type the title of the paper

A6

Journal of Academic Research in Economics Volume 6

Number 1

March 2014

ISSN 2066-0855

EDITORIAL BOARD PUBLISHING EDITOR DRAGOS MIHAI IPATE, Spiru Haret University EDITOR-IN-CHIEF CLAUDIU CHIRU, Spiru Haret University ASSISTANT EDITOR GEORGE LAZAROIU, Contemporary Science Association

INTERNATIONAL ADVISORY BOARD JON L. BRYAN, Bridgewater State College DUMITRU BURDESCU , University of Craiova MARIN BURTICA, West University Timisoara SOHAIL S. CHAUDHRY, Villanova School of Business DUMITRU CIUCUR, Bucharest Academy of Economic Studies LUMINITA CONSTANTIN, Bucharest Academy of Economic Studies ANCA DACHIN, Bucharest Academy of Economic Studies MANUELA EPURE, Spiru Haret University LEVENT GOKDEMIR, Inonu University EDUARD IONESCU, Spiru Haret University KASH KHORASANY, Montreal University RAJ KUMAR, Banaras Hindu University, Varanasi MARTIN MACHACEK, VSB-Technical University of Ostrava COSTEL NEGREI, Bucharest Academy of Economic Studies ABDELNASER OMRAN, Universiti Sains Malaysia T. RAMAYAH, Universiti Sains Malaysia ANDRE SLABBERT, Cape Peninsula University of Technology, Cape Town CENK A. YUKSEL, University of Istanbul MOHAMMED ZAHEERUDDIN, Montreal University LETITIA ZAHIU, Bucharest Academy of Economic Studies GHEORGHE ZAMAN, Economics Research Institute, Bucharest

PROOFREADERS MIHAELA BEBESELEA, Spiru Haret University CAMELIA BOARCAS, Spiru Haret University ONORINA BOTEZAT, Spiru Haret University MIHAELA CIOBANICA, Spiru Haret University CRISTINA CIOTE, Spiru Haret University DANIEL DANECI, Spiru Haret University MIHNEA DRUMEA, Spiru Haret University PAULA MITRAN, Spiru Haret University LAVINIA NADRAG, Ovidius University Constanta OCTAV NEGURITA, Spiru Haret University RALUCA PACURARU, Spiru Haret University IULIANA PARVU, Spiru Haret University LAURA PATACHE, Spiru Haret University MEVLUDIYE SIMSEK, Bilecik University GEORGIANA SUSMANSCHI, Spiru Haret University ADINA TRANDAFIR, Spiru Haret University MIHAELA TUROF, Spiru Haret University

Contents

ENDOGENOUS WEALTH AND ENVIRONMENT BASED ON THE SOLOW MODEL WITH GENDER DIVISION OF LABOR AND LEISURE WEI-BIN ZHANG

7

IMPACT OF FOREIGN INSTITUTIONAL INVESTMENT ON THE VOLATILITY OF INDIAN STOCK MARKET SURESH KUMAR JASDEEP DHAMI

32

RELATIONSHIP BETWEEN TRADE OPENNESS AND ECONOMIC GROWTH OF INDIA: A TIME SERIES ANALYSIS MONOJIT CHATTERJI SUSHIL MOHAN SAYANTAN GHOSH DASTIDAR

45

PORTFOLIO IN TURKISH ECONOMY, AND A LONG TERMED RELATION BETWEEN FOREIGN DIRECT INVESTMENTS AND THE GROWTH, AND THE STRUCTURAL BREAKAGE ANALYSIS (1980-2012)

70

BILAL KARGI

TURKISH BANKING SECTOR: THE ANALYSIS OF MACROECONOMICS INDICATORS AND BANK PROFITABILITY WITH PANEL DATA APPROACH

82

NURİ BALTACI

AN ADJUSTED DUPONT MODEL FOR ENTERPRISE PERFORMANCE EVALUATION

93

XIAOSONG ZHENG BING ZHANG

THE APPLICATION OF ECONOMIC VALUE ADDED ON PERFORMANCE EVALUATION OF LISTED BANKS IN CHINA XIAOSONG ZHENG

103

THE APPLICABILITY OF THE OPTION EXCHANGE MARKETS IN THE CENTRAL BANK FOREIGN EXCHANGE POLICIES: THE COLOMBIA APPLICATION

119

BÜLENT DICLEHAN ÇADIRCI MEVLÜDIYE ŞIMŞEK

AUDITING OF CORPORATE SOCIAL RESPONSIBILITY (CASE STUDY – ALBANIAN BANKING SECTOR) HOLTJANA BELLO ELVIN MEKA

150

JOURNAL OF ACADEMIC RESEARCH IN ECONOMICS

TURKISH BANKING SECTOR: THE ANALYSIS OF MACROECONOMICS INDICATORS AND BANK PROFITABILITY WITH PANEL DATA APPROACH NURİ BALTACI 1 Gumushane University, Turkey E-Mail: [email protected] Abstract Turkish banking sector secured its growing profitability during the period of 2007 global financial crises and afterwards. While several large-scale banks declared their bankruptcy as a result of 2007 global crises, how did Turkish banks reach their position of growing profitability? In this study the relationship between the profitability of Turkish banks in the sector and macroeconomic variables will be examined. In the study, the sectorial data of 31 banks and macro-economic data, that covers the period of 2001-2011, is analyzed by using panel data method. As a result of the analysis, a positive relationship between bank profitability and inflation and indicators of crisis has been found, which shows that banking sector is affected by general economy. The findings of the study support the other studies in the literature. Keywords: Turkish Banking Sector, Bank Profitability, Macro-economics Indicators JEL Classification: C30, G21, E44.

1. INTRODUCTION Financial intermediaries assume a very important role in economies. Especially its linking role between investment and savings is very important for investments (Kunt, Huizinga, 1999, p. 379). Banking sector covers a great part in financial system in developing countries including Turkey. Especially in countries with savings deficiency banks serve as a brokerage house, which is crucial for investment and growth. Particularly, during the period of 2007 global financial crisis while bankruptcy of many finance and banking institutions became an issue, going through this period was comparatively easy for Turkish banking sector. The 1

Gumushane University, Faculty of Economics and Administrative Sciences, Department of Economics, Gumushane/Turkey

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VOLUME 6 NUMBER 1 MARCH 2014


financial crisis appeared in USA, also called mortgage crisis, first caused many banks to bankrupt in the U.S. then spread to other economies via financial network and turned into a global crisis. While the crisis resulted in bankruptcy of many banks in the U.S. and Europe, the banking sector in Turkey attracted the attention of the world with its only decreasing profits. Also in 2009, in which financial crisis deepened and global bankruptcies increased, Turkish banking sector gathered more attention internationally with its increasing net profits, return on assets (ROA) and return on equity rates (ROE) (Bankalarımız, 2009, pp. 1-42) Analysing the Turkish banking sector as in periods before and after 2001 is very important since in 2001 with the establishment of Banking Regulation and Supervision Agency (BRSA) the supervision of the banks and the regulation of the market have reached a more modern system. The banking sector was a factor that caused the financial crises of 2000 and 2001 to deepen. In 2001 Transition to the Strong Economy Program (TSEP) proficiency and capital structure of the banks reregulated.In July in 2012 Basel II implementation started but the impact of the implementation to capital adequacy has been limited. Decrease in credit growth as a result of strict monetary policy implementations, epecialy the implementation of limiting credit cards and installments in 2013, caused expectations of sectoral shrinkage. On the other hand increasing exchange rate affects the open positions of the banks. In the sector the ratio of past-due receivanles is approximately 3% . Banking system in the developing countries play a big role in financial system. Disruptions in the banking systems cause to serious financial crises in the countries. As we can observe from the results of the crises of 2000 and 2001 that if a serious supervision and regulation cannot be performed in the banking sector, it will bring critical problems to national economy. In this sense, it can be said that the Turkish banking sector has important effect on appearance of financial sector. The success of the sector provides the development of the financial system and it also leads to provide funding to the country. The aim of the study is to examine the relationship between the profitability of Turkish banks in the sector and macroeconomic variables and to investigate profitability of banks in the crisis periods. The paper is structured as follows. Section 2 surveys the relevant literature on banking profitability and theoretical background. Section 3 describes the data sample and methodology used. Section 4 presents the results of our empirical analysis, and Section 5 concludes.

2. LITERATURE When we look at the literature about banking sector in Turkey, significant studies can be seen. Demirel, Atakişi & Abacıoğlu (2013) investigated Turkish banking sector’s profitability using various methods like panel data. They used the return on assets, return on equity and total assets ratio of costs as dependent variable in their model. VOLUME 6 NUMBER 1 MARCH 2014

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Sarıtaş & Saray (2012) used banking sector profitability rate to investigate the positive effect of the regulations enacted after 2001 in the Turkish banking sector on profitability in period of 2002-2009. They segmented banks and found that profitability of Turkish banks increased except 2008 global crises period. Alper & Anbar (2011) investigated the relationship between bank-specific inner macro-economic variables of commercial banks and their profitability in the period of 2002-2010 in their study. They used ROA and ROE as bank profitability indicators; they picked panel data analyze method in their study. They found positive effects of asset size and non-interest income on profitability. They also found negative effects of non-performing loans and loans size on profitability. According to other results in the literature, there is a positive and significant effect between real interest variable using as a macroeconomic variable and profitability. Alp & et al.’s (2010) study is about defining of intrinsic determinants of bank profits at 2010. They found positive effect of banks' capital adequacy and bank size on profits. They used as net profit / total assets as a dependent variable in their study. Dağıdır (2010) investigated the macroeconomic indicators effect on bank profitability in his/her study. His/her study’s aim to investigate the relationship between the profitability of Turkish banking sector and macroeconomic variables. He used interest margins as an indicator for bank profitability data, he also used inflation, growth, GDP and industrial production index for macro data. He/she found a negative and statistically significant relationship between interest margins and inflation. Bumin (2009) analyzed the profitability of Turkish banking system using data set between 2002 and 2008 years. He argued that thanks to 2001 banking regulations; the profits of Turkish banks have increased. He also argued that because of global crises at 2008, the profits of Turkish banks have decreased. Rate variables have been used at this study. Detection of profitability has been made by interpreting profitability ratios for the period. Tunay & Silpar (2006) differentiated Turkish banks as commercial banks and development and investment banks. They analyzed profitability of commercial banks in their study. When we check the literature about profitability of bank, important studies also can be seen. Naucer (2003) used panel data method at his/her study which determinant of Tunisian banking sector profitability. In same study, he investigated the effect of net interest margin that belongs to Tunisian banking sector between 1980-2000 time period, financial structure and macroeconomic variables on profitability. He/she found that bank related variables have significantly impacted on bank profitability. For instance, while high interest margin has positively impacted on bank profitability, bank size has negatively impacted on bank profitability. However, Naucer (2003) couldn’t find any significant effect of macroeconomic

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indicator on profitability. However, he/she found a positive relationship between financial structure and bank profitability. Srairi (2010) used stochastic limit analysis method to investigate Islamic banking in terms of profitability and costs for the period of 1999 - 2007 in Gulf countries. In his/her study he/she compared the productivity levels of traditional banking and Islamic banking using bank specific variables. He/she found that banks at Gulf region are more profitable than others. He/she also found that conventional banks are more profitable than others in terms of cost and profitability. Furthermore, high credit activities have positive effect on banks’ profitability, but have negative effect on cost efficiency. Coccorese & Pellecchia (2009) analyzed multi-market connectivity and profitability using banking sector data and market data of the Italian banking sector in the period of 2002 and 2005. According to multimarket communication theory, banks are getting aggressive in case of retaliation of competitors at other markets. Coccorese & Pellecchia (2009) tested and confirmed this theory. According to findings, contacts between banks have a positive effect on profitability. In addition, improving of these contacts has positively effect on profitability. Ayadi & Boujelbene, (2012) have made detection of deposits of banks' profitability using panel data method in period of 1995-2005. They found the positive effect of the number and size of banks on profitability. They also found that while the ratio of stock market capitalization and assets as financial variables have negatively and significantly effect on profitability, macro variables have not significantly effect on bank profitability. As a result of this study, they revealed that bank profitability could vary whether it subjected to financial markets or bank groups. Hsieh & Lee (2010) analyzed the relationship between bank profitability and competition in 61 countries in period of 1992-2006. They found that increasing of barriers and restrictions in banking sector have negatively effect on bank profitability; however solid financial structure and high per capita income level have negative effect on bank profitability. They also found that competition and restrictions in banking sector has negative effect on bank profitability. Karimzadeh, Akhtar & Karimzadeh (2013) have investigated the determinants of Indian banking sector profitability in the context of the industry specific variable and macro variables in India. Findings obtained from the study show that the rapid growth of Indian banking sector is the most crucial predictor of Indian economy. They found a positive relationship between economic growth and profitability and they also found a robust negative relationship between inflation and bank profitability. Sufian & Habibullah (2009) used data that covers the period of 2000 and 2005 to determine profit rate of Chinese banking sectors with macro and sector data. They found statistically significant relationship between money supply growth and national income. They found negative non robust relationship between inflation and bank profitability.


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3. METHODOLOGY AND DATA In the study, the effect of bank capital on profitability is examined by using the panel data methodology, because of the benefits it provides. Baltagi (2001) and Hsiao (1986) indicate panel data methodology controls for individual heterogeneity, reduces problems associated with multicollinearity and estimation bias, and specifies the time-varying relation between dependent and independent variables. Arellano & Bover (1995)/Blundell & Bond (1998) the estimator of generalized method of moments (Robust standard deviation) is used. Arellano & Bover (1995)/Blundell & Bond (1998) the estimator of generalized method of moments, the effective instrumental variable is estimated by orthogonal deviations method instead of the transformation of the first difference in Arellano & Bond (1991). Thus, the data loss is minimized by using the average of the possible future values instead of first-difference method in the data set where unbalanced panel or units are bigger than the time. A serial correlation test for panel GMM estimators developed by Arellano & Bond (1991) is used in this study. The significant serial correlation means our estimated coefficients were biased. Thus, in order to produce robust results we tested the serial correlation and the test results were insignificant. Also, it is necessary to test the results of dynamic panel data estimation model that are realized under the conditions of GMM with first and second-order autocorrelation tests suggested by Arellano & Bond (1991). According to the results, it is expected that second-order autocorrelation would be statistically significant. The models that do not have the second-order autocorrelation are the suitable models (Tatoglu, 2012). The fact could be tested by the Wald test that whether the model estimate is done correctly or not (Roodman, 2006). The data comes from The Banks Association of Turkey (TBB), Turkey Statistical Institute (TUIK) and Banking Regulation and Supervision Agency (BDDK). According to the earlier literature discussion and this study’ purpose, the works of Naceur (2003) to establish the relationship between bank capital and profitability is modified. ܴ‫ܽ݋‬௜௝ǡ௧ ൌ ‫ܨ‬ሺ‫ܥܤ‬௜௝Ǥ௧ ൅ ‫ܯ‬௧ ൅ ‫ܵܨ‬௧ ሻ

(1)

Here, t and i denote time period and banks, respectively. Term BCt includes the set of bank specific variables. Roait refers to the i the bank’s profitability in year t, proxied by return on assets. Term Mit includes the set of macro-economic control variables. Term FSit includes the Crisis dummy to examine effect of 2008 Crisis on banking profitability.

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This paper mainly investigates the relationships among macro-economic and profitability for Turkish banks with the latest and a wider range of panel data that cover 31 banks from 2001 to 2011. The relationship between bank-specific and macro-economic variables and profitability can be specified as follows:

ܴ‫ܽ݋‬௜௧ ൌ ߙ଴ ൅ ߙଵ ܴ‫ܽ݋‬௜௧ିଵ ൅ ߙଶ ܶ‫ܴܣ‬௜௧ ൅ ߙଷ ܰܲ‫ܴܮ‬௜௧ ൅ ߙସ ܰ‫ܣܶܮ‬௜௧ ൅ ߙହ ‫ܲܦܩ‬௜௧ ൅ ߙ଺ ‫ܨܰܫ‬௜௧ ൅ ߙ଻ ‫ܻܯܯܷܦ‬௜௧ ൅ ɉ௜௧ ൅ ߝ௜௧

(2)

Here, t and i denote time period and banks, respectively, λi is an unobserved bank-specific effect, and εit is the idiosyncratic error term. Roait refers to the i the bank’s profitability in year t, proxied by return on assets. Term TARit includes bank asseti / total banking sector asset. Term NPLRit shows nonperforming loans / total loans. Term NLTAit shows net loans to total assets. Term GDPit includes the real GDP growth rate at 2003 costant price. INFit shows the inflation rate proxy by the change of Consumer Price Index (CPI) with inflation deflator. DUMMYit represents the recent subprime crisis dummy. Table 1. Variables Description Variables Profitability Bankspecific variables

Descriptions Return on assets (ROA) Non performing loans rate (NPLR) Loans rate (NLTA) Total asset rate (TAR)

Inflation rate (INF) Macro control variables

Real GDP growth rate (GDP) The recent subprime crisis dummy (DUMMY)

Net income / total assets Non performing loans / total loans Net loans to total assets Bank asseti / total banking sector asset The change of Consumer Price Index (CPI) with inflation deflator. GDP growth rate at 2003 costant price 2008 = 1; otherwise 0

Expected signs

+

+/-

+/+/-

The dependent and independent variables are shown in Table 1. Following the previous studies (Hsieh & Lee, 2010; Karimzadeh, Akhtar & Karimzadeh, 2013; Sufian & Habibullah, 2009).

4. EMPIRICAL ANALYSIS Table 2 provides descriptive statistics of all variables. During the entire period 2001–2011, used as indicators of bank profitability, the mean value of return on asset (ROA) is 1,2%. In addition, the average bank asseti / total banking sector asset (TAR) is 2,9%. As can be seen from Table 2; non-performing loans / total VOLUME 6 NUMBER 1 MARCH 2014

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loans (NPLR), net loans to total assets (NLTA) is average 42,8% and 14,6%, respectively. Table 2. Descriptive Variables Variable Roa TAR NPLR NLTA GDP INF

Obs 341 341 341 341 341 341

Mean 1.200 2.969 42.875 14.606 4.413 16.402

Std. Dev. 6.243 4.593 266.395 16.290 5.153 14.757

Min -63.200 0.000 0.000 0.000 -5.697 5.294

Max 32.200 18.700 3759.100 87.400 9.362 52.805

Table 3 reports the correlation coefficients between the variables. The correlations between the dependent and independent variables are seen in Table 3. The correlation coefficients show both the direction and greatness of the relations between dependent variables and independent variables. There is a negative relation between net return on asset and non-performing loans / total loans and there is a positive relation between return on assets and net loans to total assets and bank asseti / total banking sector asset. Table 3. Correlation Matrix ROA TAR NPLR NLTA GDP INF

ROA 1.0000 0.0055 -0.3801 0.0046 0.1486 -0.2438

TAR

NPLR

NLTA

GDP

INF

1.0000 -0.0763 -0.2602 0.0132 -0.0393

1.0000 -0.1170 0.0698 -0.0344

1.0000 0.0284 -0.0158

1.0000 -0.4511

1.0000

The correlation among the independent variables is in Table 3. The correlation coefficients will put forth both the relations among the variables and also the presence of high multicollinearity problems among the independent variables will be used in the model. In this regard, in case of the high correlation (± 0,90 and higher) among those independent variables, they will not been estimated in the same equation. Instead of this, they will take a part in different equations. While look at the Table 3, it is seen that this multi collinearity problem (multi collinearity) is not valid for any kind of independent variables. This finding expresses that it could take a part in estimating of all independent variables.

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Table 4. Arellano–Bond’s Two-Stage Generalized Moments Estimator standart errors) dependent variable: ROA Dependent Variables: ROA Roa L1 TAR NPLR NLTA GDP INF DUMMY

(with robust

Commercial Banks in Turkey 0.221** (0.091) 0.795** (0.380) -0.010*** (0.003) -0.060* (0.036) 0.078 (0.066) 0.108*** (0.037) 0.649*** (0.221) 0.2079 114.78 0.0000 293 30

Sargan Test ( p-value)a Arellano-Bond Order ( p-value) 2b Wald chi2(7) Prob>chi2 Number of observations Number of banks Numbers in parentheses are standard errors. * Significance level at 10%, ** Significance level at 5%, *** Significance level at 1%. a: Cannot calculate Sargan test with vce(robust) b: The null hypothesis is that the error term in the first difference regression exhibits no second order serial correlation

In the model, ROA is used as an indicator of profitability of the banking sector. Tunay & Silpar (2006), Özkul (2001), Pılloff & Rhoades (2002), Naceur (2003), Sufian (2009) used return on assets as dependent variable in their own studies. As a result of the model, it is found that there is a strong positive and statistically significant correlation between one period lagged value of the ROA and ROA at 5% significance level. And, a positive and statistically relationship has been found between total assets and ROA at the same significance level. The findings of the study support the studies of Srairi (2010), Coccorese & Pellecchia (2009), Ayadi & Boujelbene (2012), Hassan & Bashir (2003), Hsieh & Lee (2010) in the literature. Credit risk has a negative impact on the profitability of the banking. In the model, the ratio of non-performing loans to total receivables variable explains the profitability of bank as negatively and statistically significant on the 10% significance level. However, Srairi (2010) determines a positive relationship between those variables at the same significance level in his own study. In our model, a negative and statistically significant relationship between the ratio of VOLUME 6 NUMBER 1 MARCH 2014

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loans received to total loans and bank profitability has been found at the 10% significance level. The findings of the study support the studies of Srairi (2010), Coccorese & Pellecchia (2009). In the study, it was found that there is not a strong relationship between economic growth and profitability of bank. Naceur (2003) also could not find statistically significant relationship between profitability of bank and growth variable, which he used in his study. The banks will not be affected by this relationship unless they are able to predict inflation. In the analyzing section, relative inflation rate is measured highly closely to prediction of Central Bank of Turkey. A positive and statistically significant relationship between inflation and bank profitability is determined at 1% significance level. While the Bourke(1989), Molneux & Thornton (1992), Abreau & Mendes (2002) found the similar result with our study, Naceur (2003) found no statistically relationship between inflation and bank profitability. In the study, the crisis is used as a dummy variable. A value of 1 is assigned to 2007, the year the crisis appeared, and other years are assigned to 0.The positive and statistically significant relationship between inflation and bank profitability indicates that Turkish banking sector is not affected by the global crisis and Turkish banking sector secured its growing profitability during the period of 2007 global financial crises and afterwards. The underlying factors behind these arguments can be explained by the reregulation of proficiency and capital structure of the banks in 2001 and positive results of the effective controls of banking system.

5. CONCLUSION The Turkish banking sector had gone through difficult times and caused the financial crises of 2000. In 2001 with the Transition to the Strong Economy Program (TSEP) and establishment of Banking Regulation and Supervision Agency (BRSA) the Turkish banking sector was subjected to a strict supervision and regulation. During this period, a big step has been taken regarding capital adequacy of the banks and their supervision, and the regulations to secure the sector operate in solid ground has been still going on in 2013. In our study, when the sectoral profitibility is analyzed especially within periods of crieses and variables of macro-economics we see that banks countinue operating in solid ground. Particularly, it can be said that in environments where monetry stability is secured, banks are able to countinue their profitibilaty. In addition to not been affected seriously from financial crisis banks countinue to operate as profitiable instituitions.

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