Examining Internal Factors That Affect Banks Performance Through Panel Regression Analysis *

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1 Journal of Modern Accounting and Auditing, ISSN March 2011, Vol. 7, No. 3, Examining Internal Factors That Affect Banks Performance Through Panel Regression Analysis * Ekşi İbrahim Halil, Özçalıcı Mehmet, Büyükkonuklu Buket Kilis 7 Aralik University, Turkey The importance of banks which constitutes the main structure of the financial system increased with globalization on the both sides of country and firm. Factors that affect banks performance can be macroeconomic or internal factors relevant with banks. In this study, different internal factors that can have an impact on banks profitability are examined with panel data analysis. The dataset which include 22 private, state or foreign owned deposit banks provided from the Association of Turkish Banking. Data contains the period between Equity profitability has been chosen as dependent variable. Independent variables are market share and number of branches. According to the regression results, market share and number of branches has positive and significant effect on profitability. Keywords: profitability, number of branches, market share, panel data Introduction Banks play an important role in Turkey s financial system. When we look at the composition of Balance Sheet of the Financial Sector we can see that a huge part (88.2 %) belongs to banks. In this context the health of banks has a crucial importance for Turkey economy. By September 2009, of the 49 banks in the Turkish banking sector, 32 are deposit banks, 13 are development and investment banks and 4 are participation banks. This is pointing the prevalence of deposit banking in the Turkish banking sector (Financial Stability Report, 2009). Empirical Studies Regarding Bank Performance Based on Bank Profitability Berger (1995) found a strong positive relationship between return on equity (ROE) and Equity/Total Assets, using banks performance variables as ROE, return on assets (ROA) and net interest margin. Naceur and Goaied (2001) determined that good performer banks labor and capital efficiencies are higher, deposit accounts volume is higher relative to income earning assets and they increase their equity or enhanced equity with undistributed profit. Türker (2002) researched Turkish banking sector profitability determinants using panel data including the periods Two-step approach are applied to measure the relative importance of the micro and the macro elements to determine the profitability. Within the micro determinants: capital, liquidity, personnel * This research originally presented in International Conference on Social Sciences 2010 and revised for this journal. Ekşi İbrahim Halil, assistant professor, Department of Business and Administration, Kilis 7 Aralik University. Özçalıcı Mehmet, research assistant, Department of Business and Administration, Kilis 7 Aralik University. Büyükkonuklu Buket, research assistant, Department of Business and Administration, Kilis 7 Aralik University.

2 EXAMINING INTERNAL FACTORS THAT AFFECT BANKS PERFORMANCE 311 expenditures, deposits and market share are found to have a significant influences on net interest margins. Among the macro variables, inflation and budget deficits have significant effect on net interest margins. At the end of the analysis results concluded that capital, liquidity, personnel expenditures, loans, non-performing loans and deposits are the micro determinants of return on assets (ROA). The findings of her study also revealed that, the most important contributors of return on equity (ROE) are capital, securities portfolio, liquidity, personnel expenditures, loans, deposits and market share. The most extensive research about this subject belongs to Demirgüç and Huizingha (1998). These two researchers tried to explain the interest spread and profitability components using 80 countries data during the period of In their study, macro-economic variables, taxing, banking regulations, financial structure and legal criterion are used as variables. They found that when bank assets/gdp ratio increases and bank concentration rate decreases, banks interest spread and profitability declined. In developing countries foreign banks are more profitable than national banks whereas in developed countries that relationship reverses. Methodology In the bank profitability literature, panel data analysis was used nearly in all of the studies (Türker, 2002; Demirhan, 2009; Naceur & Goaied, 2001; Kosmidou, Tanna, & Pasioura, 2003; Karaca & Uğur, 2008; Hirtle, 2007). In this study similar to literature, the variables that have impact on profitability will be investigated with panel data analysis. Panel Data In economic researches different data types can be used such as time series, cross section data and time series-cross section data. Panel data is a method using to estimate the economic relationship with cross section series which has time dimension. Panel data is a data set where there are time series which belong to multiple sections. When every section has equal length time series we call them balanced panel data and when time series length differ among sections we call them unbalanced panel data (Atalay, 2007). Simple function of panel data is: Y it = α + β it X it + + β it X it + e it (i=1,2,3,,n; t=1,2,,k) (1) In Equation (1), i stands for section whereas t for time. In this Equation, there is an individual effect (which includes properties that belong to sections but don t change with time) can t be observed with independent variables and there is an error term including different properties that belong to different units. These kinds of models are known as one-way error component regression models (Baltagi, 2005). Error term in most of the studies is shown as follows: e it = μ i + ν it (2) μ i in Equation (2) is individual effect and changes from section to section without depending on time. ν it can change with both time and section. So μ i shows un-observable section effect, ν it shows stochastic error term. One-way error component models consist of with only section effect and stochastic error terms. Models which include unobservable time effects are two-way error component regression models. Two-way error component regression models can be shown as this: e it =μ i +λ t + v it (3)

3 312 EXAMINING INTERNAL FACTORS THAT AFFECT BANKS PERFORMANCE In Equation (3), λ t is a variable that effects whole sections and belongs to only one time zone and cannot be expressed by other variables. With these assumptions λ t stands for unobservable time effect (Özer & Çiftçi, 2009, p. 4). One and two way error component models are divided into two groups depending on assumptions individual and time effects on the error term. when one way error term is predicted the individual effect, and when two-way error term both individual predicted and term effects assumed as the fixed effects that have to be predicted, the model is named fixed effect models. The other model is random effect model (Atalay, 2007, p. 48). In fixed effect models it is assumed that μ i is fixed which stands for unobservable horizontal section effects, v it has zero mean and has normal distribution with fixed variance. In this model, we got n equation with some slope but different intersection point. As a result fixed effect method allows a flexible expression of the heterogeneity between sections (Şimşek, 2008, p. 226). In the random effect model, differences on units or units and time are including in the model as components of error term, because preventing the loss of degree of freedom. In the random effect model it is important to find special error components which belong to unit or unit and time rather than finding special parameters which belong to unit or unit and time. Moreover in the random effect model, it is taking into account the effects that come from outside of sample as well the effects of observable sample section, units and time (Pazarlioğlu & Gürler, 2007). Hausman Test Hausman test was used to determine whether to use fixed effect (predicting different coefficient for each country on data set) or random effect (predicting different coefficient for each country in dataset in a randomly manner) for datasets which includes short time section or has similar properties. Hausman (1978) tested the relationship between independent variables and changeable effects on horizontal sections. If null hypothesis rejected fixed effects model will be chosen, otherwise random effect models (Nart, 2010). Data Set In our study we used annual data of 22 deposit banks (state or private) in Turkey between the years The data are obtained from the web site of the Banks Association of Turkey. Banks investigated in study are given in Table 1. Dependent variable of our study is net profit/total shareholders equity ratio. In literature, it can be seen that profitability variables are used as the measure of performance. In the previous studies investigating banks profitability, independent variables are generally classified into two groups namely internal and external factors. External factors can be macro factors such as inflation, interest, GDP. Capital adequacy, asset quality, liquidity, asset volume, market share and risk levels are taken as internal factors. In this study, banks market share and number of branches are chosen as independent variables. The variables and definition used in this study is as follow: PE: Net profit/total shareholders equity (%); MS: Market share of banks in overall deposits (%); NB: Number of branches of bank at the end of relevant year (number); From this point, two regression models between profitability and independent variables are as follows:

4 EXAMINING INTERNAL FACTORS THAT AFFECT BANKS PERFORMANCE 313 Model 1: PE it = α + β it MS it + e it (4) Model 2: PE it = α + β it NB it + e it (5) In Equations (4) and (5), i and t stand for banks and years respectively. e it is error term. Main Empirical Results The investigated banks: mean and standard deviation values for each bank are given in Table 1. Table 1 Banks and Descriptive Statistics Banks PE MS NB Mean Std. error Mean Std. error Mean Std. error Ziraat Bankası , Halk Bankası Vakıflar Bankası Adabank Akbank Alternatif Bank Anadolubank Şekerbank Tekstil Bankası Turkish Bank TEB Garanti Bankası İş Bankası Yapı Kredi Bankası Arap Türk Bankası Citibank Denizbank Deutsche Bank Finans Bank Fortis Bank HSBC Bank Eurobank Tekfen Before solving the model, Hausman Test was used to determine which method will be used. Hausman model determining test indicated to use fixed model. Model 1 s predicting results between profitability variable and market share are shown in Table 2. Table 2 Regression Analysis Results for Model 1 Variables Coefficient Std. error t-statistic Prob. C MS a R-squared F-statistic Prob(F-statistic) Note. a : at 1% critical level.

5 314 EXAMINING INTERNAL FACTORS THAT AFFECT BANKS PERFORMANCE Results indicate that market share variable has positive and statistically significant effect on profitability. R-squared value which represents the models explanatory power is 43%. That means 43% of dependent variables (in here profitability) is explained by independent variable. It is important to have a high R 2 value to put the meaningful of models. Probability F-statistics represents that overall variables have statistically significance at the 1% level. Before solving the second model we used Hausman test too. Hausman result indicated that random effect model has to be used. Second model s predictive results, between banks profitability variable and number of branch variables are shown in Table 3. Table 3 Regression Analysis Results for Model 2 Variables Coefficient Std. error t-statistic Prob. C NB b R-squared F-statistic Prob(F-statistic) Note. b : at 5% critical level. At the regression, number of branch variable has positive and statistically meaningful effect on profitability. But R 2 which stands for the models explanatory power is 3%. That is a very low level. So we can say that number of branch doesn t have strong impact on profitability. Conclusion This study executes with the annual data belong to private, state and foreign owned 22 deposit banks between the years Number of branches and market shares effect on bank profitability is investigated. Net profit/equity ratio is used as bank performance indicator. Hausman model determining test was used. Result of the test indicates that fixed model is suitable for market share and profitability model whereas random effect model is suitable for number of branches and profitability model. At the end of the analysis, positive and significant relationship is found between the number of branch-bank performance and market share-bank performance. Market share and bank performance relationship is positive and statistically significant. The explanatory power is relatively low for number of branches and bank profitability. We think that is because when banks increase their number of branches they will have to undertake new costs and that will decrease the profitability. References Atalay, S. S. (2007). Reel Convergence on New European Countries and Turkey (Central Bank of the Republic of Turkey Expertise Sufficiency Thesis). Baltagi, H. B. (2005). Econometric analysis of panel data third edition. West Sussex, England: John Wiley & Sons Ltd. Berger, A. (1995). The relationship between capital and earnings in banking. Journal of Money, Credit, and Banking, 27(2). Demirgüç K. A., & Huizinga, H. (1998). Determinants of commercial bank interest margins and profitability: Some international evidence. (Policy Research Working Paper 1900).

6 EXAMINING INTERNAL FACTORS THAT AFFECT BANKS PERFORMANCE 315 Demirhan, A. (2009). The Analysis of sector share change of the banks by panel data model with qualitative dependent variable. Journal of Managerial Economics and Management, 64, ( Central Bank of the Republic of Turkey-Financial Stability Report. (2009, October). Hausman, J. A. (1978). Specification tests in econometrics. Econometrica, 46(6), Hirtle, B. (2007). The impact of network size on bank branch performance. Journal of Banking & Finance, (31), Karaca, S. S., & Uğur, A. (2008). Risk and profitability analysis in Turkey in Banking Sector. Accounting Academicians Collaboration Foundation ( Kosmidou, K., Tanna, S., & Pasiouras, F. (2003). Determinants of profitability of domestic UK commercial banks: Panel evidence from the period (Conventory University Business School Applied Research Working Paper Series, RP08-4). Naceur, S. B., & Goaied, M. (2001). The determinants of the Tunisian deposit banks performance. Applied Financial Economics, (11), Nart, E. Ç. (2010). The effects of custom union to Turkey s foreign trade: Panel data analysis. Journal of Yasar University, 17(5), Özer, M., & Çiftçi, N. (2009). Relationship between R&D expenditures and exports: A panel data analysis for OECD countries. Dumlupinar University Journal of Social Sciences, 23. Pazarlioğlu, M. V., & Gürler, Ö. K. (2007). Telecommunication Investments and Economic Growth: Panel Data Approach. Journal of Financial Politics & Economic Comments, 508, Şimşek, N. (2008). Analysis of Turkey s ıntra-ındustry foreign Trade. Beta Yayınevi, İstanbul. Türker K. Y. (2002). Determinants of profitability in Turkish Banking system: (Banking Regulation and Supervision Agency Working Reports. June 2002 No.2002/1).