“Impact of determinants of the financial distress on financial sustainability of Ethiopian commercial banks” Kishor Meher https://orcid.org/0000-0003-1294-7915 http://www.researcherid.com/rid/L-4260-2018 AUTHORS Henok Getaneh https://orcid.org/0000-0003-3740-890X ARTICLE INFO Kishor Meher and Henok Getaneh (2019). Impact of determinants of the financial distress on financial sustainability of Ethiopian commercial banks. Banks and Bank Systems, 14(3), 187-201. doi:10.21511/bbs.14(3).2019.16 DOI http://dx.doi.org/10.21511/bbs.14(3).2019.16 RELEASED ON Thursday, 10 October 2019 RECEIVED ON Saturday, 15 June 2019 ACCEPTED ON Friday, 13 September 2019 LICENSE This work is licensed under a Creative Commons Attribution 4.0 International License JOURNAL "Banks and Bank Systems" ISSN PRINT 1816-7403 ISSN ONLINE 1991-7074 PUBLISHER LLC “Consulting Publishing Company “Business Perspectives” FOUNDER LLC “Consulting Publishing Company “Business Perspectives” NUMBER OF REFERENCES NUMBER OF FIGURES NUMBER OF TABLES 48 0 7 © The author(s) 2019. This publication is an open access article. businessperspectives.org Banks and Bank Systems, Volume 14, Issue 3, 2019 Kishor Meher (India), Henok Getaneh (Ethiopia) BUSINESS PERSPECTIVES LLC “СPС “Business Perspectives” Hryhorii Skovoroda lane, 10, Sumy, 40022, Ukraine www.businessperspectives.org Received on: 15th of June, 2019 Accepted on: 13th of September, 2019 © Kishor Meher, Henok Getaneh, 2019 Kishor Meher, Ph.D., Professor, Department of Accounting and Finance, College of Business and Economics, Debre Berhan University, India. Henok Getaneh, M.Sc., Lecturer, Department of Accounting and Finance, College of Business and Economics, Debre Berhan University, Ethiopia. This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International license, which permits unrestricted re-use, distribution, and reproduction in any medium, provided the original work is properly cited. http://dx.doi.org/10.21511/bbs.14(3).2019.16 IMPACT OF Determinants of THE FINANCIAL DISTRESS ON FINANCIAL SUSTAINABILITY OF ETHIOPIAN COMMERCIAL BANKS Abstract The study aims to investigate the impact of determinants of financial distress on financial sustainability of Ethiopian commercial banks. The balanced panel data of 12 commercial banks of Ethiopia have been taken for the study from 2011 to 2017. The research deploys Ordinary Least Square (OLS) Regression Model. The indicators of financial distress are bank’s specific internals and macro-economic factors. The proxies of financial sustainability are Return on Assets, Return on Equity, Financial Stability Index and Bank Soundness. The findings reveal that the Absolute Liquidity Risk and Net Income Growth are found to be positive and significant and Solvency Risk negative and significant in relation to Return on Assets. Asset Quality is found to be positive and significant and Solvency Risk negative and significant with respect to Return on Equity. The Asset Quality and Net Income Risk are positive and significant and Solvency Risk is negative and significant with relation to the Financial Stability Index. Absolute Liquidity Risk and Liquidity Risk are positive and significant and Credit Risk negative and significant with Bank Soundness. Free Cash Flow and Net Income Growth are essential for enhancing Return on Assets and Bank Soundness, and managing equity within the prudential norms could bring forth short-term financial sustainability of commercial banks. By lowering provisioning of loan loss, Growth in Net Interest Income and managing Solvency Risk could ensure financial stability to the banks, which in turn leads to financial sustainability. The study reveals that financial sustainability of banks is insulated from the exposures of systematic risks originating from macroeconomic factors. Keywords financial intermediation, financial stability, banking crisis, corporate distress, financial ratios, risk management, firm performance, bankruptcy JEL Classification G21, G32, G33, L25, O16 INTRODUCTION The financial soundness of a country depends on a robust financial system that comprises a set of financial institutions, efficient financial markets, tradeable financial instruments and, after all, customer centric financial services. The nature and extent of financial crisis in the financial system depend on understanding the impact and likelihood of systemic risk (Allen et al., 2006). The evolution of stability of the world financial system emanates from the understanding of the systemic risk gravity. Bank distress poses as a reflection of systemic risk that acts as stumbling block on the economy or financial system as a whole (Bernanke, 2009). The financial institutions like banks and insurance companies act as mediation from savers to investors and channelize the cash flow from surplus to deficit economy and constantly thrive for balanced regional growth of a nation. The role of a banking sector is to utilize the resources judiciously that fuels economic growth and brings global competitiveness (Mwega, 2011). Efficient financial services in the banking sector could be achieved only through appropriate management of financial distress by the banks (Bariviera et al., 187 Banks and Bank Systems, Volume 14, Issue 3, 2019 2014). The prime cause of bankruptcy is due to bank distress when the bank is not able to meet the claims of the depositors that ultimately turn the ailing bank into bankruptcy due to lending to the low creditworthy borrowers having conflict of interest and macroeconomic instability (Brownbridge, 1998). The history of banking has been evolved way back in 1905 in Ethiopia by forming Bank of Abyssinia as a result of the memorandum of understanding between the then king Menelik-II and the National Bank of Egypt. Later on, the National Bank of Ethiopia was formed as the Central Bank in 1963 by a proclamation No. 206/1963. There are at present three Government banks and sixteen private banks operating in Ethiopia (NBE, 2017). Ethiopia is reeling on restricted domestic banking with the cluster of nationalized commercial banks comprising of public and private banks under the aegis of the National Bank of Ethiopia at present, and the country has not yet opened the entry of foreign banks to operate in the economy. In view of sluggish manufacturing sector, the Ethiopian economy becomes an import dependent economy coupled with incessant shortage of foreign currencies due to heavy import. Thus, the domestic money supply in circulation of economy is inadequate to sustain acceptable economic growth, which might turn the domestic banks succumbed to failure while obliging financial commitment to the creditors and depositors leading to financial distress. Alentina et al. (2009) have taken 389 banks in 41 Sub-Saharan Africa countries and observed that higher returns of assets are the results of high bank size, macro-economic stability and infusion of private capital into banking system. The Central bank of Ethiopia proclamation No. 592/2008 envisages that a bank is said to be designated as a situation of “receivership” instead of “bankruptcy” when the bank’s liabilities are found to be more than its assets (NBE, 2008). The symptomatic condition of financial institutions is financial distress that aggravates into insolvency. Taddese Lencho (2008) has concluded that the financial distress of a bank could initially lead to insolvency, which would be declared later to bankruptcy by a court of law. When a company experiences financial distress, operating conditions may deteriorate, heavy financial burdens become commonplace and wages are renegotiated downwards. If the situation continues, bankruptcy may become a reality (Garlappi & Yan, 2011). However, if appropriate management steps are taken and financial distress factors are used effectively, it can recover and experience a resurgence (Wang & Shiu, 2014). 1. LITERATURE REVIEW Empirical evidence of the researchers on the effect of external variables as well as firm specific variables acting as the determinants of financial distress on financial sustainability of commercial banks are discussed below. 1.1. Financial distress itors that ultimately results in bankruptcy (Tan, 2012). The various proxies of financial distress are important determinants of bank failure of any institution (Bergman et al., 2012). Hill et al. (2012) noted that the financial performance of a bank is influenced by variables of financial distress such as liquidity, size and leverage, etc. Khalid (2017) has divided the variables of financial distress into firm’s specific and external factors of a country. Aspachs et al. (2007) propose to assess the capacity of banks to assume risks based on a combination of the probability of default of banks and their profitability. The financial distress arises out of bank’s specific factors and macro-economic factors. The following literatures are discussed on the indicators of financial distress of commercial banks. When an institution is plagued by financial, managerial and operational malfunctions, it is said to be in financial distress. The financial institutions are engulfed in financial distress when these are involved in unethical business practices, facing shortage of adequate capital and meager deposit base. Thus low financial distress is an indication of better financial performance of the banks. The symptom of financial distress 1.1.1. Bank’s specific internal factors is manifesting in decreasing financial performance of a bank followed by inability to meet The internal determinants of financial distress payment obligation to the creditors and depos- are bank’s specific internal factors, viz: Absolute 188 http://dx.doi.org/10.21511/bbs.14(3).2019.16 Banks and Bank Systems, Volume 14, Issue 3, 2019 Cash Ratio, Cash Ratio, Net Income Growth, loss to the total loan and advances disbursed Asset Quality, Net Interest Risk, Credit Risk, and by the bank. The financial distress could be reSolvency Risk taken for the study. duced by better management of Asset Quality of loan portfolio due to lowest provision of loss • Absolute Liquidity Risk (CaR1) that brings financial stability to financial institutions. Carapeto et al. (2011) used non-perAbsolute Liquidity Risk is called Absolute Cash forming loan to total loan as a single accountRatio that can be measured by the total cash and ing variable that can be used to measure bank bank balance after deposit at the National Bank financial distress. Reinhardt (1999) noted that of Ethiopia divided by the demand deposits of the the weak banking sector in an economy is due bank customer. This ratio reveals the ability of the to excessive default risk taking leading to an inbank to meet immediate financial obligation aris- crease in the non-performing loans and chances ing out of the customers who will withdraw on of insolvency. demand. • Net Interest Risk (NIR) • Liquidity Risk (CaR2) Net Interest Risk is a default risk that acts as an Liquidity risk of a bank is called Cash Ratio that indicator of financial distress and depends on the can be measured by the quantum of total cash and paying capacity and regular paying habit of the bank balance divided by the total deposits by the borrowers. Net Interest Risk is measured by net customers. This ratio shows overall liquidity of a interest margin to the total loan and advances by bank to fulfil the financial obligation of the depos- the bank. itors. Ariffin (2012) noted that the relationship between liquidity risk and financial performance is • Credit Risk (CR) not always predicted by the conventional financial theory of “high risk-high return” and concluded The loan given to the borrowers out of the monthat liquidity risk always lowers ROA and ROE. ey of the depositors becomes a default risk and Ongore and Kusa (2013) have given an opposite an indicator of financial distress. The credit view that financial performance of Kenyan banks risk is measured by total loan and advances of is less affected by liquidity. the bank to the total deposits by the depositors. Adeolu (2014) asserted that management of asset • Net Income Growth (NIG) quality entails the evaluation of a firm’s assets to facilitate the measurement of credit risk asNet income growth indicates a situation of con- sociated with its operation to ensure profitabilistant growth of income of a bank that brings fi- ty resulting in improved financial performance. nancial sustainability of banks in the long run. Abdullah et al. (2014) observed that default Sultana and Akter (2015(2018) have noted that credit risk is inversely affecting the financial the loan growth ratio is the significant predictor performance of banks. of net income growth of the banking sector of Bangladesh. This study has calculated Net Income • Solvency Risk (SR) or Capital Adequacy Ratio Growth as excess of profit after tax between the (CAR) current years over the previous year to the profit after tax of the previous year. Capital Adequacy Ratio or Solvency Risk acts as cushion to prevent financial distress in case of • Asset Quality (AQ) non-repayment by the borrowers. The Capital Adequacy Ratio is measured by the total equity to The quality of loan and advances to the borrow- total loan and advances of the bank. Olalekan and ers by the banks depends on the extent of how Adeyinka (2013) posited that adequacy of capital much lowest loan loss provision done against the acts as primary capital to the assets given as loan loan and advances to smooth earning. Thus, as- and advances. They asserted that capital would be set quality is measured by the provision of loan used to absorb an unanticipated abnormal loss http://dx.doi.org/10.21511/bbs.14(3).2019.16 189 Banks and Bank Systems, Volume 14, Issue 3, 2019 in cases where such losses cannot be absorbed by earnings in financial institutions. Foggitt et al. (2017) proposed that the commercial banks should have enough capital reserve in order to mitigate the effect of financial crisis emanating from systemic risk. 1.1.2. Macroeconomic factors The external determinants of the study are macroeconomic factors such as General Inflation, GDP per Capita, Trade Deficit, Ending Exchange Rate and Lending Interest Rate. External factors are found to have a mixed relationship with bank’s sustainability. Some studies found a significant positive relationship, while some revealed the opposite and there are also studies that proved no relationship at all. Bennaceur and Goaied (2008) argued that macroeconomic factors do not have association with financial performance of banks. Owoputi et al. (2014) observed that endogenous factors like capital adequacy, bank size, productivity growth and deposits have a positive and significant effect on profitability. The performance of banks is not affected by credit risk and liquidity risk. The exogenous factors like inflation rate and interest rate have no influence on profitability of Nigerian banks. Other factors, such as the GDP or the economic growth, rate of interest and the nature of the financial system, are key parameters that are used to define the macro-economic environments (Berger et al., 2010). flation. Abdullah et al. (2014) noted that GDP and inflation rate are negatively associated with return on assets. • GDP per Capita (GDPC) GDP per Capita is the economic well-being of a nation. The real GDP per capita has been considered as one of variables for the study. Kosmidou et al. (2007) argued economic growth influences performance of banks positively, while Khwarish (2011) has found a negative relationship. Boubakri et al. (2005) observed that performance of banks significantly influences economic growth in 16 European countries, which is consistent with Althanasoglou et al. (2006) who studied on banks of Egypt. Increase in GDP growth has a linear effect on the profitability level of banks. • Trade Deficit (TD) Since Ethiopia imports most of goods for internal consumption for which there is always a deficit, the balance of trade account is observed in the balance of payment account. This study has taken Trade Deficit as an indicator of financial distress although no evidence is found in the literature. • Lending Interest Rate (LIR) Generally, the interest rate of a country affects the deposit and credit function of the bank and particularly the lending interest rate influences the profitability of banks. So lending interest rate has been taken for the study. Gull and Zaman • General Inflation (INF) (2013) evaluated the impact of interest rate fluctuations and financial outcomes of banking sector When a country is experiencing high inflation, the of Pakistan. Interest rate and other variables show purchasing power of the consumers has been di- significant association on profitability of banks of minished. Such situation brings sluggish econom- Pakistan. ic growth, which has a negative effect on the performance of a bank. General inflation of the coun- • Ending Exchange Rate (EER) try has been considered for the study. According to Vong and Chan (2006), inflation is shown to be The exchange rate of a country depends on the positive and significant with banks’ performance, demand and supply of foreign currencies that because when the inflation is high, the banks depend on export, import and foreign direct incharge high interest rate. However, Kosmidou et al. vestment bringing inflow of foreign currencies (2007) revealed that when inflation rate begins to to the country. Since Ethiopia consumes more increase, the loan transactions will start decrease. foreign currencies through import leading to Hence, there is an inverse association between in- trade deficit, ending exchange rate has been takflation and performance of a bank during high in- en for the study. 190 http://dx.doi.org/10.21511/bbs.14(3).2019.16 Banks and Bank Systems, Volume 14, Issue 3, 2019 1.2. Financial sustainability assets of a bank and acts as an indicator of sustainability of banks in the short run. Said and Tumin The financial sustainability of banks has been taken (2011) studied the financial performance of banks as a dependent variable. The proxies of financial sus- in Malaysia and China and observed that liquiditainability are Return on Assets, Return on Equity, ty risk and size of banks have no significant influFinancial Stability Index and Bank Soundness. The ence on return on assets of banks. financial sustainability can be measured from the short-term and long-term points of view. • Return on Equity (ROE) While Return of Assets and Bank Failure are the indicators of short-term financial position, the Financial Stability Index and Solvency Risk are meant to assess the long-term financial position. The Ethiopian commercial banks have deployed only equity capital that boosts the shareholders to expect adequate returns on their investment. • Financial sustainability of banks has a critical implication for economic well-being of any nation and it is generally considered to be the reflector of financial and economic conditions of a country other than its intermediation role in an economy (Ongore & Kusa, 2013). Financial sustainability factors are important drivers, which withstand risks facing the business. Strategic management and information management are thus required to take into account and evaluate information necessary in pursuing financial sustainability of an organization (Schaltegger, 2011). The classification proposed by Bardsen et al. (2006) has two large groups of definitions of financial stability. The first group includes definitions based on information characteristics where financial stability is applied to financial markets (Mishkin, 1999). As Ethiopia has no regulated financial market in the form of stock exchange as of now, the interpretation of the first group is not relevant for the study. The second group includes the works of Crockett (1996), Tsomocos (2003), where “financial stability” is used as an analogy to “financial sustainability”. Padoa-Schioppa (2003) has observed that financial sustainability in a financial system could tolerate and absorb the risks during the transition from savings and investments in the economy. This view is supported by Shinasi (2004), Kadomtsev and Israelyan (2015). Al-Shawabkeh and Kanungo (2017) posited that sustainability of a banking system could be improved by reassessing credit risks and improved decision making by the managers. • Return on Assets (ROA) The operating efficiency of a bank can be judged from the income arising out of utilization of total http://dx.doi.org/10.21511/bbs.14(3).2019.16 Financial Stability Index (FSI) Financial Stability Index (FSI) symbolizes the long-term sustainability of commercial banks. FSI is measured by a profit/risk (PR) indicator of a commercial bank with respect to total banking system. • Bank Soundness (BF) Free cash balance is calculated after deducting deposited case reserve at the National Bank of Ethiopia from total cash and bank balance held by banks. A bank is in the way to financial soundness when the free cash balance is sufficient to meet the demand deposits of the customers. If the free cash balance is less than demand deposits, then the bank is on the verge of financial distress leading to bank failure. The bank having financial soundness has been taken as zero, while the bank having bank failure has been taken as one in this study. Zhen (2015) has studied banks of OECD, NAFTA, Southeast Asian nations, G8, G20 countries and European Union and observed that asset quality, loan ratios and fixed assets were positive and significant with bank failure. Capital adequacy ratio and net interest income were negative and significant with bank failure. 1.3. Problem statement Although enough evidence of bank failure is available across the globe, there is scanty evidence of bank failure in Ethiopian banks in the past, although many banks suffer financial distress due to liquidity crunch. Most of the researchers in sub-Saharan Africa including Ethiopia and in the global context have studied the impact of var- 191 Banks and Bank Systems, Volume 14, Issue 3, 2019 ious indigenous and exogenous factors on profitability of banks and very few study have been observed in terms of financial stability as well as financial sustainability of banks. The present study thrusts upon the firm specific factors leading to financial distress and some systematic risk factors from Ethiopian economy reflected as macroeconomic factors leading to financial distress and their ultimate influence on the financial sustainability of Ethiopian banks. Therefore, the study aims to identify and evaluate the effect of firm specific indicators of financial distress and macroeconomic variables on the financial sustainability of banks. H1: There is an association between internal determinants of financial distress and financial sustainability of commercial banks. H0: There is no association between external determinants of financial distress and financial sustainability of commercial banks. H1: There is an association between external determinants of financial distress and financial sustainability of commercial banks. • The aim of the study is to identify the various proxies of financial distress and evaluate their association with financial sustainability of Ethiopian • commercial banks. The following hypotheses are framed to carry out the analysis. • 1.4. Hypotheses H0: Internal determinants: Liquidity Risk, Absolute Liquidity Risk, Net Income Growth, Asset Quality, Net Interest Risk, Credit Risk, Solvency Risk. External determinants: Trade Deficit, GDP per Capita, General Inflation, Ending Exchange Rate, Lending Interest Rate. Financial Sustainability: Return on Assets, Return on Equity, Financial Stability Index, Bank Soundness. There is no association between internal de- The proxies of financial distress and financial susterminants of financial distress and financial tainability are described with formulae and symsustainability of commercial banks. bols shown in Table 1. Table 1. List of variables and their proxies and symbols Name Symbol Dependent variables Return on Assets Return on Equity ROA ROE Bank Soundness BS Financial Stability Index FSI Proxies of financial sustainability Profit before Tax to Total Assets Profit after Tax to Total Equity If free cash flow > demand deposits = 0 (bank soundness) If free cash flow < demand deposits = 1 (bank failure) Free cash flow = total cash & bank balance – reserve with central bank (NBE) Profit before Tax X Total Loan & Advances X Total Assets of the individual bank divided by Total Assets of the banking system; R = EQ/CAR, where R = Risk Weighted Assets, CAR = Capital Adequacy Ratio PR = PBT/R, where PR = Profit/Risk Indicator of Individual bank, PBT = Profit before Tax; FS I= PR·A/TA, where A = Assets of banks in particular year, TA = Total assets of the banking system Proxies of firm’s specific factors of financial distress Independent variables Absolute Liquidity Risk CaR1 Net Income Growth NIG Liquidity Risk Asset Quality Net Interest Risk Credit Risk Solvency Risk/Capital Adequacy Ratio CaR2 AQ NIR CR Free cash flow to demand deposits Free cash flow = total cash and bank balance – reserve with the National Bank of Ethiopia (Profit after tax of the current year – profit after tax of the previous year) to profit after tax of previous year Total Cash & Bank Balance to Total Deposits of the bank Provision for Loan Loss to Total Loan & Advances Net Interest Income to Total Loan & Advances Total Loan & Advances to Total Deposits SR/CAR It denotes Capital Adequacy ratio measured by Total Equity to Total Loan & Advances. 192 http://dx.doi.org/10.21511/bbs.14(3).2019.16 Banks and Bank Systems, Volume 14, Issue 3, 2019 Table 1 (cont.). List of variables and their proxies and symbols Name Symbol Independent variables Trade Deficit GDP per Capita General Inflation Ending Exchange Rate Lending Interest Rate TD GDPC INF EER LIR Macroeconomic factors Natural log of Trade Deficit has been taken Trade Deficit = Import – Export GDP per Capita of the people of the country has been taken Consumer Price Index of the country has been taken Closing Exchange Rate of the year has been taken Average Lending Interest Rate of banks has been taken 2. RESEARCH METHODS Income Growth (NIG), Inflation (INF), Real GDP per Capita (GDPC), Trade deficit (TD), Ending Exchange Rate (EER), Lending Interest Rate (LIR). The research has been designed to implement quantitative and inferential approach. The population of commercial banks consists of 19 banks, which includes three Government and 16 private commercial banks. Convenience sampling is adopted to select sample based on availability of financial data since inception. Balanced panel data of a sample of 12 banks have been taken for the study from the annual reports of individual banks for the period from 2011 to 2017. Hutcheson and Sofroniou (1999) stated that when the regression model comprises both continuous and dummy variables, Ordinary Least Square (OLS) is a suitable statistical technique. This study has deployed the OLS regression Model comprising pooled regression and fixed effect regression analysis done by R Studio. The model specification of the regression model balanced panel data is described below: Yit = β 0 + β1 X it + € it , (1) i 1... N , t 1...T , = = where i stands for the ith cross-sectional unit and t for the tth time period, β0 is the intercept for each entity, Yit is the dependent variable, where, i = entity and t = time, Xit represents one independent variable, β1 is the coefficient for that independent variable, €it is the error term. The regression model is specified as follows with financial sustainability as the dependent variable whose proxies are Return on Assets (ROA), Return on Equity (ROE), Bank Soundness (BS) and Financial Stability Index (FSI). The proxies of financial distress as independent variables are Absolute Liquidity Risk (CaR1), Liquidity Risk (CaR2), Asset Quality (AQ), Net Interest Risk (NIR), Credit Risk (CR), Solvency Risk (SR), Net http://dx.doi.org/10.21511/bbs.14(3).2019.16 ROAit = β 0 + β1CaR1it + β 2 NIGit + + β3CaR 2it + β 4 AQit + β5 NIRit + + β 6CRit + β 7 SRit + β8 TDit + (2) + β9GDPCit + β10 INFit + β11 EERit + + β12 LIRit + € it , ROEit = β 0 + β1CaR1it + β 2 NIGit + + β3CaR 2it + β 4 AQit + β5 NIRit + + β 6CRit + β 7 SRit + β8 TDit + (3) + β9GDPCit + β10 INFit + β11 EERit + + β12 LIRit + € it , β 0 + β1CaR1it + β 2 NIGit + FSI it = + β3CaR 2it + β 4 AQit + β5 NIRit + + β 6CRit + β 7 SRit + β8 TDit + (4) + β9GDPCit + β10 INFit + β11 EERit + + β12 LIRit + € it , β 0 + β1CaR1it + β 2 NIGit + BSit = + β3CaR 2it + β 4 AQit + β5 NIRit + + β 6CRit + β 7 SRit + β8 TDit + (5) + β9GDPCit + β10 INFit + β11 EERit + + β12 LIRit + € it. 3. RESULTS AND DISCUSSION At first, the study has used serial correlation test to find serial correlation between dependent and independent variables and then the OLS Regression Model has been applied, which includes Pooled Regression and Fixed Effect Regression Model. 193 Banks and Bank Systems, Volume 14, Issue 3, 2019 Then PF test has been conducted to find the supe- H1: Fixed Effect Model is appropriate. riority of one model over another. Table 3. PF test between pooled and fixed effect regression models 3.1. Serial correlation test Source: Developed by authors based on the R Studio analysis. In order to test the relationship amongst the varVariables F-value DF1 DF2 P-value iables, a serial correlation test has been deployed Return on Assets (ROA) 0.28247 –1 71 NA using the Durbin-Watson test for serial correlaReturn on Equity (ROE) 0.008106 –1 71 NA tion in panel data. The test is applied for each Financial Stability Index (FSI) 0.073365 –1 71 NA dependent variable with all the independent var- Bank Soundness (BS) 2.1927e-05 –1 71 NA iables and the result of the test has been shown In all these cases, null hypothesis is rejected in Table 2. as p-value is not applicable. Hence, fixed effect Table 2. Serial correlation test amongst the model is appropriate in all the cases; fixed effect variables Regression Model is applied for all the dependent Source: Developed by authors based on the R Studio analysis. variables. DurbinWatson test P-value Return on Assets (ROA) 2.1956 0.8932 Return on Equity (ROE) 2.7396 0.9998 Variables Financial Stability Index (FSI) 2.4582 0.9837 Bank Soundness (BS) 2.4659 0.9852 3.2.1. Return on Assets (ROA) The Fixed Effect Model is applied by regressing Return on Assets with all the bank’s specific factors and macroeconomic factors and the result is shown in Table 4. Table 4 reveals the fixed effect regression results where F-statistics shows that p-value is fully significant. That shows robustness of a model of good fit. Absolute Cash Ratio being a proxy of H0: There is no serial correlation amongst the Absolute Liquidity Risk is found positive and variables in error terms. significant with Return on Assets at 5% as p-value is less than 0.05. The Net Income Growth is H1: There is a serial correlation amongst the var- significant and has positive association with iables in error terms. Return on Assets at 1% as p-value is less than 0.01. The Capital Adequacy Ratio being the Table 2 reveals that p-value is more than 5% (0.05) proxy of Solvency Risk is fully significant but in all cases. Null hypothesis is rejected, which im- establishes negative association with Return on plies that there is no serial correlation between the Assets as p-value is less than 0.001. The Return dependent and independent variables. on Assets is not influenced by macroeconomic factors. Further, R-square reveals that Return 3.2. OLS regression analysis on Assets is explained by 34.5% of bank’s specific factors that include Absolute Liquidity OLS Regression Model is applied to regress each Risk, Net Income Growth and Solvency Risk. dependent variable with all the independent variables in which pooled and fixed effect model are de- The findings of the Fixed Effect Regression Model ployed. Then PF test has been resorted to evaluate reveal that the increase in operating efficiency of appropriateness between pooled and fixed effect banks reflecting through Return on Assets demodels (see Table 3). The hypothesis for the PF test pends on adequate free cash flow accessible for the for each dependent variable with all the independ- business to meet immediate financial obligation ent variables are framed below. from the demand depositors. The Return on Assets increases when there is growth in net profit after H0: Pooled Model is appropriate. tax year after year. Further, Solvency Risk can be The hypotheses for each dependent variable with all independent variables are framed below. 194 http://dx.doi.org/10.21511/bbs.14(3).2019.16 Banks and Bank Systems, Volume 14, Issue 3, 2019 Table 4. Fixed effect regression model on Return on Assets Source: Developed by authors based on the R Studio analysis. Balanced panel n=7 T = 12 N = 84 Min 1st Qu Median 3rd Qu Max –0.02458439 –0.00414773 –0.00048076 0.00317376 0.02917991 Variables Estimate Std. error t-value Pr ( > |t|) CaR1 0.0037131 0.0017447 2.1282 0.036843* NIG 0.0053213 0.0016705 3.1856 0.002158** CaR2 –0.0028126 0.0027874 –1.0090 0.316435 AQ 0.0123656 0.0429208 0.2881 0.774119 NIR –0.0327358 0.0502013 –0.6521 0.516478 CR 0.0036924 0.0043124 0.8562 0.394801 SR –0.0299591 0.0064397 –4.6522 1.508e-05*** 0.001*** 0.01** 0.05* ? Sig. code Total sum of squares: 0.0079619 Residual sum of squares: 0.0052121 R-squared: 0.34536 Adj. R-squared: 0.22379 F-statistic: 5.27568 on 7 and 70 DF, p-value: 7.157e-05 Note: *, **, *** denote levels of significance at 5%, 1% and 0.01%, respectively. minimized by deploying equity capital in secur- Table 5 shows the model of good fit as F-statistics ing more loan portfolio that would accelerate more shows that p-value is fully significant. Return on Assets. The Return on Assets is not found to be affected by the macroeconomic factors. Asset Quality being a proxy of non-performing loan is showing significant and positive association with Return on Equity at 1% as p-value is less 3.2.2. Return on Equity (ROE) than 0.01. Capital Adequacy Ratio being a proxy Return on Equity is regressed with bank’s specific of Solvency Risk is fully significant but shows negfactors and macroeconomic factors. The result is ative association with Return on Equity as p-valshown in Table 5. ue is less than 0.001. The Return on Equity is exTable 5. Fixed effect regression model on Return on Equity Source: Developed by authors based on the R Studio analysis. Balanced panel: n=7 T = 12 N = 84 Min 1st Qu Median 3rd Qu Max –0.216519 –0.043777 –0.016162 0.017400 0.349480 Pr ( > |t|) Estimate Std. error t-value CaR1 –0.018642 0.019885 –0.9375 0.351734 NIG 0.025273 0.019039 1.3274 0.188680 CaR2 –0.028750 0.031769 –0.9050 0.368584 AQ 1.389643 0.489193 2.8407 0.005891** 0.505737 Variables NIR 0.382747 0.572173 0.6689 CR 0.015247 0.049151 0.3102 0.757324 SR –0.416984 0.073397 –5.6812 2.834e-07*** 0.001*** 0.01** 0.05* Sig. code Total sum of squares: 1.4208 Residual sum of squares: 0.67708 R-squared: 0.52345 Adj. R-squared: 0.43494 F-statistic: 10.984 on 7 and 70 DF, p-value: 2.8187e-09 Note: *, **, *** denote levels of significance at 5%, 1% and 0.01%, respectively. http://dx.doi.org/10.21511/bbs.14(3).2019.16 195 Banks and Bank Systems, Volume 14, Issue 3, 2019 Table 6. Fixed effect regression model on Financial Stability Index Source: Developed by authors based on the R Studio analysis. Balanced Panel: n=7 T = 12 N = 84 Min 1st Qu Median 3rd Qu Max –0.0251336 –0.0093082 –0.0032716 0.0057468 0.0558687 Variables Estimate Std. Error t-value Pr ( > |t|) –0.00099335 0.00334032 –0.2974 0.76706 CaR1 NIG –0.00218459 0.00319817 –0.6831 0.49681 CaR2 –0.00445787 0.00533657 –0.8353 0.40637 AQ 0.45653150 0.08217394 5.5557 4.674e-07*** NIR 0.19785509 0.09611275 2.0586 0.04326* CR –0.00053485 0.00825633 –0.0648 0.94853 SR –0.02561388 0.01232914 –2.0775 0.04142* 0.001*** 0.01** 0.05* Sig. code Total sum of squares: 0.037916 Residual sum of squares: 0.019105 R-squared: 0.49613 Adj. R-squared: 0.40255 F-statistic: 9.84631 on 7 and 70 DF, p-value: 1.7473e-08 Note: *, **, *** denote levels of significance at 5%, 1% and 0.01%, respectively. plained by 52.3% of bank’s specific factors, which The Solvency Risk is significant but shows a negainclude Asset Quality and Capital Adequacy Ratio. tive association with the Financial Stability Index at 1% as p-value is less than 0.01. The results demonstrate that the shareholders expect more returns on investment in equity due to The Financial Stability Index is explained by 49.6% better Asset Quality resulting from creating low- with the firm’s specific factors that include Asset est provision of loan loss against loan and advanc- Quality, Net Interest Risk and Capital Adequacy es. Further, in order to stay with long-term sus- Ratio. tainability of banking business while maximizing the profit for the shareholders, the banks should The Financial Stability Index being a proxy of have lowest solvency risk by way of minimum eq- financial sustainability of banks is dependent uity buffer as per the norm against the loan and on low financial distress resulting from better advances. The Return on Equity is not found to be management of loan portfolio by way of lowest affected by the macroeconomic factors. provisioning of loss resulting from non-performing assets. Although Net Interest Risk is 3.2.3. Financial Stability Index (FSI) inviting default risk by increasing the loan portfolio, such increased risk is coupled with the The Financial Stability Index is regressed with increase in net interest margin that paves that bank’s specific factors and macroeconomic factors way to strengthen the financial stability index. and the result is shown in Table 6. Although financial stability of banks depends on Capital Adequacy Ratio of banks that miniTable 6 demonstrates the robustness of a model mizes the Solvency Risk by way of keeping preof good fit as F-statistics show that p-value is fully scribed minimum equity so that the balance eqsignificant. The Asset Quality is positive and fully uity could be deployed into investment in loan significant with the Financial Stability Index as portfolio, which in turn leads to financial susp-value is less than 0.001. The Net Interest Risk tainability of commercial banks. The Financial is positive and significant with the Financial Stability Index is not found to be affected by Stability Index at 1% as p-value is less than 0.01. macroeconomic factors. 196 http://dx.doi.org/10.21511/bbs.14(3).2019.16 Banks and Bank Systems, Volume 14, Issue 3, 2019 Table 7. Fixed effect regression model on Bank Soundness Source: Developed by authors based on the R Studio analysis. Balanced Panel n=7 T = 12 N = 84 Min 1st Qu Median 3rd Qu Max. –0.640830 –0.191690 0.034878 0.201533 0.649184 Variables Estimate Std. Error t-value Pr(>|t|) CaR1 –0.557649 0.058434 –9.5432 2.69e-14*** NIG 0.080270 0.055948 1.4347 0.15581 CaR2 0.185540 0.093356 1.9874 0.05079* AQ –0.935003 1.437522 –0.6504 0.51755 NIR 2.171431 1.681362 1.2915 0.20079 CR –0.280976 0.144433 –1.9454 0.05575* SR –0.303890 0.215682 –1.4090 0.16327 0.001*** 0.01** 0.05* Sig. code Total sum of squares: 16.583 Residual sum of squares: 5.8467 R-squared: 0.64744 Adj. R-squared: 0.58196 F-statistic: 18.3638 on 7 and 70 DF, p-value: 1.2277e-13 Note: *, **, *** denote levels of significance at 5%, 1% and 0.01%, respectively. 3.2.4. Bank Soundness (BS) free cash flow is being maintained as a safeguard against demand deposits, bank failure would be The Bank Failure is regressed with bank’s specific reduced. On the other hand, availability of surplus factors and macroeconomic factors and the result cash by way of enough liquidity more than total deposits brings more bank failure, because the banks is shown in Table 7. would be unable to earn income from idle surplus Table 7 reveals the model of good fit as F statistics cash just because they want to pay the financial show significant p-value. The Cash Ratio (CaR1) obligation to the depositors. In other words, bank being a proxy of Absolute Liquidity Risk is nega- soundness can be achieved by deploying surplus tive and fully significant with Bank Soundness as cash in securing more loan portfolio. p-value is less than 0.001. Further, the Cash Ratio (CaR2) being a proxy of liquidity risk is significant More investment in loan portfolio brings more debut positively associated with Bank Soundness at fault risk, which in turn lead to bank failure. In 5% as p-value is less than 0.05. The Credit Risk be- other words, the bank should keep the default risk ing a proxy of default risk is positive and signifi- arising from loan and advances kept to minimum, cant with Bank Failure at 5% as p-value is less than which would result in low financial distress and 0.05. The Bank Soundness is explained by 64.7% minimize the probability of consequent bank failof the bank’s specific factors of financial distress, ure and maximize the chance of bank soundness. which include absolute Liquidity Risk, Liquidity Bank soundness is not found to be affected by the Risk and Credit Risk of the loan portfolio of com- macroeconomic factors. mercial banks. The findings reveal that the proxies of financial The results have shown that more bank failure sustainability of commercial banks in Ethiopia could be imminent if the absolute liquidity risk are insulated from the systematic risk emanating would be kept at high resulting in inability of from macroeconomic factors. This result is found banks to pay off the immediate demand obliga- consistent with Bennaceur and Goaied (2008), tions of the customers. In other words, when more Owoputi et al. (2014). http://dx.doi.org/10.21511/bbs.14(3).2019.16 197 Banks and Bank Systems, Volume 14, Issue 3, 2019 CONCLUSION At the outset, Durbin-Watson test does not find serial correlation amongst the variables. PF test reveals that fixed effect model is appropriate for the study. The Return on Assets and Bank Soundness representing short-term financial sustainability of banks reveal that the contribution of consistent income growth year after year, management of absolute free cash to meet the demand of depositors and maintaining minimum equity capital as per the prudential norms of the Central Bank have a tremendous effect on the Return on Assets growth. While absolute free cash could be adequately kept to reduce probability of financial distress vis-a-vis bank failure, total cash and bank balance should be kept minimum by deploying the surplus cash in securing loan portfolio having low default risk that maximizes the chance of bank soundness, which in turn accelerates the financial sustainability of commercial banks. The Return on Equity and Financial Stability Index representing long-term financial sustainability of commercial banks demonstrate that lowest provision of loan loss ensures better Asset Quality of loan leading to low financial distress. So better Asset Quality ensures quick and timely payment of interest by the borrowers bringing more Return on Equity, which has continuing effect on financial sustainability of banks. Secondly, although low Capital Adequacy Ratio invites more financial distress by way of Solvency Risk, it triggers the equity capital to be invested in the business for greater return on equity and its ripple effect on sustainability of banks in the long run. So more equity capital deployed in the banking business by keeping minimum equity as per the norms (at present 8%) would bring more returns to the shareholders. The contribution of Net Interest Income and Asset Quality ensuring timely payment of interest by the borrowers will strengthen the Financial Stability Index. Further, keeping aside equity to ensure solvency position of banks and deploying balance fund in loan and advances will improve the Financial Stability Index, which in turn accelerates the financial sustainability of commercial banks. The study is not free from the following limitations. Since the banks have relied on equity capital and no debt finance is involved in the business, the financial leverage being an important indicator of financial distress affecting financial sustainability argued by Meher and Ajibie (2018) has been excluded from the study. Another important macroeconomic indicator called economic cycle has been excluded due to unavailability of relevant data. Since the financial sustainability of banks is insulated from the perils of systematic risk arising from macroeconomic variables, the managers continuously strive to create strategy to lower the financial distress through professional management practice in selecting the right borrowers having adequate creditworthiness that would maximize the profit as well as the wealth of the shareholders. The research findings have thrown challenges to the policy makers and regulators to tight rope the banking regulations from the shock of financial distress by enforcing prudential norms on adequate funding and deposit base. ACKNOWLEDGMENT The authors express thanks to the officials of the banks who have supplied the hard copies of their annual reports, as some reports are not found on their web sites. 198 http://dx.doi.org/10.21511/bbs.14(3).2019.16 Banks and Bank Systems, Volume 14, Issue 3, 2019 REFERENCES 1. 2. 3. 4. 5. 6. 7. Abdullah, M., Parvez, K., & Ayreen, S. (2014). Bank specific, industry specific and macroeconomic determinants of commercial bank profitability: a case of Bangladesh. World Journal of Social Science, 4(3), 82-96. Retrieved from https:// www.researchgate.net/publication/320930850_Bank_Specific_ Industry_Specific_and_Macroeconomic_Determinants_of_Commercial_Bank_Profitability_A_ Case_of_Bangladesh Adeolu, M. (2014). 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