International Journal of Economic Perspectives, 2014 ...

International Journal of Economic Perspectives, 2014, Volume 8, Issue 4, 19-38.

The Effect of Inflation and Interest Rate on Turkish Banking System’s Incomes1 Ercan OZEN*, PhD Department of Banking and Finance, School of Applied Sciences, Uşak University, Uşak, Turkey, Post Code (64200). Tel. (+90) 532 549 53 42 / (+90) 276 221 21 21 (7065), E-mail: [email protected], [email protected].

Metin TETIK, PhD Department of International Logistics and Transportation, School of Applied Sciences, Uşak University, Uşak, Turkey, Post Code (64200).Tel. (+90) 276 221 21 21 (7081), E-mail: [email protected].

ABSTRACT The study aims to explore 1) to understand how low inflation and interest rates affect to Turkish banking system’s income. 2) to find out whether low profit margins of banking, said that contraction in public because of low inflation and low interest rate, compensated by commission income. Data set of the study consists 46 quarterly between 2002:1 and 2013:4. The main findings based on SVAR model impulse response analysis, it has been showed that an increase of political interest rate has negative effect on rate of assets (ROA) and hasn’t any statistically meaningful effect on rate of equity (ROE). Whereas, it has been showed that inflation doesn’t affect to ROA as statistically and affect ROE as statistically. Another finding of the study is that contribution of net interest income to profitability bigger than that of commission. This result means that the interest income is still the major profit element of banks. JEL Classification: G21; E43; E52; E31. Key Words: Finance; Banking; Inflation; Interest Rate; Commission; SVAR. *Corresponding author. 1

This study is revised and extended version of the proceeding titled as "Effects of Low Inflation and Low Inflation Rates on Main Incomes of Turkish Banking System: Interest Income or Commission?" and presented at 18th Financial Symposium held in Denizli / Turkey between 14th and 17th October 2014. 1.

INTRODUCTION

The Turkish economy has been in the form of two-digit inflation and interest rates. This situation has changed to three-digit numbers in 1994 and in 2001, overnight interest rates has been in four-digit numbers. In the time period after 2001, a decrease, which can be evaluated as a stable one, has been seen in inflation and interest rates. In the Turkish economy, which has changed from high inflation and interest rates to low ones, it has seen that companies have affected differently from this changed environment. During the related time period so far, there have been news and comments in the public opinion and these news and comments have been indicating that many companies have narrowed their profit margins. It has also been stated that net interest income margins of banks have decreased substantially because of the decreasing interest rates. It can be said that the banks, which have pressure on their interest incomes, have intense works within different areas, which can create different income instead of interest; in order not to make incomes decreased. One these works are related to fee and commission incomes. In last years, it has been claimed that banks get money from their customers in an unfair way, by taking extra payments called as commission fee. The banks, which maintain its profitability and have high capital adequacy rates, have been employed as one of the most important insurance tools during the global financial crisis in 2008. A strong banking system is a critical economical confidence source for the community, but it also receives serious negative critiques from the International Journal of Economic Perspectives ISSN 1307-1637 © International Economic Society http://www.econ-society.org

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International Journal of Economic Perspectives, 2014, Volume 8, Issue 4, 19-38. community. Because banks gain the related incomes from their customers, by using different ways like interest income, fee income or commission income etc. This situation is an income for the banking system whereas it is an incurred cost for the customers. At this point, this cost is not welcomed by the customers. Objective of this work is to understand how asset profitability and equity profitability rate of the Turkish banking system have changed as being associated with the inflation and interest rates, which have been in a decrease trend since 2002. It is also aimed to determine the relation between the values of low inflation and interest incomes during the interest, fee and commission incomes, profitability before tax, and the rates of inflation and interest. Also, another objective is to find out if the banks can whether recover their narrowed interest margins via fee and commission incomes or not. 2. THEORATICAL ASPECTS AND THE LITERATURE There are many factors affecting incomes and expenses, and profit or loss of banks. These factors are categorized under two groups called as internal and external factors. Internal factors are generally indicated like bank magnitude, capital, risk management, expense management, movable value holders, and credits in chase (Güngör, 2007). These factors are the ones, which are directly related to the bank management or can be controlled by the bank management. Variables, which cannot be controlled by the bank management, are external variables. These are the elements like inflation, interest rates, and domestic income. Our work is based on the relation of inflation and interest rates (as external variables-factors), with net interest incomes, net fee and commission incomes, and profit before the tax variables of banks. Inflation and interest rates may affect the profit of companies. Gwin et al. (2000) have indicated that fluctuation within inflation and interest rates allows sellers to obtain higher profit margins. During the fluctuation of prices, there can be information pollution within the market. This pollution makes it difficult for customers to track prices and allows companies to apply higher profit margins. But on the other hand, inflation may cause banking profit margins to be seen bigger although they are smaller in reality (Gülhan and Uzunlar, 2011). Demirguc-Kunt and Huizinga (1999) have suggested that the inflation will affect bank profits in a positive manner. The authors have indicated that in the relation between the inflation and the profit, incomes will be more than costs and because of the inflation, credit interest rates and the profitability as a result will be high. Also, it has been indicated that interest incomes received from lags within credits affect the profit in a positive manner. However, Demirguc-Kunt and Huizinga (1999) have expressed that unexpected inflation shocks will make the interest rate adjustments of banks slower and bank cost will increase more than incomes. In their work, Gülhan and Uzunlar (2011) have found that inflation has a positive and meaningful effect on asset profitability. As similar, Aksoy (2007) has performed a research work on determining the relation between inflation and asset profitability and found that asset profitability is higher in banks having foreign share, countries having high inflation rate, and banks in which passive asset amount is low. Additionally, the author has found a positive relation between inflation and net interest income. In their work, Gwin et al. (2000) has found out that profit margin of companies are connected with the inflation rate and companies have higher profit margins in especially inflationist environment. Vejzagic and Zarafat (2014) have found that in Malaysia, during the 1995-2011 period, bank asset profitability has affected positively from increase in national income, and negatively from the inflation, and also there is no relation between bnk profits and real interest rates. As similar, Sayılgan and Yıldırım (2009) have found that there is a reverse relation between inflation and bank profitability. According to this, bank profitability increases when the inflations decrease. The works explains that profitability improve with industrial production index in harmony. Naceur (2003) has expressed that inflation and interest rates have no significant effect on asset profitability and capital stock profitability of banks and banks are not in a profitability trend in inflationist environment. Akbaş (2012) has also determined that inflation has meaningful and negative effect on asset profitability of banks and it also has no meaningful effect on capital stock profitability. International Journal of Economic Perspectives ISSN 1307-1637 © International Economic Society http://www.econ-society.org

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International Journal of Economic Perspectives, 2014, Volume 8, Issue 4, 19-38. Alper and Anbar (2011) have found that some internal variables has effects on profitability and real interest rate, which is one of macro-economic variables, has positive effect on return of equity (ROE) but it also has no effect on return of asset (ROA). Alper and Anbar have expressed that inflation rate and national income have no effect on ROA and ROE. Additionally, Kaya (2002) has found positive relation between real interest rates and ROE. Vu and Nahm (2013) have obtained findings explaining that in Vietnam, because of suitable conditions provided by low inflation, profitability cause increase in the banking system. Sufian (2009) has stated that in Malaysia, for the 2000-2004 term, high inflation rate affects profitability in a positive manner whereas Sufian and Kamarudin (2012) have determined that inflation has had negative effects on bank profitability for the 2000-2010 term in the same country. According to the findings by Pouw and Kakes (2013), inflation decrease bank profits. Sufian has stated in the work performed for south Asia countries that inflation has no significant effect on banking profits. As it is seen, inflation has different effects on bank profits as shown by similar works performed for similar countries. In the work based on 1995-2009 term, Taşkın (2011) has expressed that macro-economic variables have no significant effect on ROE and ROA and it is internal variables, which determine the profitability. According to Gwin et al. (2000), there is no theory explaining that why profit margins of different companies are different for changes in the inflation. The authors have suggested that obtaining costs of companies against the inflation may be a theory. 3. COURSE OF SOME INCOMES AND EXPENSES IN THE TURKISH BANKING SYSTEM It has been being discussed that if inflation and interest rates, which are in decrease trend because of the political approaches applied since start of 2000s, affect the banking sector in a positive or negative way. It has seen that interest incomes, interest expenses, net interest incomes, net interest expenses, fee and commission incomes, profits before tax, equities or assets of banks increase nominally while inflation and interest rates continue to their decrease trend. In order to see the exact course, net interest incomes, net fee and commission incomes, and profits before tax of banks have been defined in a yearly form and corrected according to Consumer Price Index (CPI). These corrected items have been adjusted with equity and asset. Their course in time is shown in Figure 3.1 and Figure 3.2. According to the Figure 3.1, rate of net interest incomes to the equity is in a decrease trend except from second and third quarter of 2003. The rate of net interest / equity has decreased from the level of 40% to the level of 30%. On the other hand, profits before the tax have also decreased to the level of 15% from the level of 20% at the start of 2014, except from the unexpected deviation in the third quarter of 2005. Interest and profit data decrease against the equity and it is thought that banks will recover this decrease with fee and commission incomes. Equity rate of fee and commission incomes has increased to the level of %15 in 2006 from the level of 10% in 2002 and decreased to the level of 10% again in 2014. At this point, it is understood that banks cannot increase their net interest incomes and fee and commission incomes against the equity. The Figure 3.2 presents the course of data related to net interest income, fee and commission incomes and profit before the tax (which are also in a decrease trend against the equity) against the asset. The rate of net interest incomes to the asset has increased to the level of 5,7% in 2005, and decreased to the level of 3,3% at the start of 2014. On the other hand, the rate of the profit before the tax to the asset has decreased to the level of 1,6% from the level of 3%, except from 2005. Also, the rate of fee and commissions to the asset has decreased to the level of %1 from the level of 1,2%-1,4%. It can be understood from the Figure 3.1 and Figure 3.2 that net interest incomes, profits before the tax, and fee and commission incomes against both equity and the asset of banks have become weak. As a more detailed analysis for net profit, and net fee and commission incomes, rates for total interest income and the profit before the tax have shown in Figure 3.3. According to the graphic, rate of net interest incomes of banks to the total interest incomes have been at about the level of 32% in 2002, 53,60% in the first quarter of 2010, and 49% at the start of 2014. In this sense, banks have maintained their net interest margin within the total interest income, during the work period. If the fluctuation in 2005 is omitted, the rate of net interest income / the International Journal of Economic Perspectives ISSN 1307-1637 © International Economic Society http://www.econ-society.org

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International Journal of Economic Perspectives, 2014, Volume 8, Issue 4, 19-38. profit before the tax has maintained its status with the level of 200%. This situation indicates that the share of the net interest income in profit is still maintained. The rate of fee and commission incomes to net interest incomes has increased to the level of 49% in 2003 and now keeps its level about 30% with a slight fluctuation occurred in time. This situation shows that fee and commission incomes of banks increased significantly, as against interest incomes within last years. But the rate of net fee and commission incomes to the profit before the tax has increased to the level of 63% (which is also the level in 2009), at the start of 2014. Increase in the share of fee and commission incomes within the profit before the tax is because of decrease in positive effect of income items of banks over the profit. In order to see the levels, to which yearly interest incomes, interest expense, net interest, fee and commission, profit before the tax, capital stock, and assets of banks has reached, the Figure 3.4 has been prepared after making decontamination from the inflation. It can be seen from the figure that assets show a significant real growth according to 2002. This situation shows that assets have a magnitude, which cannot be compared with other items. In order to perform a better comparison for other assets except from the asset, a new figure has been formed by eliminating the asset. Figure 3.5 shows the course of items except from the asset. As it can be seen from the figure, each item has been in a real increase along years. Gross interest incomes and expenses have reached to the highest level until 2009. After that, it has been in a lower and undulating course. In 2013, it has also increased to the highest level as being associated with movements in net interest, gross interest income and interest expenses. Profit before the tax has shown an undulating increase except from the first quarter of 2014. Fee and commission incomes have also shown a real increase trend along the year. In order to show the momentum shown by the items according to the start year, an index has formed by making starting year value of all items as 100, and the Figure 3.6 has prepared. If we take the starting year into consideration, it is seen that index values regarding to all items increase. The assets is the one among all items, which provides the highest increase. Because the equity shows an increase near to the asset, rates of asset and equity shown at the start of this section have decreased. In the related period, fee and commissions are not the nominally most significant item but in a remarkable growth momentum. Banking Regulation and Supervision Agency continues to limit the profit distribution in order to make financial structure of banks strong. In order to recover the narrowing in decreased domestic deposit / credit interest margin, banks use more low cost abroad sources and this situation causes continuity in growth of passives. According to the report of Banking Regulation and Supervision Agency (2014), rate of fund related to abroad banks to the total passive, which is 9,2% in 2002, has reached to 17% in 2013. Using funds related to abroad banks decrease the total source cost in banks and this situation allows keeping the net interest margin despite decreased inflation and interests. On the other hand, as it is indicated by Kaya and Doğan (2005), it is seen that banks head for a more effective structure. In 2001, Banking Regulation and Supervision Agency has started the “Banking Sector Reconstruction Program” in order to make effectiveness and competition in the system permanent and make the financial and operational structure of the banking system stronger. Thanks to this program, it has been aimed to increase the profitability and effectiveness in the system (Güngör, 2007: 41). Bakırcı and Sarıkaya (2012) have shown that the effectiveness in the banking system has increased with the inflation decreased in 2001-2008 term. It is expected that this effectiveness increase will make positive effect over profitability. 4. THE MODEL In this study, profits of banks in Turkey have analyzed via SVAR methodology in order to examine the relation among fee and commission incomes, net interest incomes with politics interest, and the inflation. In the sense of data frequency, quarterly data are used. 4.1. Features of the Data and Choosing the Variables In the study, data regarding to the time period between January 2002 and December 2013 are used. The variables are generally profits of banks, fee and commission incomes, net interest incomes with politics interest rate, and inflation. But these variables, which will be used in the sense of VAR model, have been divided into two groups. International Journal of Economic Perspectives ISSN 1307-1637 © International Economic Society http://www.econ-society.org

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International Journal of Economic Perspectives, 2014, Volume 8, Issue 4, 19-38. In the first group, rate of profit before tax to the asset for the banks calculated as quarterly, rate of net interest of banks to their assets, rate of fee and commission incomes to assets with the mean of three-monthly politics interest, and the mean of three-monthly Consumer Price Index (CPI) have taken into consideration. On the other hand; in the second group, rate of profit before tax to the equity for the banks calculated as quarterly, rate of net interest of banks to their equities, rate of fee and commission incomes to equity with the mean of three-monthly politics interest rate, and the mean of three-monthly Consumer Price Index (CPI) have taken into consideration. A brief view on these variables is shown in Table 1.1. The variable of politics interest has been obtained from Istanbul Stock Exchange, whereas CPI variable is from Turkish Statistical Institute (TÜİK) web site, and other variables are from The Banks Association of Turkey database. 4.2. Structural VAR Modeling with Contemporaneous Restrictions The VAR system used in our work has been thought as a structural VAR model, which ensures the concurrency and lag interactions among the variables expressed within previous paragraphs. The SVAR model, which aims calculating the interaction among these variables is like this; BYt = A+ CYt−p + εt (1) In the Equation 1, Yt variable is a 5x1 internal variables vector including [ROA, RIA, CIA, CPI, PIR] or [ROE, RIE, CIE, CPI, PIR].1 Also, A, B, and C are structural coefficients, and εt is 5x1 dimensions [ε1t, ε2t, ε3t, ε4t , ε5t ], structural shock vector, which has zero mean and no relations. B is a 5x5 dimensions matrix. B matrix can be determined contemporaneous structural coefficients, which have diagonal elements as 1, and provide contemporaneous feed-back among elements, which are out of diagonal. If we write the SVAR model via equations, in order to show restrictions over contemporaneous structural coefficients; a) for first group;

p

p

p

PIRit +a12 RIAt +a13 CIAt +a14 CPIt + a15 ROAt =b10 + c11,i PIRit-i + c12,i RIAt-i + c13,i CIAt-i + p

p

i=1

i=1

i=1

p

p

c14,i CPIt-i + c15,i ROAt-i 1.1a I=1

i=1

p

a21 PIRt +RIAt +a23 CIAt +a24 CPIT + a25 ROAt =b20 + c21,i PIRt-i + c22,i t-i + c23,i t-i + p

p

i=1

i=1

i=1


i=1

p

p

p

a31 PIRt +a32 RIAt +CIAt +a34 CPIt + a35 ROAt =b30 + c31,i PIRt-i + c32,i RIAt-i + c33,i CIAt-i + p

p

i=1

i=1

i=1


i=1

p

p

p

a41 PIRt +a42 RIAt +a43 CIAt +CPIt + a45 ROAt =b40 + c41,i PIRt-i + c42,i RIAt-i + c43,i CIAt-i + p

p

i=1

i=1

i=1


i=1

p

p

p

a51 PIRt +a52 RIAt +a53 CIAt +a54 CPIt + ROAt =b50 + c51,i PIRt-i + c52,i RIAt-i + c53,i CIAt-i + p

p

i=1

i=1

i=1


1

i=1

The reason for ordering this vector like this will be discussed in the section of variable ordering.

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International Journal of Economic Perspectives, 2014, Volume 8, Issue 4, 19-38. b) for second group ;

p

p

p

PIRit +a12 RIEt +a13 CIEt +a14 CPIt + a15 ROEt =b10 + c11,i PIRit-i + c12,i RIEt-i + c13,i CIEt-i + p

p

i=1

i=1

i=1

p

p

c14,i CPIt-i + c15,i ROEt-i 1.1b I=1

i=1

p

a21 PIRt +RIEt +a23 CIEt +a24 CPIt + a25 ROEt =b20 + c21,i PIRt-i + c22,i t-i + c23,i t-i + p

p

i=1

i=1

i=1


i=1

p

p

p

a31 PIRt +a32 RIEt +CIEt +a34 CPIt + a35 ROEt =b30 + c31,i PIRt-i + c32,i RIEt-i + c33,i CIEt-i + p

p

i=1

i=1

i=1


i=1

p

p

p

a41 PIRt +a42 RIEt +a43 CIEt +CPIt + a45 ROEt =b40 + c41,i PIRt-i + c42,i RIEt-i + c43,i CIEt-i + p

p

i=1

i=1

i=1


i=1

p

p

p

a51 PIRt +a52 RIEt +a53 CIEt +a54 CPIt + ROEt =b50 + c51,i PIRt-i + c52,i RIEt-i + c53,i CIEt-i + p

p

i=1

i=1

i=1


i=1

In the related equations above, p is number of maximum lag. Each equation in the system above shows that an internal variable at the t time affects from other variables at the t time, lagged values, current value, and other variables are in relation with p lagged values. In the sense of structural coefficients, Leduc, Sill, and Stark (2007) and Mehra and Herrington (2008) provides a similar restriction in their works and make shocks ( ), itself, lagged values, and lagged values of other variables having no relation. These restrictions; = = = = 0 = = = 0 (2) = = 0 = 0 With these structural restrictions, the B coefficient in the Equation 1 reformed again and diagonal elements become 1 whereas elements over the diagonal are 0. These restrictions have designed by taking the differentiation order in [ROA, RIA, CIA, CPI, PIR] or [ROE, RIE, CIE, CPI, PIR] into consideration. In the differentiation order, each variable in the parenthesis is affected simultaneously by the variables placed before it and it is also not affected by the variables placed after it. It is necessary to express some information about these structural restrictions in this sense. These are; 1. All restrictions over contemporaneous structural coefficients are zero and there is no restriction over lags of structural parameters. 2. Having no restriction over the simultaneity relation among internal variables does not mean that these simultaneity coefficients are zero. 3. The zero restriction in simultaneity coefficients does not mean that variables with zero coefficients will not affect the variables placed before it in the order. But effects within lags of all other variables are allowed. By multiplying the Equation 1with the B-1, a standard VAR(p) model is obtained; (3)

Yt = ∏0+∏1Yt-1+et


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International Journal of Economic Perspectives, 2014, Volume 8, Issue 4, 19-38. −1

Here, ∏0=Β

Α;

−1

∏ 1= Β

C and et=B-1εt.

In the Equation ∏0and ∏1 matrices are 5x5 dimensions reduced form coefficients matrix and et is 5x1 dimensions reduced form error vector. In this sense, structural shock ( t), and structural coefficients (A, B, C ) in the structural VAR system forms the distinguished structural VAR model by being defined again with reduced form parameters ∏0, ∏1, et). With a general definition, by placing (n2-n)/2 restrictions over the structural VAR model, restriction parameters are defined again.2 Here, n is the number of variables in the model. Because our structural VAR model is 5x1 dimensions, 10 restrictions should be placed over our structural coefficients. Because of this, it will be seen that 10 restrictions have been placed over structural parameters in our structural model (Tetik and İvrendi, 2013). 4.3. Pre-Tests It is important to perform pre-tests in order to obtain meaningful results from VAR models. In this sense, it is necessary to predict VAR by performing stability tests of variables in the model, test for the most suitable lag period, and Granger causality analysis tests. All tests and estimations done in our work have been performed via JMulTi packet program. 4.3.1 Stability Tests In order to use VAR model, all variables used within the model should be stable. If variables that will be used in the model are not stable (carrying unit root), the estimation results of the model will be meaningless. In this sense, if we look at to graphical shapes in their first differences for the serial for the 1st group as [ROA, RIA, CIA, CPI, PIR] and the serial for the 2nd group as [ROE, RIE, CIE, CPI, PIR]. It can be understood from the figures that first differences of serials are stable according to their levels. In order to see stability of serials in an econometrical manner, widely-used Augmented Dickey-Fuller stability test has been employed. According to the ADF test results, it has been found that first differences of all variables are stable (as seen in Table 1.2) although no variable is stable at the significance level of 1%.3 Our analysis continues with the form of all variables as their 1st differences are taken. At this point, the orders of variables in our model are for the 1st group as as [ROA_d1, RIA_d1, CIA_d1, CPI_d1, PIR_d1], and for the 2nd group as [ROE_d1, RIE_d1, CIE_d1, CPI_d1, PIR_d1] 4.4. Determining the Period Length of Lags Determining the period length lags in VAR systems is too important, because it affects the analyses results greatly. Because increased lag length causes permissiveness to decrease fast, the most appropriate lag length is as short as not causing data lose about interaction of serials, and as long as causing no autocorrelation among error terms. In the literature, Akaike Data Criterion, Schwarz Daha Criterion, Hannan-Quinn Data Criterion (HQ) and Final Prediction Error are used for determining the optimal lag length. The optimal lag length is determined in these tests according to the smallest value. Hacker and Hatemi (2008) have searched performances of different criteria for choosing optimal lag length in both stable and unstable VAR models. In this sense, SIC has been found as having better performance. Lag test results for the model in the 1st. and the 2nd group are as table 4.3. Table 4.3 shows that lag length of the models in both groups is 6. 4.5. Order of Variables In the VAR system, action-reaction functions used for determining reactions of variables to shocks are sensitive to the order of variables in the system. The most common application in the literature is related to ordering variables from external to internal. For the first variable in the system, being the most external variable means not showing reaction to the shocks from other variables while being not reaction oriented for both its self-shocks and shock come from other variables; as being the most internal one (Çiçek, 2005). 2

For detailed information, works by Sims (1986) and Bernanke (1986) can be examied. According to ADF test results, ADF value of profita is -1.27, ADF value of interest-incomea is -0.70, ADF value of the commissionincomea is -0.82, ADF value of cpi variable is -1.91 and ADF value of pol-interest variable is -3.11.

3


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PIR, which is used as politics variable, placed in the first order because it is determined by the central bank as external, not affected by other variables, and the reason for all other variables as the result of causality tests. Net interest incomes and fee and commission incomes variables have become second and third variables according to causality tests and because they affect bank profits. CPI variable has become the last but one variable in the system according to causality tests. Finally, bank profits has become last variable. It has become the last one because it does not affect by the others and it is not reason for any variables. Eventually, our variables are added to the model as first differences. 4.6. Estimates of Structural VAR model It is expected that structural VAR model provides more meaningful results in examining interaction between money politics and financial variables. But before predicting the model, it is necessary to examine simultaneity and causality among these variables (Lutkepohl, 2005). Otherwise, forming cause-effect and causality relation among variables in the model becomes related to only theoretical reasons. Before the SVAR model, it is an important approach to test cause-effect and causality among variables in the model statistically for significance of the model. In this sense, in the Table 4.4, and Table 4.5, Granger causality test has been used for examining simultaneity and causality among the related variables. It is possible to have new results by changing the place of variables in H0 hypothesizes but obtained results above are enough for us. There is a simultaneity situation among all variables when we examine the causality and simultaneity relation among variables. This situation is an important starting for our structural VAR model, on which we will work. Also, it is seen when we examine the 1st group that causality among variables is high and only CPI and profit variables are not reason of other variables. It is though that it is because CPI and profit variables are last two variables before forming structural VAR model. This result is same for the 2nd group. When we predict SVAR model, predictions of contemporaneous coefficients of limited equations are shown. Rows within Table 4.6 and Table 4.7 are for the related parameters of these limited equations. Coefficients in Table 4.6 and 4.7 are generally contemporaneous coefficients in equations from 1.1 to 1.5. All parameters except from six parameters in Table 4.6, and three parameters in Table 4.7 are statistically significant and affect other variables in the SVAR model simultaneously. Generally, contemporaneous coefficients in of our SVAR model seem consistent with contemporaneous interaction theoretical expectations. Also, lags of depended variables itself and other variables within equations from 1.1a to 1.5a and 1.1b to 1.5b are significantly explainable because all coefficients over the diagonal in Table 4.6 and 4.7 are statistically meaningful. (Tetik and İvrendi, 2013) 4.7. Impulse-Response Analysis in the Sense of Structural VAR Model Comments regarding to predicted results of SVAR models are made by examining effect-reaction function graphics. Impulse-response analysis is graphical visualization of reactions given by variables to shocks. Over the vertical axis of impulse-response function obtained from predicted result of the SVAR model, direction and percentage size of reactions given by other variables to the one standard deviation increase shock (given to the related variable) are shown. On the other hand, the horizontal axis shows the spend time (in the day scale) after giving the shock. Cut lines are for 95% confidence interval for reaction of variables and have important role on detecting statistically meaningfulness of the results.4 In the first column in Figure 4.3, reaction of other variables to the PIR_d1 is shown. Bank asset profitability (ROA_d1) has shown a negative contemporaneous reaction to a positive shock within PIR _d1 variable and after that it has come back to its old location by decreasing. Theoretically, an increase made by the central bank within politics interests can be explained as increase in funding cost in banking sector and having negative effect on interest margins because of expiry mismatch. It is also seen that other variables do not show statistically meaningful contemporaneous reaction to a positive shock happened in PIR_d1 variable. In the second column of Figure 4.3, effects of a positive shock over the RIA_d1, which is the rate of net interest income of banks to the assets, is seen. There are two significant effects over here. As first, rate of fee and commission incomes to assets (CIA_d1) has shown positive contemporaneous reaction to a positive shock 4

Hall’s CIS has been used for the interval, which is the reliability of this frame model.


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International Journal of Economic Perspectives, 2014, Volume 8, Issue 4, 19-38. happened in RIA_d1 variable. Theoretically, there are two reasons of increase in interest income. These are interest rate increases and more credit placements. The reason for one increase in fee and commission income because of one increase in interest income is credit allocation fee taken by banks for the credits given by them. Also, increases in interest rates and commission rates, which are applied by banks to services like letter of guarantee, cause this income item to increase. As second, bank profits (ROA_d1) have shown positive, contemporaneous reaction to a positive shock happened in the RIA_d1 variable. When it is examined theoretically, it can be expressed that increase in bank profits because of one increase in net interest incomes is a meaningful result. In the third column of Figure 4.3, effects of a positive shock over the CIA_d1, which the rate of fee and commission income of banks to the assets, is seen. Bank asset profitability (ROA_d1) has shown a positive reaction to a positive shock in the commission-incomea_d1 variable. As similar to the one in net interest income, this result seems appropriate theoretically. When these two effects are compared, it is seen it shows more reaction to one increase in net interest incomes rather than one increase in bank profits commission incomes. In the first column of Figure 4.4, statistically meaningful reaction of a positive shock in politics interest variable over other variables is seen. In the second column of the same figure, a positive shock within RIA_d1, which is the rate of net interest income of banks to the equity, is seen. Here, two meaningful effects as similar to the ones seen in Figure 4.3, are seen. These effects are occurred contemporaneous, positive reaction from equity rate of fee and commission incomes to a positive shock happened in RIA_d1 (CIA_d1) and bank equity profitability (ROA_d1). Theoretically, it can be said that explanations of these reactions are parallel with the comments for Figure 4.3. 5. CONCLUSION AND EVALUATION In this study, the relation between profits, fee and commission incomes, net interest incomes of the banks in Turkey with the inflation and politics interest has been analyzed. Analyze has been made by dividing the variables into two groups. In the first group, the rate of profits before tax, net interest incomes, and fee and commission incomes of banks to the assets has been used while it has been the rate of these variables to the equity. After that, models have been formed and analyzed by adding mean of three-monthly politics interest and mean of three-monthly Consumer Price Index to these variables in both two groups. When the analyze findings are examined, it is seen that one increase made by the central bank in politics interests cause negative effects on asset profitability in banking sector. This finding has been explained as the increase in politics interests will increase funding costs in banking sector and it will have negative effects on net interest margins because of expiry mismatch. This finding does not overlap with the ones by Kaya (2002). The reason of this situation may be the periods taken into consideration in the studies or usage of nominal interest rates rather than real interests, in this study. According to another finding in the analyze, one increase in the rate of net interest incomes of banks to the assets increases the rate of fee and commission incomes of banks to the assets. This result may be explained as that this income item increases because of reasons like one increase in net interest incomes of banks, and increase in commission rates applied by banks to services like credit allocation fee taken by banks for the given credits, and the letter of guarantee. Another analyze finding is that one increase in the rate of fee and commission income to the assets and also rate of net interest incomes of banks to the assets increase the bank asset profitability. But when we compare these two effects, it is seen that effect of increase in interest incomes on asset profitability is bigger than the effect of commission incomes on asset profitability. It is also seen that one increase in the rate of net interest incomes of banks to their equities causes increase in capital stock profitability of banks. As final, effect of the inflation over bank profits has been examined and it has been found that effect of one increase in inflation on asset profitability is statistically not meaningful. However, it has also seen that the inflation affects equity profitability of banks in a meaningful and positive manner. This different effect of the inflation may because of more increase in assets rather than the equity. According to the results, equity will increase when the inflation increases and equity will decrease when the inflation decreases. These results are parallel with some other results in the literature. Data used within the econometric analyze section of the work International Journal of Economic Perspectives ISSN 1307-1637 © International Economic Society http://www.econ-society.org

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International Journal of Economic Perspectives, 2014, Volume 8, Issue 4, 19-38. formed by nominal values. Because of this, it can be thought that profits in the inflationist period are virtual ones. In order to make a clear decision on this idea, it will be better to perform analyze works again by using the data from which the inflation purified. On the other hand, effects of inflation and interest rates over asset profitability of the banking system and equity profitability have been different. As it is known, the first objective of Turkish Republic Central Bank is to ensure price stability in the market. Central Bank uses interest rates as a fighting tool against the inflation, by limiting the consumption as a money politics tool. This situation may cause a different flow for interest and make the inflation rates to create different effects over analyzes. Within the non-econometric analyze section of the study, gross interest incomes, interest expenses, net interest incomes, net fee and commission incomes, equity, and asset totals related to 2002:4-2014-1 term in the banking system has been examined. Variables except from equity and asset have been transformed into yearly as quarterly returns. After that, all data has been purified from the inflation by using the Consumer Price Index. According to the rates calculated via formed real data set, net interest income, net fee and commission incomes, and the rates of the profit before tax to the equity have been decreased generally. As the same way, values regarding to incomes and expenses have been adjusted with the corrected asset. According to the calculations, net interest income, net fee and commission incomes, and the rate of profit before tax to the asset have decreased in time. It can be understood from these values that profitability rates in the banking system have decreased. However, data related to the variables used in analyze have increased in real terms, according to 2002. Since the starting year, the highest real size has been ensured. This has been followed by the real growth in the equity. It is understood that assets and the equity of the banking system has shown a remarkable growth because of reasons like profit distribution limitation, and increased work capacity by trust environment in the market as a result of the decreased inflation etc., which are provided by the Banking Regulation and Supervision Agency as regulations. It should be seen as a common situation that rates like asset profitability, and equity profitability are in a decrease trend because of high grow in these two items. With the decreased inflation, real increase in interest incomes of banks become slower and interest expenses have located in a lower real size than gross interest incomes. As a result of this, net interest income has reach to a more real grow increase than both gross interest income and interest expense. It can be expressed from this situation that banks do not allow domestic credit-deposit interest interval, which has dropped behind in decreased interest and inflation environment, to decrease in a real manner. As one of the most wondered subjects, weight of net fee and commission incomes within net interest and profit before tax has provided a stable course. This result shows that effects of net fee and commission incomes over the banking system are too far according to the effects by net interest. These items keep its real growth but its share within incomes does not reach to high values. According to the index prepared based on 2002, the highest increase has shown by the assets. High momentum seen in net fee and commission incomes since 2003 has decreased its effect in 2009. According to the index, the most serial is interest expenses. In this situation, net interest income has reached to top levels because the gross interest incomes have been high according to the index value. According to the index, shown in the Figure 3.6, profit before the tax decreases in last two quarters. It can be thought that this is because of applications like decreasing the number of credit card installments. This study can be improved by using the real interest rate rather than the used politics interest rate, employing the real data regarding to variables in causality and reaction analyses, and adding some different macroeconomic variables like national income variable to the research scope. REFERENCES Akbaş, H.E., (2012). Determinants of Bank Profitability: an Investigation on Turkish Banking Sector. Öneri, 10(37), 103-110. Atasoy, H., (2007). Türk Bankacılık Sektöründe Gelir-Gider Analizi ve Karlılık Performansının Belirleyicileri. Türkiye Cumhuriyet Merkez Bankası Uzmanlık Tezi, Ankara.


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International Journal of Economic Perspectives, 2014, Volume 8, Issue 4, 19-38. Bakırcı, F., Sarıkaya, M., (2012). Türkiye’de Yüksek ve Düşük Enflasyon Dönemlerinde Bankaların Etkinliği ve Etkinliğe Etki Eden Faktörler. Ekev Akademi Dergisi, 16(51), 369-392. Bankacılık Düzenleme ve Denetleme Kurumu (BDDK), 2014. Türk Bankacılık Sektörü Genel Görünümü-Aralık 2013, Ankara. Borsa İstanbul İnternet Sayfası, www.borsaistanbul.com.tr. Çiçek, M. (2005). Türkiye'de Parasal Aktarım Mekanizması: VAR (Vektör Otoregresyon) Yaklaşımıyla Bir Analiz, İktisat, İşletme ve Finans, ss.82-105. Demirgüç-Kunt, A. and Huizinga, H., (1999). Determinants Of Commercial Bank Interest Margins And Profitability. Some International Evidence. World Bank Economic Review, 13(2), 379-408. Gülhan, Ü., Uzunlar, E., (2011). Bankacılık Sektöründe Karlılığı Etkileyen Faktörler: Türk Bankacılık Sektörüne Yönelik Bir Uygulama. Atatürk Üniversitesi Sosyal Bilimler Enstitüsü Dergisi, 15 (1), 341-368. Güngör, B., (2007). Türkiye’de Faaliyet Gösteren Yerel ve Yabancı Bankaların Kârlılık Seviyelerini Etkileyen Faktörler: Panel Veri Analizi. İktisat İşletme ve Finans, 22(258), 40-63. Gwin, C.R., College, B., (2000). Inflation and Increasing http://faculty.babson.edu/gwin/research/inflation.pdf , (Quoted: 10.06.2014)

Profit

Margins.

Hacker , R.S., and Hatemi, A.J. (2008). Optimal lag-length choice in stable and unstable VAR models under situations of homoscedasticity and ARCH, Journal of Applied Statistics, 3:6,601-615. Kaya, Y.T., (2002). Türk Bankacılık Sektöründe Karlılığın Belirleyicileri 1997-2000. MSPD Çalışma Raporları, BDDK yayınları, 2002(1), 1-16. Kaya, Y.T., Doğan, E., (2005). Dezenflasyon Sürecinde Türk Bankacılık Sisteminde Etkinliğin Gelişimi. ARD Çalışma Raporları, BDDK Yayınları, 2005(10). 1-16. Leduc, S., Sill, K., and Stark, T. (2007). Self-Fulfilling Expectations and the Inflation of the 1970s: Evidence from the Livingston Survey, Journal of Monetary Economics 54, ss.433-59. Lutkepohl, H. (2005). New Introduction to Multiple Time Series Analysis, ISBN 3-540 40172-5, SpringerVerlag Berlin Heidelberg 2005. Mehra, Y., Herrington, C. (2008). On the Sources of Movements in Inflation Expectations: A Few Insights from a VAR Model, Federal Reserve Bank of Richmond Economic Quarterly 94, No 2, ss.121-146. Naceur, S., (2003). The Determinants Of The Tunisian Banking Industry Profitability: Panel Evidence. ERF Research Fellow, Department of Finance, Université Libre de Tunis. http://www.mafhoum.com/press6/174E11.pdf, (Quoted: 17.06.2014) Pouw L., Kakes, J., (2013). What Drives Bank Earnings? Evidence for 28 Banking Sectors. Applied Economics Letters, 20(11), 1062-1066. DOI: 10.1080/13504851.2013.783676. Sayılgan, G., Yıldırım, O., (2009). Determinants of Profitability in Turkish Banking Sector: 2002-2007. International Research Journal of Finance and Economics, 28, 207-213. Sufian, F., (2009). Factors Influencing Bank Profitability in a Developing Economy: Empirical Evidence from Malaysia. Global Business Review, 10(2), 225-241. Sufian, F., Kamarudin, F., (2012). Bank-Specific and Macroeconomic Determinants of Profitability of Bangladesh’s Commercial Banks. Bangladesh Development Studies, XXXV, December, 4, 1-28. Sufian, F., (2012). Determinants of Bank Profitability in Developing Economies: Empirical Evidence from the South Asian Banking Sectors. Contemporary South Asia, 20(3), September, 375–399. International Journal of Economic Perspectives ISSN 1307-1637 © International Economic Society http://www.econ-society.org

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Taşkın, F.T., (2011). Türkiye’de Ticari Bankaların Performansını Etkileyen Faktörler. Ege Akademik Bakış, 11(2), Nisan, 289 – 298. Tetik, M., & İvrendi, M. (2013). Para Politikası Beklentilerinin Finansal Yatırım Araçları Üzerindeki Etkileri: Türkiye Örneği. Iktisat Isletme ve Finans,28(333), 107-136. Türkiye Bankalar Birliği İnternet Sayfası, www.tbb.org.tr Türkiye İstatistik Kurumu İnternet Sayfası, www.tuik.gov.tr Vejzagic, M., Zarafat, H., (2014). An Analysıs Of Macroeconomıc Determınants Of Commercıal Banks Profıtabılıty In Malaysıa For The Perıod 1995-2011. Asian Economic and Financial Review, 4(1):41-57. Vu, H., Nahm, D., (2013), The Determinants of Profit Efficiency of Banks in Vietnam. Journal of the Asia Pacific Economy, Vol. 18, No. 4, 615–631, http://dx.doi.org/10.1080/13547860.2013.803847


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International Journal of Economic Perspectives, 2014, Volume 8, Issue 4, 19-38. APPENDIX TABLES Table 4.1. Variables in the model 1st Group ROA

2nd Group

Return of Asset Before Tax

ROE

Rate of Net Interest Incomes to the Asset Rate of Fee and Commission CIA Incomes to the Asset Mean of Three-Monthly CPI Consumer Price Index Mean of Three-Monthly PIR Politics Interest Rates Table 4.2. ADF unit root test results RIA

All Term ROA_d1 RIA_d1 CIA_d1 ROE_d1 RIE_d1 CIE_d1 CPI_d1 PIR_d1

Test Form Level + Constant Term Level + Constant Term Level + Constant Term Level + Constant Term Level + Constant Term Level + Constant Term Level + Constant Term Level + Constant Term

Table 4.3. Lag length tests Test type Akaike Info Criterion Final Prediction Error Hannan-Quinn Criterion: Schwarz Criterion

RIE CIE CPI PIR

ADF Value -7.4759 -4.0455 -5.0651 -7.7283 -4.6777 -3.9818 -7.1106 -3.8921

Return of Equity Before Tax Rate of Net Interest Incomes to the Equity Rate of Fee and Commission Incomes to the Equity Mean of Three-Monthly Consumer Price Index Mean of Three-Monthly Politics Interest Rates

Davidson and Mackinnon Critical Values 1% 5% 10% -3.43 -2.86 -2.57 -3.43 -2.86 -2.57 -3.43 -2.86 -2.57 -3.43 -2.86 -2.57 -3.43 -2.86 -2.57 -3.43 -2.86 -2.57 -3.43 -2.86 -2.57 -3.43 -2.86 -2.57

1st group

2nd group

Number of optimal lag 6 10 6 6

Number of optimal lag 6 10 6 6


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International Journal of Economic Perspectives, 2014, Volume 8, Issue 4, 19-38. Table 4.4. Granger and Instantaneous Causality Tests for the SVAR Model for 1st Group Variables. Test-1 for Granger causality Test statistic H0: “PIR_d1” is not Granger reason of “RIA_d1, CIA_d1, CPI_d1, pval-F= 0.0002 l = 3.6764 ROA_d1”. Simultaneity causality Test-1 Test statistic: pval-Chi= There is not simultaneity reason between H0: “PIR_d1” and “RIA_d1, c = 27.8113 0.0000 CIA_d1, CPI_d1, ROA_d1”. Test-2 for Granger causality Test statistic H0: “RIA_d1” is not Granger reason of ““PIR_d1, CIA_d1, CPI_d1, pval-F= 0.0006 l = 3.3155 ROA_d1”. Simultaneity causality Test-2 Test statistic: pval-Chi= There is not simultaneity reason between H0: “RIA_d1” and “PIR_d1, c = 19.9450 0.0005 CIA_d1, CPI_d1, ROA_d1”. Test-3 for Granger causality Test statistic l = H0: “CIA_d1” is not Granger reason of ““PIR_d1, RIA_d1, CPI_d1, pval-F= 0.0006 3.3459 ROA_d1”. Simultaneity causality Test-3 Test statistic: pval-Chi= There is not simultaneity reason between H0: “CIA_d1” and “PIR_d1, c = 20.7141 0.0004 RIA_d1, CPI_d1, ROA_d1”. Test-4 for Granger causality H0: “CPI_d1” is not Granger reason of PIR_d1, RIA_d1, CIA_d1, ROA_d1”.

Test statistic I = 0.7772

pval-F= 0.7380

Test statistic c = 15.3226

pval-Chi= 0.0041

Test statistic l = 0.9858

pval-F= 0.5058

Test statistic: c = 23.8968

pvalChi=0.0001

Simultaneity causality Test-4 There is not simultaneity reason between H0: “CPI_d1” and “PIR_d1, RIA_d1, CIA_d1, ROA_d1”. Test-5 for Granger causality H0: “ROA_d1” is not Granger reason of “PIR_d1, RIA_d1, CIA_d1, CPI_d1”. Simultaneity causality Test-5 There is not simultaneity reason between H0: “ROA_d1” and “PIR_d1, RIA_d1, CIA_d1, CPI_d1”.

*Bold cells show statistically significant coefficients in the SVAR model Table 4.5. Test results for the causality relation among 2nd group variables. Test-1 for Granger causality H0: “PIR_d1” is not Granger reason of “RIE_d1, CIE_d1, CPI_d1, ROE_d1”. Simultaneity causality Test-1 There is not simultaneity reason between H0: “PIR_d1” and “RIE_d1, CIE_d1, CPI_d1, ROE_d1”. Test-2 for Granger causality H0: “RIE_d1” is not Granger reason of ““PIR_d1, CIE_d1, CPI_d1, ROE_d1”. Simultaneity causality Test-2 There is not simultaneity reason between H0: “RIE_d1” and “PIR_d1, CIE_d1, CPI_d1, ROE_d1”. Test-3 for Granger causality H0: “CIE_d1” is not Granger reason of ““PIR_d1, RIE_d1, CPI_d1, ROE_d1”. Simultaneity causality Test-3 There is not simultaneity reason between H0: “CIE_d1” and “PIR_d1, RIE_d1, CPI_d1, ROE_d1”. Test-4 for Granger causality H0: “CPI_d1” is not Granger reason of PIR_d1, RIE_d1, CIE_d1, ROE_d1”. Simultaneity causality Test-4 There is not simultaneity reason between H0: “CPI_d1” and “PIR_d1, RIE_d1, CIE_d1, ROE_d1”.


pval-F= 0.7317


pval-Chi= 0.0000


pval-F= 0.0440


pval-Chi= 0.0281


pval-F= 0.0295


pval-Chi= 0.0000

Test statistic I = 0.6308

pval-F= 0.8797

Test statistic c = 110.6276

pval-Chi= 0.0000


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International Journal of Economic Perspectives, 2014, Volume 8, Issue 4, 19-38. Test-5 for Granger causality H0: “ROE_d1” is not Granger reason of “PIR_d1, RIE_d1, CIE_d1, CPI_d1”. Simultaneity causality Test-5 There is not simultaneity reason between H0: “ROE_d1” and “PIR_d1, RIE_d1, CIA_d1, CPI_d1”.


pval-F= 0.0007


pvalChi=0.4257

*Bold cells show statistically significant coefficients in the SVAR model. Table 4.6. Contemporaneous Structural Coefficients for 1st Group. a11 Prediction 7.3286 0.00 0.00 Std. dev. {0.8093} a21 a22 Prediction: -0.2160 Prediction 1119.32 Std. dev. { 1.1448} Std. dev. {123.608} 0.00 a31 Prediction 0.4227 Std. dev. {1.1460}

a32 -631.15 Std. dev. {188.192} Prediction

0.00

0.00

0.00

0.00

0.00

0.00

a33 Prediction 7.9338 Std. dev. {0.8761}

a41

a42

a43

a44

Prediction -7.4954

Prediction -198.04

Prediction 1.7181

Prediction 191.277

Std. dev. {1.4144}

Std. dev. {201.872}

Std. dev. {1.2535}

Std. dev. {21.1231}


a52 Prediction -518.424 Std. dev. {210.970}

a53 Prediction -1.2336 Std. dev. {1.2751}


0.00 a54 Prediction 414.00 Std. dev. {45.719}

*Bold cells show statistically significant coefficients in the SVAR model Table 4.7. Contemporaneous Structural Coefficients for 1st Group. a11 Prediction 4.8186 0.00 0.00 Std. dev. { 0.5321} a21 a22 Prediction: 0.0350 Prediction 269.8610 Std. dev. { 0.7525} Std. dev. { 29.8012 } 0.00 a31

a32

a33

Prediction -4.0513

Prediction -114.8143

Prediction 16.4873

Std. dev. {

0.8755}

Std. dev. {

44.0111}

Std. dev. {

1.8207}

0.00

0.00

0.00

0.00

0.00

0.00

a41

a42

a43

a44

Prediction -18.3306

Prediction -103.4648

Prediction 2.2507

Prediction 222.6784

Std. dev. {

2.2504}

a51 Prediction 6.7104 Std. dev. { 3.1163}

Std. dev. {

47.2047 }

a52 Prediction -163.6215 Std. dev. { 51.8201}

Std. dev. {

2.5868}

a53 Prediction 2.1207 Std. dev. { 2.6093 }

Std. dev. {

24.5907}

a54 Prediction -93.9925 Std. dev. { 36.2925 }

0.00 a54 Prediction 43.3016 Std. dev. { 4.7819}

*Bold cells show statistically significant coefficients in the SVAR model


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International Journal of Economic Perspectives, 2014, Volume 8, Issue 4, 19-38. FIGURES: Figure 3.1. Rates of Quarter Term Equity Profitability, Which Has Been Adjusted and Annualized According to the Interest5 50% 45% 40% 35% 30% 25% 20% 15% 10% 5% 0%

Net Interest Income/Equity Commission Income/Equity

2014-1

2013-2

2012-3

2011-4

2011-1

2010-2

2009-3

2008-4

2008-1

2007-2

2006-3

2005-4

2005-1

2004-2

2003-3

2002-4

Profit Before Tax/Equity

Years

Figure 3.2. Equity Profitability Rates Adjusted and Annualized According to the Inflation6 6% 5% 4% 3%

Net Interest Income/Assets

2%

Commission Income/Assets

1%

Profit Before Tax/Assets

2014-1

2013-2

2012-3

2011-4

2011-1

2010-2

2009-3

2008-4

2008-1

2007-2

2006-3

2005-4

2005-1

2004-2

2003-3

2002-4

0%

Years

5

In the third quarter of 2005, important operations related to unions, transfer, and liquidation have realized. During this period, “Provision for Loans and Other Receivables” at the total of 3,3 billion TRL and “Other Activity Expenses” at the total of 7,1 billion TRL have been occured as important expenses. Because of this, the result of third quarter activity has closed with loss. Although there is no fluctuation in usual incomes and expenses, the amount of profitability before the tax and the rate of profitability before the tax / equity have decreased. 6 The reasons for the decrease in profitability before the tax / asset profitability in third quarter of 2005 are the ones explained in Figure 3.1.


34

International Journal of Economic Perspectives, 2014, Volume 8, Issue 4, 19-38. Figure 3.3. Rate of Net Interest and Commission Incomes, Which Have Been Adjusted And Annualized, to the Total Interest and the Profit Before the Tax. 400% Net Interest Income/Gross Interest Income

300% 200%

Net Interest Income/Profit Before Tax

100% 2014-1

2013-2

2012-3

2011-4

2011-1

2010-2

2009-3

2008-4

2008-1

2007-2

2006-3

2005-4

2005-1

2004-2

2003-3

2002-4

0%

Years

Net Commission/Net Interest Income Net Commission/Profit Before Tax

600,000 500,000 400,000 300,000 200,000 100,000 0

Adjusted Interest Income Adjusted Interest Expense Adjusted Net Interest Income Adjusted Commission 2002-4 2003-3 2004-2 2005-1 2005-4 2006-3 2007-2 2008-1 2008-4 2009-3 2010-2 2011-1 2011-4 2012-3 2013-2 2014-1

Million TRY

Figure 3.4. As Associated With Banks, Some Financial Performances Adjusted According to the Inflation

Years

Adjusted Profit Before Tax Adjusted Equity Adjusted Assets

70,000 60,000 50,000 40,000 30,000 20,000 10,000 0

Adjusted Interest Income Adjusted Interest Expense Adjusted Net Interest Income Adjusted Commission 2002-4 2003-3 2004-2 2005-1 2005-4 2006-3 2007-2 2008-1 2008-4 2009-3 2010-2 2011-1 2011-4 2012-3 2013-2 2014-1

Million TRY

Figure 3.5. Financial Performance, Which Have Been Adjusted According to the Inflation Except from the Asset

Adjusted Profit Before Tax Adjusted Equity

Years


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International Journal of Economic Perspectives, 2014, Volume 8, Issue 4, 19-38. Figure 3.6. Taking the 2002:4 Term into Consideration, Financial Performance Index, Which Have Been Adjusted According to the Inflation 600.00

Index Value

500.00 Adjusted Interest Income

400.00

Adjusted Interest Expense 300.00

Adjusted Net Interest Income

200.00

Adjusted Commission

100.00

Adjusted Profit Before Tax Adjusted Equity 2002-4 2003-3 2004-2 2005-1 2005-4 2006-3 2007-2 2008-1 2008-4 2009-3 2010-2 2011-1 2011-4 2012-3 2013-2 2014-1

0.00

Adjusted Assets

Years

Figure 4.1. The Variables in the Model at Level.


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International Journal of Economic Perspectives, 2014, Volume 8, Issue 4, 19-38. Figure 4.2. The Variables in the First Differences.

Figure 4.3. System Impulse Responses to One Standard Deviation Shock in the 1st Group.

*Solid line represents the point estimate; dashed lines represent 95% CIs based on 2000 replications of the Hall bootstrap; Grey line is zero line.


37

International Journal of Economic Perspectives, 2014, Volume 8, Issue 4, 19-38. Figure 4.4. System Impulse Responses to One Standard Deviation Shock in the 2nd Group.

*Solid line represents the point estimate; dashed lines represent 95% CIs based on 2000 replications of the Hall bootstrap; Grey line is zero line.


38