting bank'southward involvement in riskier areas of activity.

Employing panel information from the The states of America's (USA) depository financial institution property companies and controlling for quality of management, leverage and diversification, de Haan and Poghosyan (2012) discover that bank size reduces returns volatility. However, the issue is non-linear: when bank size exceeds some threshold, size positively impacts returns volatility. This probably explains why i dimension of the contend on the optimal size of banks focuses on whether there should be regulatory restrictions on depository financial institution size every bit a manner of circumventing the recrudescence of the global crisis and its attendant problems. One view is the imposition of capital surcharges on large banks as in Basel Iii. Another view is that policy-makers should reduce the too-big-to-fail subsidies (Farhi & Tirole, 2012; Stein, 2013).

The above points to the importance of bank size to the stability of the fiscal organisation in particular and the economy in general. This newspaper contributes to the argue on the size–stability nexus with data from the rural banking industry in Ghana. The interest of the newspaper lies in whether or not increasing size of a rural bank [as well called rural and community banks (RCBs)] ¹ has any significant implications for its stability. This involvement stems from the design of RCBs as unit banks with geographically demarcated areas of operations which limits the extent to which they tin can grow.

Interest in the business models of banks is gathering momentum in recent times, especially subsequently the global fiscal crisis. Co-ordinate to Köhler (2015), business models relate to how banks make profits, the customers they serve and the distribution channels they use. One surface area of business model is funding structure. Then far, the debate has revolved around whether or non it is more appropriate for a bank to adopt wholesale funding than deposit funding (Calomiris & Kahn, 1991; Huang & Ratnovski, 2011; Shleifer & Vishny, 2010). This newspaper joins the fence by exploring the effect of a bank'due south funding risk on its stability.

The results of this report indicate that bank size (measured every bit natural logarithm of total assets and natural logarithm of deposits), bank funding adventure (measured as funding risk Z-score), profitability (measured as return on disinterestedness-ROE), inflation and gdp (Gross domestic product) have generally supported banking concern stability. The results also bespeak that diversification, credit gamble and financial development or construction have generally undermined bank stability.

The contributions of this newspaper to knowledge are largely twofold. The get-go contribution of this newspaper to knowledge is that it analyses banking company stability which is one of the risks that are of much significance to policy-makers in their quest to achieve financial evolution and economic growth. The finding that size promotes banking concern stability makes a contribution to the ongoing fence on the effect of bank size on bank stability. At to the lowest degree the finding suggests that the button for depository financial institution size restrictions in the name of ensuring stability in the financial organisation must be pursued with considerable tact and caution. Blanket implementation of size constraints aimed at taming the growth rate of bank size may be inimical to the stability of banks such equally RCBs in Ghana.

The second contribution of this study to knowledge is that it shows that the funding risk of a rural bank has a positive statistically significant effect on its stability. The postulation is that RCBs that improve their funding risk Z-scores should anticipate better stability. This represents an addition to the determinants of depository financial institution stability. It is expected that future researchers will test the consequence of the funding risk Z-score on banking company stability with information from different parts of the world.

2. Theoretical review

The connection between depository financial institution size and banking company stability can be understood in the context of the agency theory of the firm. The crux of the agency theory (Jensen & Meckling, 1976) is that owners and managers of the firm take incompatible goals with the latter postulated as running the firm to pursue their personal inflation at the expense of the old. In other words, the theory submits that the decisions and deportment of managers are inordinately skewed towards personal gains. Thus, an increasing firm size is a issue of managerial empire-building and that large firms are characterized by bad governance. The contention is that managers may increase the size of a firm to receive larger bounty or to enjoy private benefits from the prestige of running a big firm (Gabaix & Landier, 2008; Jensen, 1986; Murphy, 1985). This theory, by extrapolation, predicts a negative relationship betwixt banking company size and bank stability.

Some other theory that offers an explanation for the possible human relationship betwixt bank size and bank stability is the stewardship theory. The theory argues that managers are inherently trustworthy and thus are non susceptible to misappropriate the resources of the business firm (Davis, Schoorman, & Donaldson, 1997; Donaldson & Davis, 1991). Information technology posits that in that location are not-financial motivators, and that corporate managers are seen equally drawing motivation from the need to achieve, to gain intrinsic satisfaction via successful execution of intrinsically challenging work, to do responsibility and authority and by information technology draw recognition from peers and bosses (McClelland, 1961). When corporate managers identify with the firm (more than likely if they accept been with the firm for a long time and have shaped its form and directions), this facilitates the merging of individual ego and the corporation, thus melding individual cocky-esteem with corporate prestige. The theory argues that information technology is possible for a corporate managing director to notice a form of activeness personally unrewarding, however, they are probable to pursue information technology from a sense of duty. This compliance with a duty when there is no personal reward is referred to every bit normally induced compliance (Etzioni, 1975). When corporate managers perceive that their fortunes are inextricably tied to their current employers through an expectation of future employment or alimony rights, they may view their interest as aligned with that of the firm and its owners even if they do not ain shares in the house. In essence, the stewardship theory submits that there is no inner motivational problem among corporate managers; corporate managers aspire to achieve good corporate functioning. Functioning variations, in the view of the theory, emanates from the structural situation in which corporate managers find themselves. If the structural situation is convenient, one should expect good corporate performance from corporate managers. The question arises as to whether or not the organizational construction supports corporate managers to formulate and implement plans for loftier corporate performance. Structures support goals to the extent that they "provide clear, consistent expectations and authorize and empower senior management" (Donaldson & Davis, 1991). In a nutshell, different agency theory that predicts a short-run inflation-induced increasing size that may be inimical to stability in the long-run, stewardship theory suggests that increasing size is indicative of structural convenience that may enhance stability. By deduction, the stewardship theory predicts a positive relationship betwixt bank size and depository financial institution stability.

The effect of bank size on bank stability can also be viewed from the perspective of the concentration-stability and concentration-fragility hypotheses (Uhde & Heimeshoff, 2009). The concentration-stability hypothesis argues that larger banks in concentrated banking sectors subtract financial fragility through at least five channels: (1) larger banks may increase profits, building up high "capital buffers", thus allowing them to be less susceptible to liquidity or macroeconomic shocks; (2) larger banks may ameliorate their charter value, dissuading bank managers from extreme run a risk-taking behaviour. The argument of Boot and Thakor (2000) is that larger banks tend to resort to credit rationing; thus, they tape fewer but higher quality credit investments which meliorate their financial stability; (iii) supervisory bodies find larger, but fewer, banks easier to monitor, thus, there is effective supervision in concentrated banking markets which reduces the risk of system-broad contagion; (4) larger banks tend to be subject to providing credit monitoring services; and (5) larger banks enjoy higher economies of scale and scope, therefore, they have the potential to diversify loan-portfolio risks efficiently and geographically through cross-border activities (Mirzaei, Moore, & Liu, 2013). However, there are ii angles to this. The commencement argument is that size promotes better diversification which reduces risks and permits banks to support their operations with less capital and less-stable funding. The second argument centres on the ability of larger banks to operate in a different market segment. Larger banks may have a comparative advantage in market place-based activities which crave pregnant fixed costs and enjoy economies of scale (Laeven et al., 2014). Consequently, the prognosis of the concentration-stability hypothesis is that at that place is a positive relationship between bank size and bank stability.

The concentration-fragility view submits that larger banks in a concentrated marketplace decrease stability through three channels: (ane) exacerbation of moral hazard problem due to the fact that larger banks are seen every bit "too large to fail" institutions and are, thus, given authorities guarantees. According to Mishkin (1999), as banks increase in size, the moral hazard problem is exacerbated for the manager whose hazard-loving behaviour is inflated with the knowledge of being shielded by government's safety net (i.eastward. the effect of too-big-to-fail subsidies, an intervention usually implemented past fundamental banks to bail out financially distressed big banks). It posits that larger banks respond to too-large-to-fail subsidies. Owing to the perception that the creditors of larger banks volition be rescued by the bailout subsidies in case of bank distress, the toll of debt for larger banks is lower, thus encouraging them to develop the penchant for utilize of leverage and unstable funding, and to engage in risky market place-based activities (Laeven et al., 2014); (2) due to the fact that larger banks tend to charge college loan interest because of their market power, borrowers may exist compelled to undertake risky projects to be able to pay off the loans which may increase default risks; and (3) managerial efficiency such equally run a risk diversification in assets and liabilities may deteriorate in a concentrated banking market place, causing high operational risk (Mirzaei et al., 2013). Hence, the prediction of the concentration-fragility hypothesis is that the effect of size on bank stability is negative.

According to Köhler (2015), retail banks fund their activities with client deposits. Since RCBs are retail banks, the paper adopts the funding risk Z-score adult past Adusei (2015) that measures the number of deviations customer deposits mobilized past a bank would take to fall from the hateful to wipe out equity capital or to call for equity recapitalization to measure the funding adventure of RCBs. The college the funding risk Z-score, the more stable the funding sources of the bank. It is, therefore, expected that funding risk volition positively impact bank stability.

three. Empirical review

Empirically, not much attention has been given to the size–stability human relationship. So far studies have focused on how contest affects banking concern stability (Amidu & Wolfe, 2013; Beck, De Jonghe, & Schepens, 2013; Fiordelisi & Mare, 2014). I written report that specifically explores size–stability connexion is Laeven et al. (2014). It analyses the relationship between banking company size and bank stability with data from 52 countries and finds that larger banks, on average, create more risks than smaller banks. Köhler (2015) analyses the impact of business organisation models on bank stability in the EU banking sector for the menstruation between 2002 and 2011. Amongst other things, the study reports that bank size has a significant negative touch on on bank stability, implying that larger banks are less stable than smaller banks. Nonetheless, Altaee, Talo, and Adam (2013) examination the stability of banks in the Gulf Cooperation Council countries and observe, among other things, that size (represented past total assets) has no statistically significant impact on bank stability. The obvious conclusion from the higher up is that the relationship between size and stability is inconclusive. Thus, there is scope for the further interrogation of this human relationship. What is the effect of the size of a rural banking concern on its stability.

The relationship betwixt funding structure and bank stability has been receiving accumulating empirical attention. Whereas Calomiris and Kahn (1991) submit that wholesale funding may lessen banking company take a chance via a improve monitoring of banks by sophisticated fund providers and a better diversification of funding resources, Huang and Ratnovski (2011) are of the view that the price of wholesale funds is less stable and that wholesale funds are repriced more than quickly to reflect banking concern's riskiness. On the other hand, customer deposits are repriced more slowly and are relatively more stable (Shleifer & Vishny, 2010). Demirgüç-Kunt and Huizinga (2010) notice that a larger share of non-deposit funding is associated with greater instability. However, Köhler (2015) reports different impact of non-deposit funding for different types of banks. Whereas an increment in the share of non-eolith funding decreases the stability of retail-oriented banks, an increment in the share of non-deposit funding increases the stability of investment banks (Köhler, 2015). The current written report examines the event of funding risk on the stability of RCBs in Ghana.

In the cyberbanking context, it is of import to distinguish funding risk from funding liquidity and funding liquidity take chances. Co-ordinate to Drehmann and Nikolaou (2010, p. ii), funding liquidity is "the power to settle obligations with immediacy". The definition offered past the International monetary fund (2008) is in line with the foregoing definition. It defines funding liquidity as "the ability of a solvent institution to make agreed-upon payments in a timely manner" (IMF, 2008, p. eleven). Funding liquidity take chances is "the possibility that over a specific horizon the bank will become unable to settle obligations with immediacy" (Drehmann & Nikolaou, 2010, p. 2). The higher up definitions bear the notion of the ability of a bank to run into its financial obligations as and when they fall due. In contrast, funding risk, in this paper, is defined as the probability that the eolith mobilization strategies of a rural banking concern volition fail or the probability that depositors of a rural depository financial institution will withdraw their deposits, resulting in the deterioration of the banking company'southward deposits which compels it to autumn on equity sources of funding. Information technology is unlike from funding liquidity and funding liquidity risk, in the sense that it focuses on the reliability of customer deposits documented in the extant literature as the main source of funding retail banks.

iv. Overview of rural banking in Ghana

The rural banking model started in Ghana in the late 1970s as a means of encouraging rural savings every bit well every bit meeting the peculiar financial needs of rural dwellers. Deposit mobilization, credit and investment extension and involvement in the payments arrangement were the traditional banking functions penciled every bit the mandate of rural banks. Rural banks are express liability companies owned by residents of the localities where they are set up with limits placed on the number of shares an individual can acquire.

At that place are 4 major services offered by rural banks. These are microfinance loans, susu loans, salary loans and commercial loans (Nair & Fissha, 2010). Table 1 provides details of major products marketed by RCBs.

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Table ane. Major rural bank credit products

Table 2 summarizes the legal, regulatory and tax framework of RCBs. As tin be observed, the minimum capital letter requirement for establishing a rural bank is GH¢ 150,000 ² an equivalent of United states$37,500. ³

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Tabular array 2. The legal, regulatory and revenue enhancement framework of RCBs

5. Methodology

5.ane. Variables

In this section, the variables used for analysing banking company stability are presented. A summary of the variables and how they are measured is presented in Tabular array three.

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Tabular array iii. Variables, definitions, notations and expected signs

5.1.one. Dependent variables

Ane mensurate of bank stability is Z-score. Also called bank stability (BSTAB), Z-score comprises bookkeeping measures of profitability, leverage and volatility (Demirgüç-Kunt & Huizinga, 2010; Stiroh, 2004a, 2004b). Information technology is computed every bit: (i) $$Z\text{- score}{\left(\text{BSTAB}\right)}_{i,t}=\left[\frac{{\text{ROA}}_{i,t}+\frac{{\text{E}}_{i,t}}{{\text{A}}_{i,t}}}{\mathit{\sigma }{\text{ROA}}_{ip}}\right]$$ (i)

where BSTAB _{i, t} is the stability Z-score of bank i in quarter t, ROA_it is the return on assets ratio, East/A is the equity-to-asset ratio of bank i in quarter t and σROA _ip is the standard departure of the ROA of banking concern i over the whole sample menses p (Köhler, 2015). Z-score is divers as the number of standard deviations by which a banking company'south ROA has to fall for the bank to become insolvent. It is, thus, an indicator of insolvency chance. Thus, a college Z-score predicts a lower chance of instability or insolvency. In this written report, Z-score is used to measure the overall bank stability. Post-obit the example of Köhler (2015), the two components of the Z-score are also used as dependent variables to proceeds an insight into the component that is driving the relationship betwixt the Z-score and the independent variables. The components are: (ii) $${\text{RAROA}}_{it}=\frac{{\text{ROA}}_{it}}{\mathit{\sigma }({\text{ROA}}_{ip})}$$ (ii) (three) $${\text{RAEA}}_{it}=\frac{E/A_{it}}{\mathit{\sigma }({\text{ROA}}_{ip})}$$ (3)

5.1.two. Contained and control variables

Bank size is one of the two independent variables and is measured as the natural logarithm of total avails of a rural bank (Amidu & Wolfe, 2013). Another measure of bank size is the natural logarithm of customer deposits. This is used equally the ancillary measure of bank size. The second independent variable is funding gamble (FUNDRISK) which is measured by a Z-score. ⁴ The Z-score is computed as follows: (4) $$Z\text{-score}{\left(\text{FUNDRISK}\right)}_{i,t}=\left[\frac{\text{DEP}/{\text{TA}}_{i,t}+E/{\text{TA}}_{i,t}}{\mathit{\sigma }\left(\text{DEP}/{\text{TA}}_{ip}\right)}\right]$$ (4)

where Z-score (FUNDRISK) is the funding risk Z-score of depository financial institution i in time t which measures the number of deviations customer deposits would have to fall to compel the banking company to wipe out equity finance; DEP/TA _it is the eolith to total assets ratio of banking company i in time t; Eastward/TA _it is the equity to total assets ratio of bank i in fourth dimension t; and σ(DEP/TA _ip ) is the standard deviation of the deposit-to- nugget ratio. This measure of funding risk of RCBs is important considering retail-oriented banks fund their activities with client deposits (Köhler, 2015). It is, therefore, expected that funding risk volition positively bear on bank stability.

The control variables obtained from the literature are the investment-to-avails ratio measuring diversification in the business organisation model of the bank (Beccalli, Anolli, & Borello, 2015); liquidity risk measured by the greenbacks and due from balances held at other depository institutions to total avails ratio (Fiordelisi & Mare, 2014; Rose & Hudgins, 2008); the loans-to-assets ratio measuring credit risk (Curak, Poposki, & Pepur, 2012); and profitability measured by ROA and ROE which are common measures of depository financial institution profitability. The use of total loans to total assets ratio to mensurate credit risk is deliberate. The total loans-to-total assets ratio indicates the extent to which the bank is vulnerable to variations in the repayment attitudes of its borrowers. A higher loans-to-full assets ratio indicates that the bank has more than of its assets in loans which ways that if at that place should be more than borrower default, the banking concern is closer to insolvency. Indeed, the employ of loans-to-assets ratio as measure of credit gamble is not novel. Researchers such as Curak et al. (2012) have measured credit risk by this ratio.

To bank check the robustness of the findings, three external variables are introduced to further examine the impact of bank size and bank funding take chances on bank stability. These are inflation, financial development and Gdp. Whereas aggrandizement is used to measure macroeconomic stability in Republic of ghana, financial development as measured past growth in private sector credit is used to proxy the financial construction in Ghana. Gdp is used to measure the overall wellness of Ghana's economy.

The consequence of inflation on banking concern performance depends on whether or non the sometime is anticipated or unexpected. When aggrandizement is anticipated and interest rates are adjusted accordingly, the effect of aggrandizement on profitability and ultimately stability should be positive (Perry, 1992). On the other hand, when aggrandizement is unexpected, a negative effect on bank stability is expected because unexpected increases in inflation crusade cash-flow problems for borrowers leading to abrupt absconding of loan arrangements with accompanying loan losses. Hoggarth, Milne, and Wood (1998) argue that loftier and variable inflation may create loan planning and negotiation difficulties.

Financial evolution equally measured by the growth in private sector credit could exist good or bad for banking concern stability. If high-quality credit is extended to the private sector, this could yield more profits which volition result in banks edifice upwards "uppercase buffers" resulting in improved banking company stability. On the other mitt, growth in private sector credit could adversely bear upon bank stability if this growth is associated with falling underwriting standards resulting in more non-performing loans. In other words, the effect of fiscal development on bank profitability could either be positive or negative. Mirzaei et al. (2013) provide evidence that supports this postulation. They find that fiscal structure negatively affects bank profitability in emerging economies and positively affects bank profitability in avant-garde economies.

Due to the fact that increasing Gdp suggests an improvement in the full general income in an economy, some studies have found Gdp growth equally profit-enhancing and by extension stability-enhancing (Kosmidou, 2008). On the other hand, growth in GDP is associated with a reduction in profitability, and past extension, a reduction in banking concern stability (Tan & Floros, 2012). The intuition is that an improvement in economical growth results in an improvement in the business concern environment and lowers bank entry barriers. This promotes competition in the banking industry which reduces banking concern profitability (Tan & Floros, 2012). A reduction in banking concern profitability implies a reduction in its stability. It is obvious from the to a higher place that there are two contrasting positions on the issue of GDP on depository financial institution stability (positive and negative).

v.1.3. The models

Using the three measures of banking company stability, the post-obit models are to be estimated:

(5) $${\text{BSTAB}}_{i,t}={\mathit{\beta }}_1+{\mathit{\beta }}_2{\text{BSIZE}}_{i,t-1}+{\mathit{\beta }}_{\mathrm{iii}}{\text{DEPO}}_{i{,}_t-1}+{\mathit{\beta }}_4{\text{FUNDRISK}}_{i,t-1}+{\mathit{\beta }}_{\mathrm{five}}{\text{LRISK}}_{i,t-\mathrm{ane}}+{\mathit{\beta }}_{\mathrm{half\; dozen}}{\text{CRISK}}_{i,t-1}+{\text{B}}_{\mathrm{vii}}{\text{DIV}}_{i,t-\mathrm{one}}+{\mathit{\beta }}_{\mathrm{eight}}{\text{ROE}}_{i,t-1}+{\mathit{\beta }}_9{\text{INFL}}_{t-1}+{\mathit{\beta }}_{10}{\text{FINDEV}}_{t-1}+{\mathit{\beta }}_{11}{\text{GDP}}_{t-1}+{\mathit{\mu }}_{it}$$ (five)

(vi) $${\text{RAROA}}_{i,t}={\mathit{\beta }}_1+{\mathit{\beta }}_2{\text{BSIZE}}_{i,t-1}+{\mathit{\beta }}_3{\text{DEPO}}_{i,t-1}+{\mathit{\beta }}_4{\text{FUNDRISK}}_{i,t-\mathrm{one}}+{\mathit{\beta }}_5{\text{LRISK}}_{i,t-1}+{\mathit{\beta }}_6{\text{CRISK}}_{i,t-\mathrm{i}}+{\mathrm{B}}_{\mathrm{vii}}{\text{DIV}}_{i,t-1}+{\mathit{\beta }}_8{\text{ROE}}_{i,t-1}+{\mathit{\beta }}_9{\text{INFL}}_{t-1}+{\mathit{\beta }}_{10}{\text{FINDEV}}_{t-\mathrm{i}}+{\mathit{\beta }}_{11}{\text{GDP}}_{t-1}+{\mathit{\mu }}_{it}$$ (six) (vii) $${\text{RAEA}}_{i,t}={\mathit{\beta }}_1+{\mathit{\beta }}_2{\text{BSIZE}}_{i,t-\mathrm{one}}+{\mathit{\beta }}_3{\text{DEPO}}_{i,t-1}+{\mathit{\beta }}_4{\text{FUNDRISK}}_{i,t-1}+{\mathit{\beta }}_5{\text{LRISK}}_{i,t-1}+{\mathit{\beta }}_6{\text{CRISK}}_{i,t-1}+{\mathrm{B}}_7{\text{DIV}}_{i,t-\mathrm{one}}+{\mathit{\beta }}_8{\text{ROE}}_{i,t-\mathrm{i}}+{\mathit{\beta }}_{\mathrm{nine}}{\text{INFL}}_{t-1}+{\mathit{\beta }}_{\mathrm{x}}{\text{FINDEV}}_{t-\mathrm{one}}+{\mathit{\beta }}_{11}{\text{GDP}}_{t-1}+{\mathit{\mu }}_{it}$$ (7)

where BSTAB _{i, t} , RAROA _{i, t} and RAEA _{i, t} are the bank stability, bank-risk adjusted ROA and bank take chances-adjusted capitalization; SIZE is the Bank size; DEPO is the Bank deposits; FUNDRISK is the Banking concern funding adventure; LRISK is the Liquidity risk; CRISK is the Credit risk; DIV is the diversification in the business model; ROE is the Return on equity; ROA is the Return on assets; INFL is the Inflation rate; FINDEV is the Financial development; Gdp is the Gross domestic product; β and μ are the parameter and stochastic fault term respectively; i, t are the individual bank and time effect respectively.

A two-phase arroyo is used to estimate the in a higher place models. The first stage involves the interpretation of the models with natural logarithm of full assets as proxy for bank size (BSIZE). The 2d stage involves the estimation of the models with banking concern deposits (DEPO) as the 2nd measure of bank size. These estimations are initially done with only the banking concern-specific factors as control variables. The robustness of the results from each stage is checked with the re-estimation of the three models with the macroeconomic variables (inflation, financial development and GDP) as boosted command variables.

In estimating the in a higher place models, the dependent variable in time (t) is related to the explanatory variables in fourth dimension (t − one). In other words, all explanatory variables are lagged to mitigate potential endogeneity concerns (Hannan & Prager, 2009). The logic is that depository financial institution stability in fourth dimension t is a function of the combined lagged values of the explanatory variables. All data are log-transformed to bargain with skewness.

The definitions of these variables and their expected relationships with the dependent variables are presented in Table 3.

5.1.four. Model suitability checks

Three tests are performed to bank check the suitability of the panel model used in this report. First is the Hausman test. It assesses the aught hypothesis that the deviation between the fixed event (Fe) and the random consequence (RE) of the model is not systematic. The results of this test determine whether the Atomic number 26 or RE model is suitable for analysis. ⁵ The FE model assumes that each of the banks in the sample is unlike, therefore, the banking concern'due south fault term and the abiding (which captures individual characteristics) should not be correlated with those of other banks. Thus, if the error terms are correlated, then the FE model is not suitable since inferences may not be correct. In that instance, the RE model is appropriate. The 2d test is the likelihood ratio examination or the redundant FE test which assesses the appropriateness of the FE interpretation technique. The 3rd exam is the Wald test. It examines the joint significance of the explanatory variables in explaining the variations in the dependent variable.

v.ii. Data sources

Due to data constraints, 112 out of 137 rural banks in Ghana every bit at January 2013 have been selected for analysis. The 112 rural banks take requisite information needed for the written report. The depository financial institution-specific variables have been extracted from the quarterly reports on RCBs roofing 2009Q1–2013Q4 compiled past the ARB Apex Banking concern (the supervisory body of RCBs). Inflation and growth in private sector credit accept been obtained from the Bank of Ghana.

The descriptive statistics of the data are reported in Tabular array four. The full number of observations is 2,200. The hateful Z-score is 2.29. Compared to the hateful Z-scores from other parts of the world, it can exist argued that RCBs in Ghana are more stable. In their report of depository financial institution stability and profitability in advanced and emerging economies, Mirzaei et al. (2013) report 1.91 and 2.06 as hateful bank stability Z-scores for commercial and non-commercial banks, respectively, in emerging economies and one.09 and 0.99 for commercial and non-commercial banks, respectively, in advanced economies. In terms of RAROA, whereas Köhler (2015) reports 2.58 for all banks in fifteen EU countries betwixt 2002 and 2011, Table 4 shows that the mean RAROA of RCBs is 1.55, suggesting that the returns of RCBs in Ghana are more volatile than the returns of banks in the xv Eu countries. This may be attributed to the risky nature of rural financial intermediation. With respect to RAEA, whereas Köhler (2015) finds 31.24 as the hateful score of RAEA for all banks in the fifteen EU countries, the mean score for RCBs in Ghana reported in Table 4 is 0.03, suggesting that banks in the xv EU countries are better capitalized than RCBs in Ghana. Obviously, there is enough justification to suggest that RCBs require recapitalization. The mean size of RCBs in Republic of ghana in natural logarithm terms is xv.62. This contrasts with the mean bank size of xiv.88 in emerging markets banks reported by Mirzaei et al. (2013). On the face of this evidence, it tin be ended that the average rural bank in Ghana is larger than the average bank studied past Mirzaei et al. (2013). The average funding run a risk Z-score is ane.64 which is satisfactory.

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Table 4. Descriptive statistics

vi. Results

Tabular array 5 presents the Pearson correlations betwixt pairs of the independent variables. The highest correlation occurs between the ii profitability measures: ROE and ROA. Thus, ROE and ROA will not enter 1 model. ROE is included in the models 5 and vi, whilst ROA is included in model seven. The results of the correlation analysis bear witness that non inbound the two profitability measures in ane model would hateful that the models have passed the multicollinearity test (Bryman & Cramer, 1997).

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Table 5. Pearson correlation matrix

6.1. Phase one: total assets as proxy for banking concern size

The empirical results are reported in Tables 6–8. Table 6 reports the results when Z-score is used to proxy banking concern stability. Respectively, Tables seven and 8 report the results when RAROA and RAEA are used to proxy banking concern stability. The Hausman tests as well as the redundant FE tests results reported in Tables vi–eight signal that the FE model is the optimal estimation technique to use for analysis. In the three tables, the results reject the null hypothesis that the difference between the coefficient of the fixed and RE models is not significant. This is because the probability of the χ ⁱⁱ is less than 0.05 (Prob >χ ⁱⁱ = 0.0000). Thus, the report adopts the Iron panel regression model for assay. The R ² in all the models ranges between 71 and 88%, the Durbin–Watson statistic is effectually two, the F-statistic ranges betwixt sixteen.30 and 68.44 significant at 1% significance level and the Wald test χ ² values are all significant at 1% significance level. The results of these diagnostic tests suggest that the models are reliable and thus the results are likewise reliable.

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Tabular array 6. Regression results. Dependent variable: Z-score

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Table seven. Panel regression results. Dependent variable: RAROA

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Table 8. Regression results. Dependent variable: RAEA

The effect of size on bank stability has not been completely and satisfactorily resolved. Laeven et al. (2014) find that large banks, on average, create more individual and systemic chance than smaller banks. Köhler (2015) also reports that bank size has a significant negative impact on bank stability, meaning larger banks are less stable than smaller banks. However, Altaee et al. (2013) observe that size has no statistically significant bear on on bank stability. In Tables 6–8, a robust positive statistically meaning impact of size on the stability of a rural banking company is observable, suggesting that increasing size of a rural bank implies its improving stability. Indeed, this upshot is observed even when the data are split. Theoretically, support has been found for the prediction of the concentration-stability hypothesis which submits that increasing depository financial institution size implies improving banking concern stability (Beck et al., 2013; Boot & Thakor, 2000; Uhde & Heimeshoff, 2009) as well as the prediction of the stewardship theory which predicts that increasing size signals good governance and ultimately practiced stability. The event contradicts the agency theory's postulation that increasing size should signal college instability. Empirically, this result contradicts the findings of Köhler (2015), Laeven et al. (2014) and Altaee et al. (2013). The five channels through which banking sectors decrease financial fragility delineated by the concentration-stability hypothesis banking come handy as the possible explanation for this event: (1) larger banks may increase profits, edifice up loftier "capital buffers", thus allowing them to be less susceptible to liquidity or macroeconomic shocks; (2) larger banks may improve their lease value, dissuading bank managers from extreme risk-taking behaviour; (3) supervisory bodies find larger, just fewer, banks easier to monitor, thus, in that location is constructive supervision in concentrated banking markets which reduces the gamble of system-wide contagion; (iv) larger banks tend to be subject to providing credit monitoring services; and (5) larger banks relish higher economies of scale and telescopic, therefore, they take the potential to diversify loan-portfolio risks efficiently and geographically through cross-edge activities (Mirzaei et al., 2013).

The results in Tables half-dozen–8 show that under all the three measures of bank stability, there is a potent statistically meaning positive outcome of funding risk on bank stability, implying that an improvement in the bank funding risk results in a higher bank stability. This confirms the a priori prediction of this report that there should be a positive relationship between funding risk and bank stability. Every bit can be observed, this finding is robust even when the data are split. The implication is that a rural depository financial institution that shows consistency in its effective deposit mobilization strategy is more likely to be stable than its counterparts. This accords with the empirical literature that the use of larger customer eolith funding is stability enhancing (Demirgüç-Kunt & Huizinga, 2010; Köhler, 2015; Shleifer & Vishny, 2010).

Profitability equally measured past ROE has shown a robust positive statistically relationship with bank stability implying that increasing profitability implies increasing stability. This is understandable considering, all things being equal, increasing profits would hateful more funds for the bank to meet contingencies. High profitability has been linked to high stability in the banking manufacture because if profits do not flow out to shareholders as dividends, they become part of disinterestedness capital which strengthen the capital base of the banks leading to an improvement in banking company stability (Flamini, McDonald, & Schumacher, 2009).

Tables 6–viii bear witness that credit risk has a negative human relationship with banking company stability. However, this relationship is statistically insignificant, except when RAEA is used to mensurate depository financial institution stability. Thus, some confirmation has been found for the a priori prediction of this written report that credit risk should be negatively related to bank stability. The implication is that deteriorating lending standards portend dire consequences for the stability of RCBs.

Tables 6–8 indicate that under all the three measures of bank stability, the coefficient of liquidity risk (LRISK) is statistically insignificant. This suggests that liquidity risk is not a significant predictor of rural bank stability in Ghana.

The effect of diversification (DIV) on banking company stability is statistically insignificant in Tables 6 and 7. Every bit tin can be observed, the coefficient of DIV under the total models in Tables vi and seven is positive, only when the data are carve up, information technology is either negative or positive. However, in Table 8, where bank stability is measured as RAEA, a weak statistically pregnant negative coefficient of DIV is observed, suggesting that diversification has a negative outcome on bank stability.

6.1.1. Robustness check

As indicated above, the iii models of bank stability are re-estimated ^half-dozen with the inclusion of three external variables (inflation, financial development and Gdp). The purpose is to define the effects of bank size and bank funding take a chance in the midst of variations in aggrandizement, financial development and Gross domestic product. The results are reported in Table 9. As evident in the tabular array, the diagnostic checks support the determination that the results are reliable.

The impact of bank size and funding gamble on bank stability

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Table 9. Results of robustness analysis with inflation, financial development and Gross domestic product as additional control variables

Consistent with the above results, the coefficient of bank size (BSIZE) is positive under all the three models. However, under the Z-score model, the positive coefficient is statistically insignificant. That notwithstanding, generally, the results evidence that the upshot of the size of a rural banking concern on its stability is robust even in the midst of variations in inflation, financial development and GDP.

The results in Table 9 prove that the coefficient of FUNDRISK is positive under all the iii models. This underscores the robustness of the effect of funding take a chance on rural banking company stability. The implication is that funding adventure positively explains the variations in rural banking company stability irrespective of the variations in inflation, financial development and Gdp.

The coefficient of aggrandizement (INFL) is positive and statistically significant under all the three models, suggesting that inflation supports rural depository financial institution stability. In effect, an increase in inflation in one quarter results in an improvement in rural bank stability in the adjacent quarter. The implication is that RCBs in Ghana properly anticipate inflation and adjust the prices of their services accordingly. This is in alignment with the postulation of Perry (1992) that aggrandizement should positively impact banking company stability when information technology is anticipated and factored into the pricing process.

A negative statistically significant relationship between fiscal evolution and bank stability under all the three measures of depository financial institution stability is evident in Table 9, suggesting that an improvement in financial development in 1 quarter results in a reject in the stability of a rural depository financial institution in the next quarter.

Under the Z-score and RAROA models, Gross domestic product shows a positive and statistically significant touch on bank stability. On the other hand, under the RAEA model, a negative statistically meaning touch of Gross domestic product on bank stability is observed. However, since the coefficient of Gross domestic product is weak under the RAEA model (approximately −0.09), it tin be argued that Gdp has generally supported depository financial institution stability.

Generally, the other control variables have maintained their effects on bank stability, suggesting that the results in Tables 6–viii are robust.

half-dozen.2. Phase two: deposits (DEPO) as proxy for bank size

To farther explore the bear on of banking company size and funding risk on bank stability, bank size is proxied with banking concern deposits. The results of the regression estimations using deposits as proxy for bank size are reported in Tables 10 and xi. The Hausman tests every bit well as the redundant FE tests results reported in Tabular array ten evidence that the FEs model is the optimal estimation technique to use for analysis. Thus, the Atomic number 26 panel regression model is used for interpretation. The R ² in all the models ranges between 71 and 87%, the Durbin–Watson statistic is around 2, the F-statistic ranges between 32.02 and xc.95 significant at ane% significance level and the Wald test χ ² values are all pregnant at i% significance level. The results of these diagnostic tests suggest that the results are reliable. This same conclusion can be made about the results reported in Table 11. In Tabular array 11, R ² ranges from eleven to 43%, the F-statistic ranges between 0.33 and 160. threescore significant at 1%, the Durbin–Watson statistic is effectually ii and Wald test χ ² values are all meaning at i% significance level.

The touch of bank size and funding risk on bank stability

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Table 10. Regression results with deposits (DEPO) as proxy for bank size without macroeconomic variables

The impact of bank size and funding risk on bank stability

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Tabular array 11. Regression results with deposits as proxy for bank size including macroeconomic variables as control variables

In Table ten, DEPO has a positive coefficient under all the iii measures of bank stability except that under RAEA, the coefficient is statistically insignificant. The positive statistically significant coefficient of DEPO is observed in Table 11 under the RAROA mensurate of banking concern stability. However, under the Z-score and RAEA measures of depository financial institution stability, the results in Table 11 show that the inclusion of inflation, financial development and Gdp makes the coefficient of DEPO negative. Still, this is statistically insignificant. That notwithstanding, generally, these results underscore the fact that the consequence of size on rural bank stability is positive.

Tables 10 and 11 point that the coefficient of FUNDRISK is positive and statistically significant under all measures of bank stability. The obvious implication is that there is a robust positive relationship between the funding chance of a rural banking concern and its stability.

In line with the results in Table 9 when bank size is measured equally natural logarithm of total assets, inflation, financial development and GDP have maintained their effects on bank stability. Thus, these results establish the robustness of the results in Table ix.

7. Give-and-take of central findings

The demise of one bank has serious pervasive ramifications for the financial system in detail as well as the economy in general. The news that a banking company has become extinct triggers banking company panic which could transport the other banks in the industry tumbling. In the long run, customer confidence is lost resulting in low deposits and low investment. The cumulative upshot is that economic growth is stunted and the far-reaching implications are obvious. It is for this reason that after the 2007/2008 global fiscal crisis, the ongoing intellectual and policy fence has been whether or not policy-makers should constrain banking company size as a way of circumventing the recurrence of the crisis. As noted in the introduction to this paper, regulators in the Usa (under the Dodd Human action, 2010) and in the Eu [as in recommendations past the Liikanen (2012) implemented into EC law as well the recommendations past the Vickers Study (2011) implemented into Uk law] are making frantic efforts at constraining banking concern size by demanding more majuscule and liquidity in line with Basel Three requirements too as restricting banks' interest in riskier areas of action. These interventions have been occasioned by the testify that loose deregulation of the financial sector that fostered increasing bank size was largely responsible for the global financial crisis. The question that arises from the finding that size improves bank stability is, is the call for banking concern size moderation applicable to RCBs? To the extent that increasing bank size supports stability of RCBs, it is the contention of this newspaper that whatsoever endeavour to put some hurdles on the growth trajectory of RCBs in the name of size control may not augur well for them. They should exist given the necessary impetus to scale up their operations within the confines of prudential banking standards. They should exist allowed to grow insofar equally the growth is supported with adequate capitalization and liquidity.

The study has shown that funding risk supports bank stability. Thus, RCBs that are able to map out constructive strategies for mobilizing more deposits are likely to improve their stability. However, the task of mobilizing more deposits has always been daunting for RCBs because of their demarcated geographical areas of operation. RCBs offer financial intermediary services to the rural communities where abject poverty is endemic. This has made deposit mobilization challenging for them. One activity that could help the eolith mobilization drive is agriculture. Part of the rationale for introducing the RCBs was the facilitation of cocoa purchase in the rural cocoa growing areas through the special Akuafo cheque system. Unfortunately, owing to loftier illiteracy levels in the rural communities, most cocoa farmers are reluctant to receive payment for their cocoa yield through the system. Beyond the issue of illiteracy, authoritative processes of RCBs also undermine the smooth operation of the Akuafo Cheque system. Cocoa farmers have expressed misgivings virtually the processes they get through when they take Akuafo cheques. Their main complaint has been that there are rigmarole procedures at the banking halls of RCBs when they plough upwards to cash their cheques. Then to avoid the drudgery involved in cashing their cheques, they prefer taking cash at the point of sale to receiving cheques. The Full general Manager of one of the RCBs indicates that lack of conviction in the special Akuafo cheque organization coupled with increasing poverty in the rural communities has compelled about all RCBs to open branches ⁷ in the urban areas. The concern of many market place watchers and analysts is that the expansion of RCBs into the urban communities defeats the purpose for introducing the rural cyberbanking system as a special evolution banking model to promote rural financial intermediation. Is it plausible, on the footing of the current finding, to suggest that to ensure the sustainability of RCBs, regulators should officially allow them to spread their operations beyond their current rural domain? The respond is not farfetched. Judging from the fact that not much economic activity takes identify in the rural communities for which reason income levels of rural dwellers are low, the current rural banking model that restricts them to only rural areas is yearning for review. To avoid instability in the rural banking industry and its accompanying problems, information technology is the contention of this paper that the rural banking regulation should be amended to permit RCBs into the urban communities for more deposit mobilization to improve their stability. However, the extent to which a rural bank can aggrandize should exist conspicuously defined to avoid the horrors of over expansion. The decision to let RCBs into the urban centres should come with the caveat that a percentage of their loan portfolio should go into agriculture. Indeed, allowing RCBs to move into the urban areas with some restrictions will help rural communities because deposits mobilized in the urban centres could be offered as loans to rural dwellers that will become a long way to reduce rural poverty as well as boost agriculture which is the mainstay of the Ghanaian economy.

viii. Conclusion and policy implications

The purpose of this study is to examine the impact of bank size and banking concern funding risk on banking company stability with quarterly information (2009Q1–2013Q4) from the rural banking industry in Ghana. Console ordinary to the lowest degree squares regression technique with Fe has been used for assay. The study uses diversification, credit risk, liquidity gamble, profitability, aggrandizement, financial development and GDP equally command variables. The data provide robust evidence that both bank size and bank funding take chances positively bear on bank stability.

One policy implication of this study is that thought of constraining bank size as a way of safeguarding the financial arrangement that has been gathering increasing momentum since the 2007/2008 global financial crunch may non be in the best interest of RCBs in Ghana. This is because the written report has shown that increasing bank size leads to increasing stability. Information technology is, therefore, submitted that, within the parameters of prudential banking standards, RCBs should be encouraged to calibration up their operations.

To the extent that funding adventure supports banking concern stability, information technology is recommended that RCBs should intensify their deposit-mobilization efforts to meliorate their stability. Information technology is the position of this study that since client deposits are stability-supporting and income levels of rural communities are low, RCBs should be allowed to aggrandize into the urban areas where income levels are relatively higher. Doing this will ensure the stability of the RCBs and ultimately insulate the unabridged financial arrangement from any ills that emanate from bank collapse. Opening agencies in strategic locations besides as introducing innovative banking techniques such as depository financial institution on wheels strategy ^eight that will enable RCBs penetrate into hinterlands to reach out to the unbanked should be explored.

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Source: https://www.tandfonline.com/doi/full/10.1080/23322039.2015.1111489

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