Available via license: CC BY-SA 4.0
Content may be subject to copyright.
Industrija, Vol.44, No.2, 2016 85
Almir Alihodžić1
Novo Plakalović2
JEL: G2, G20, G21
DOI:10.5937/industrija44-10309
UDC: 336.77:334.7(497.6)
336.781.5
Original Scientific Paper
Determinants of Credit Growth to
Nonfinancial companies in B&H
Article history:
Received: 20 February 2016
Sent for revision: 18 Mart 2016
Received in revised form: 13 May 2016
Accepted: 16 May 2016
Available online: 11 July 2016
Abstract: Non-financial sector in B&H and the companies due to lack of its
own funds for sustainable growth rely on financing its operations through bank
loans. The dominant share of lending to banks in B&H is directed to the
household sector while on the other hand the approval of bank loans to
enterprises is on a smaller scale. Corporate sector due to underdeveloped
capital markets is not able to borrow through the issuance of equity and debt
securities. The main objective of this study is to determine which independent
variables in the regression models have an impact on the amount of approved
loans granted by banks to non-financial sector, i.e. companies. The loans
growth rate will be observed as a dependent variable, and the growth rate of
non-performing loans, the growth rate of operating costs, real GDP growth,
consumer price index, deposit growth rate, deposit interest rate, interest rate
(EURIBOR), and interest rate (LIBOR) will be used as independent variables.
Key words: growth of bank loans, bank loans to nonfinancial companies,
factors of bank loans growth, macroeconomic factors of bank loan growth
Determinante kreditnog rasta nefinansijskog sektora u
Bosni i Hercegovini
Apstrakt: Nefinansijski sector u Bosni i Hercegovini i preduzeća zbog
nedostatka sopstvenih sredstava za održivi rast se oslanjaju na finansiranje
svog poslovanja putem bankarskih kredita. Dominantno učešće u pogledu
kreditiranja banaka u BiH je usmereno prema sektoru stanovništva, dok je sa
1
University of Zenica, Faculty of Economics, Bosnia and Herzegovina,
almir.dr2@gmail.com
2
University of East Sarajevo, Faculty of Economics, Republic of Srpska
Alihodžić A., Plakalović N.: Determinants of Credit Growth to Nonfinancial companies..
86 Industrija, Vol.44, No.2, 2016
druge strane odobravanje kredita preduzećima izraženo u manjem obimu.
Korporativni sector nije u mogućnosti da pozajmljuje novčana sredstva putem
izdavanja vlasničkih i dužničkih hartija od vrednosti zbog nerazvijenosti tržišta
kapitala. Glavni cilj ovog istraživanja je da se utvrdi koje nezavisne varijable u
regresivnom modelu imaju uticaj na visinu odobrenih kredita banaka prema
nefinansijskom sektoru, tj. preduzećima. Stopa rasta kredita će se posmatrati
kao zavisna varijabla, dok stopa rasta nekvalitetnih kredita, stopa rasta
operativnih troškova, stopa rasta realnog BDP-a, indeks potrošačkih cena,
stopa rasta depozita, kamatne stope na depozite, kamatna stopa EURIBOR, i
kamatna stopa LIBOR će se posmatrati kao nezavisne varijable.
Ključne reči: stopa rasta kredita, bankarski krediti nefinansijskim
preduzećima, faktori rasta kredita, makroekonomski faktori rasta bankarskih
kredita.
1. Introduction
In this paper, we try to determine the importance of certain variables on the
growth of bank lending in B&H. Credit expansion in B&H was very strong in
the period up to the moment spill over of the global economic crisis and the
region of Southeast Europe and B&H. Excessive credit expansion has been
developing on the basis of a strong inflow of foreign capital in the country that
is largely touched by banking flows of financial resources. All this resulted in
the emergence of macroeconomic imbalances but at the same time have a
positive effect on consumption and economic growth. In this research, we
focused on the period after the spillover of the crisis and stagnation of
economic growth in the country. We have tried to identify and quantify the
impact of certain factors on the level of credit expansion in B&H in the last 9
years.
This research is designed and presented in four sections. The first section
refers to the introductory considerations, the second part present the relevant
literature, the third part describes the theoretical assumption and perceptions
the regression model and gives a definition of significant independent
variables that affect the loans growth rate alone whereas the last part of the
paper discusses the results of research, based on the application of the
regression model. This research will test the significance of observed financial
variables in the model, where the null hypothesis is the reason why the
independent variables do not significantly affect the dependent ones. In this
context, it is stated that the observed independent variables have the greatest
impact on the growth or decline rate of loans growth rate for the banking
sector in B&H. Finally, there are few interesting concluding remarks.
Alihodžić A., Plakalović N.: Determinants of Credit Growth to Nonfinancial companies..
Industrija, Vol.44, No.2, 2016 87
2. Actual changes in magnitude of bank loans and
deposits in B&H
The banking sector is still a dominating sector in the financial system while the
remaining part of the financial system is rather underdeveloped. B&H banking
sector recorded a slight increase of the balance sheet amount, therefore the
share of banks assets in the total assets of financial intermediaries increased
by 20 basis points. The absence of large domestic institutional investors, lack
of willingness to invest in the securities by households and the corporate
sector are still the limiting factors for the growth of domestic investment funds.
The domestic capital market, due to their segmentation, is not sufficiently
attractive to foreign investors. The most active segment of the capital market
is still trading in domestic debt securities (Central bank of Bosnia and
Herzegovina, Financial Stability Report, 2014., p 41). Bosnian financial market
is the bank-centred, which means that bank loans are the primary source of
financing companies.
Figure 1. Number of banks in the Bosnia and Herzegovina for the period:
2007 – Q2 2015
Source: The author’s research based on a data available on www.fba.ba and www.abrs.ba
Figure 1 shows the movement of the number of banks on the market for a
period from 2007 until the end of the second quarter of 2015. In 2007 in B&H,
there were 7 state-owned banks, whereas in the second quarter of 2015 there
were only 5 state-owned banks. On the other hand, in 2007 there were 25
private banks, while in Q2 2015 there were 21 such banks. For partial
reduction in the number of domestic as well as foreign banks, affected by the
global economic crisis, there was a reduction of the scope of business
activities, and consolidation legislation.
0
5
10
15
20
25
30
35
2007 2008 2009 2010 2011 2012 2013 2014 Q2 2015
Number of banks
Years
State owned
banks
Private banks
Total
Linear (State
owned banks )
Linear (Private
banks )
Linear (Total )
Alihodžić A., Plakalović N.: Determinants of Credit Growth to Nonfinancial companies..
88 Industrija, Vol.44, No.2, 2016
0,00
1.000,00
2.000,00
3.000,00
4.000,00
5.000,00
6.000,00
7.000,00
8.000,00
9.000,00
2007/Q1
2007/Q3
2008/Q1
2008/Q3
2009/Q1
2009/Q3
2010/Q1
2010/Q3
2011/Q1
2011/Q3
2012/Q1
2012/Q3
2013/Q1
2013/Q3
2014/Q1
2014/Q3
2015/Q1
Loans to
Nonfinancial Public
Enterprises
Loans to Private
Enterprises and
Cooperatives
Loans to
Households
Expon. (Loans to
Nonfinancial Public
Enterprises)
Expon. (Loans to
Private Enterprises
and Cooperatives)
Expon. (Loans to
Households)
The stagnating lending activity and a high level of credit risk were the main
features of the corporate sector in B&H in recent year. A low demand of
corporate sector for loans was a consequence of several factors, such as the
long-lasting stagnation of economic activities in the country, weak domestic
demand, low level of personal spending, absence of a significant investment
cycle, and the overall macroeconomic and political circumstances in the
country. (Central bank of Bosnia and Herzegovina, Financial Stability Report,
2014, p 35).
Figure 2. Trend in loans to nonfinancial public enterprises, private enterprises
and cooperatives and loans to households for the period: Q1 2007 – Q2 2015
Source: The authors’ research based on date available on www.cbbih.ba
Annual growth rates of loans were between 2 and 4% during 2014 year. Long-
term loans had slightly higher growth rates compared to short-term loans.
Therefore, annual growth rate of long-term loans to private non-financial
companies amounted up to modest 2% during the year. The main reason for
the decrease in lending activity are the strict conditions for extending new
loans contributed a lot to weak lending activities to non-financial companies.
Slightly higher growth rates of loans were recorded with households. Annual
rate of the growth of the loans to households was on the average around
5.7%, which is significantly higher compared to the growth rates of the loans
to private companies (Annual report of the Central Bank of B&H, p 23).
Alihodžić A., Plakalović N.: Determinants of Credit Growth to Nonfinancial companies..
Industrija, Vol.44, No.2, 2016 89
Figure 3. Trend in deposits to nonfinancial public enterprises, private
enterprises and cooperatives and loans to households for the period: Q1 2007
– Q2 2015
Source: The authors’ research based on date available on www.cbbih.ba
From the above graphic it can be noted that the largest average quarterly
growth of deposits for the period Q1 2007 - Q2 2015 was recorded to be in a
sector of the households, i.e. 6.24%. The second place at the average
quarterly growth of deposits belongs to the sector of the nonfinancial private
enterprises (4.37%). On the other hand, the sector of nonfinancial public
enterprises was recorded of the negative growth rate of 0.51%. The growth of
household deposits cannot be interpreted as the indicator of a better standard
of living, but it is mainly a consequence of the uncertainty in respect of the
future economic circumstances in the country, and the advantage is given to
saving instead of spending. At the same time, the growth of the deposits of
households is the indicator of trust in the banking sector and the decision of
households to choose a safer kind of saving compared to investments in
securities, despite the continued downward trend of deposit interest rates
(Central bank of Bosnia and Herzegovina, Financial Stability Report, 2014 p
33).
3. Brief Literature Review
The main objective of macroeconomic tests that increasingly converge with
the financial crisis is to establish the structural vulnerabilities in financial
systems. The ultimate goal is to score their resilience to shocks and especially
0,00
1.000,00
2.000,00
3.000,00
4.000,00
5.000,00
6.000,00
7.000,00
8.000,00
9.000,00
10.000,00
2007/Q1
2007/Q3
2008/Q1
2008/Q3
2009/Q1
2009/Q3
2010/Q1
2010/Q3
2011/Q1
2011/Q3
2012/Q1
2012/Q3
2013/Q1
2013/Q3
2014/Q1
2014/Q3
2015/Q1
Deposits of
Nonfinancial
Public
Enterprises
Deposits of
Nonfinancial
Private
Enterprises
Deposits of
Households
Expon. (Deposits
of Nonfinancial
Public
Enterprises)
Alihodžić A., Plakalović N.: Determinants of Credit Growth to Nonfinancial companies..
90 Industrija, Vol.44, No.2, 2016
the vulnerability of banks due to losses. Banks credit risk increases with the
deterioration of the situation and the increase in interest payments as a result
of which can be found in many models of credit risk (IMF, 2006).
Some research suggests (Espinoza R. Prasad A. 2010) that in the period
1995-2008 on a sample of 80 banks from the countries of the Gulf
Cooperation Council – GCC, the non-performing ratio worsened as economic
growth slows and interest rates and risk aversion rises. The applied model
shows that the cumulative effects of macroeconomic shocks over a three-year
horizon large (Espinoza R. Prasad 2010, p 1). Specific factors related to
individual banks related to underwriting and efficiency are also related to
future NPLs. Controls on banks efficiency and expansion of the previous
balance (the previous dynamic growth in loans) and are important for the
growth of NPLs. Return effects of NPLs (bank losses) on slowing growth are
also present.
In contrast to research Levine, Loayza, Beck (2000), Favara shows that the
relationship between financial development (the level of liquid liabilities of a
banking system and amount of credit issued to the private sector by banks
and other financial institutions) and economic growth is weak. This is about
the observation of these relationships in the long term. There is a significant
impact of credit growth in the real GDP growth and the magnitude of
transmission channels through which loans on real activity depend on the
specific type of loan (Garcia – M. Escribano, F. Han, 2015) so that the impact
of the credit shock in terms of lending corporations influence mainly through
investments, and credit shocks to consumer credit should go together with
private consumption. Thus, the impact of the credit expansion is seen in this
study by analysing the composition of credit portfolio (corporate, consumer
and housing credit) on economic growth in emerging market economies. At
the same time observe and influence expansion and composition of credit
played in diving real GDP growth in the past.
Countries in which there was a good climate for foreign capital inflows are
usually alive and in sharp credit expansions. Magud N.Reinhart C, Vesperon
E. (2012) analysed the impact of exchange rate flexibility on credit markets
during periods of large capital inflows. Bank credit grows more rapidly and its
composition tilts to foreign currency in economies with less flexible exchange
rate regimes. That is exactly the case in Bosnia and Herzegovina where the
regime currency index was a strong factor of influence on the inflow of foreign
capital and, as a result, there was a huge credit expansion of loans into
domestic sectors in the past. Rapid credit growth has been driven by
successful macroeconomic stabilization, robust growth, and capital inflow in
transition economies. Financial deepening is both expected and welcome, the
recent expansion (to the crisis) appears to have been excessive, as
Alihodžić A., Plakalović N.: Determinants of Credit Growth to Nonfinancial companies..
Industrija, Vol.44, No.2, 2016 91
evidenced by widening current account deficits and prudential concerns in
some countries. (Duenwald C.Gueorguiev N. 2005).
Very rapid credit expansion over several years is a subject to a significant
macroeconomic imbalance, largely fuelled by this rapid credit growth, despite
their overall formidable economic performance since the beginning of their
transition to market economies. Sirtaine S. Skamnelos I. (2007, p 31.) raises
the question of whether the current credit growth is excessive or not.
Arguments have been made, in their paper and in literature, in both directions.
(Sirtaine S. Skamnelos I. ibid.)
Through the monitoring of changes in bank loans over the last decade, the
results of research of Guo K and V. Stepanyan (2011) show that domestic
and foreign funding contribute positively and symmetrically to credit growth.
These results also show that stronger economic growth leads to higher credit
growth and high inflation, while increasing nominal credit, is detrimental to real
credit growth. Loose monetary conditions, either domestic or global, results
and more credit, and the health of the banking sector also matters.
4. Data analysis and methodologies
The date used for this study are the official date published by the Central
Bank of Bosnia and Herzegovina and Banking Agency of the FB&H and the
Banking Agency of the Republic of Srpska, from the period: Q1 2007 – Q2
2015. The research will also use the statistical package SPSS 16.0. The loan
growth rate will be observed as a dependent variable. The independent
variables are as follows:
GRNPL – The growth rate of non-performing loans;
GROC – The growth rate of operating costs;
RGDPG – Real GDP growth;
CPI – Consumer price index;
DGR – Deposit growth rate;
DIR – Deposit interest rate;
EURIBOR - Euro interbank offered rate; and
LIBOR - The London Interbank Offered Rate.
The regression model is an equation with a finite number of parameters and
variables. Depending on whether a model comprised only one or more
variables, there are simple and multiple linear regression models respectively.
In addition to a dependent variable and one or more independent variables,
each regression model contains a random variable. A simple linear regression
model expresses a relationship between the two parameters as follows:
Alihodžić A., Plakalović N.: Determinants of Credit Growth to Nonfinancial companies..
92 Industrija, Vol.44, No.2, 2016
where:
dependent variable,
- unknown parameters that need estimate, and
stochastic variable (error distances).
Unlike the simple regression model, the multiple-linear regression model is
different in that it comprises two or more independent variables.
Specifically, this model consists of independent variable , and
independent variables, which are referred to as: X_ (i,j)=1,2,…..,K.
Table 1. Descriptive explanation of the variables in the model
Variable
Symbol
Description
Loan growth rate
LGR
The annualized change in total loans from the
previous quarter, expressed as a percentage of total
loans at the end of the previous quarter.
Growth rate
nonperforming loans
GRNPL
Banks nonperforming loans to total gross loans (in
%)
The growth rate of
operating costs
GROC
Operating costs-to-total earning assets (in %)
Real GDP growth
RGDPG
Real GDP growth
Consumer Price
Index
CPI
Consumer Price Index
Deposit growth rate
DGR
The Deposit Growth Rate compares the quantity of
deposits held by a financial institution in a given
period to the quantity of deposits from an earlier
period.
Deposit interest rate
DIR
The relationship between interest expenses and
average interest-earning liabilities
Euro Interbank
Offered Rate
EURIBOR
Euribor is short for euro interbank offered rate. The
Euribor rates are based on the average interest
rates at which a large panel of European banks
borrow funds from one another.
The London
Interbank Offered
Rates
LIBOR
The London Interbank Offered Rate is the average
interest rate estimated by leading banks in London
that the average leading bank would be charged if
borrowing from other banks
This empirical study refers to the loan growth rate of the banking sector in
B&H for the period from Q1 2007 to Q2 2015. The data used for this study are
the official data (statistical analysis) of the Central Bank of Bosnia and
Alihodžić A., Plakalović N.: Determinants of Credit Growth to Nonfinancial companies..
Industrija, Vol.44, No.2, 2016 93
Herzegovina and Banking Agency of the Federation of Bosnia and
Herzegovina (FB&H) and the Banking Agency of the Republic of Srpska.
This study used a multiple-linear regression model that assesses the nature
and strength of the bond between a dependent variable, and K independent
variables that are marked with X_ (i, j) = 1,2 , ....., K. Therefore, in this study,
loan growth rate of the banking sector in B&H (LGR) is used as dependent
variable, and the following ones as independent variables: the growth rate
non-performing loan (GRNPL), the growth rate of operating costs (GROC),
real GDP growth (RGDPG), consumer price index (CPI), deposit growth rate
(DGR), deposit interest rate (DIR), Eurointer bank offered rate (EURIBOR),
and The London Inter bank offered rate (LIBOR).
The regression model in this study is presented as follows:
The representativeness of the model will examine calculation of the coefficient
of correlation (r), the coefficient of determination () and adjusted coefficient
of determination
There is also an analysis of variance (ANOVA), which
will test the significance of observed financial variables in the model, where
the null hypothesis is the reason why the independent variables do not
significantly affect the dependent:
The table below illustrates the descriptive statistics of the example.
Table 2. Descriptive statistics of the observed banking performance for the
period: Q1 2007 – Q2 2015
Dependent and independent
variables in the model
Means
Std. Deviation
N
LGR
1.529
2.608
34
GRNPL
9.176
4.764
34
GROC
0.441
0.504
34
RGDPG
6.150
698.365,44
34
CPI
1.091
5.529
34
DGR
2.206
4.829
34
DIR
1.265
0.931
34
EURIBOR
1.647
2.385
34
LIBOR
1.294
1.586
34
Source: Calculation made by the author (SPSS 16.0)
Alihodžić A., Plakalović N.: Determinants of Credit Growth to Nonfinancial companies..
94 Industrija, Vol.44, No.2, 2016
The growth in the real gross domestic product, as well as the deposit growth
rate, showed their highest volatility with a standard deviation of 698.36% and
4.83% for the period from Q1 2007 to Q2 2015 (Table 2). According to the
date the Central Bank of B&H , the realest GDP growth in the reporting period
was recorded in 2007 (6%), so that in 2009 the real GDP growth recorded a
negative value of 2.7%. In the period after 2009, there was a tendency of
further decline in GDP until 2013, as a result of weak economic activity and
weak domestic and foreign demand. According to the date of the B&H Agency
for Statistics (B&H AS) real GDP growth in the fourth quarter of 2014,
compared to the same quarter of the previous year, amounted to the high
2.4% (Central bank of Bosnia and Hercegovina, Bulletin, No. 1., 2015, P. 38).
In the first quarter of 2007, growth in deposits of the corporate sector
amounted to 19.82%, and at the end of the second quarter there was a
decline in deposits to 2.12%. The main reason given fluctuations in the non-
banking sector deposits may be mentioned primarily weakened export
potential and illiquidity of the economy.
5. The research results
Results obtained by regression analysis indicated that the coefficient of
correlation is r=0.89, indicating that there is a strong correlation between the
dependent variable, i.e. the loans growth rate – (LGR) and independent
variables: the growth rate of non-performing loans (GRNPL), the growth rate
of operating cost (GROC), real GDP growth (RGDPG), consumer price index
(CPI), deposit growth rate (DGR), deposit interest rate (DIR), interest rate
(EURIBOR), and interest rate (LIBOR).
The coefficient of determination is =79%, and the adjusted coefficient of
determination is
=0.73. The fact shows that this model described 73% of
the variations to the independent variables makes the model relatively
representative. The significance test also indicates that there is a substantial
influence of certain independent variables on the dependent variable. The
testing the null hypothesis of significance obtained statistically significant data
indicating that there is significant influence of certain independent variables at
a significance level of α=5%, and that the empirical F-ratio is (11.92) As for
this study, the value of the empirical F-ratio (11.92) is greater than the
theoretical value of F-ratio (2.34) for the 8-degree of freedom in the numerator
and 25 in the denominator, then we come to the conclusion to reject the null
hypothesis that the independent variables have a significant impact on the
dependent variable. Durbin-Watson statistics shows high correlation with
respect to the value above 2.
Alihodžić A., Plakalović N.: Determinants of Credit Growth to Nonfinancial companies..
Industrija, Vol.44, No.2, 2016 95
Table 3. Regression analysis between the following parameters: GRL, GRNPL,
GROE, RGDPG, CPI, DGR, DIR, EURIBOR, LIBOR in B&H for the period Q1 2007 –
Q2 2015
Regression Statistics
Multiple R
0.890
R Square
0.792
Adjusted R Square
0.726
Std. Error of the Estimate
1.365
Durbin - Watson
2.137
Source: the calculation made by the author (SPSS 16.0)
Table 4. Analysis of variance between the following parameters: GRL, GRNPL,
GROE, RGDPG, CPI, DGR, DIR, EURIBOR, LIBOR in B&H for the period Q1 2007 –
Q2 2015
ANOVA
Df
SS
MS
F
Significance F
Regression
8
177.855
22.232
11.923
0.000
Residual
25
46.616
1.865
-
-
Total
33
224.471
-
-
-
Based on the outputs as shown in the Table 4 (column where is Sig =0.000)
we can also conclude that the null hypothesis is null, the meaning that the
coefficient of determination for our regression model is different from zero.
Comparing the standard error of the estimate (Table 3 – 1.365) with a
standard deviation of the dependent variable (Table 2 - 2.61), it is evident
that the standard error of the estimate is significantly lower than the standard
deviation of the dependent variable, which helps in reducing errors in the
assessment, i.e. predicting the dependent variable.
Table 5. The matrix of correlation coefficients between the parameters: LGR,
GRNPL, GROE, RGDPG, CPI, DGR, DIR, EURIBOR, LIBOR in B&H for the period:
Q1 2007 – Q2 2015
LGR
GRNPL
GROC
RGDPG
CPI
DGR
DIR
EURIBOR
LIBOR
LGR
1.000
-0.620
-0.020
0.584
0.128
0.530
-0.047
0.377
0.833
GRNPL
-0.620
1.000
-0.084
0.619
-0.629
-0.214
-0.154
-0.234
-0.825
GROC
-0.022
-0.084
1.000
0.177
0.069
-0.238
0.777
0.083
0.136
RGDPG
0.584
0.619
0.177
1.000
0.338
-0.293
0.301
-0.105
-0.565
CPI
0.128
-0.629
0.069
-0.338
1.000
-0.261
0.155
-0.018
0.360
DGR
0.530
-0.214
-0.238
-0.293
0.261
1.000
-0.215
0.246
0.356
DIR
-0.047
-0.154
0.777
0.301
0.155
-0.215
1.000
0.084
0.171
EURIBOR
0.377
-0.234
0.083
-0.105
0.018
0.246
0.084
1.000
0.469
LIBOR
0.833
-0.825
0.136
-0.565
0.360
0.356
0.171
0.469
1.000
Source: Calculation by Author's (SPSS 16.0)
Alihodžić A., Plakalović N.: Determinants of Credit Growth to Nonfinancial companies..
96 Industrija, Vol.44, No.2, 2016
The coefficient of correlation can take values from -1 to +1. Thus, the resulting
ratio shows the strength of the two observed parameters. A value of zero
indicates that there is no correlation, while the value of 1.0 indicates the
correlation between complete and connected, and the value of -1.0 indicates
the correlation between complete and negative. The table above clearly
shows that a small number of variables are slightly negatively correlated, and
on the other hand, it shows that the small number of observed variables have
a positive correlation. Given the case analysis of the influence of independent
variables on the dependent variable, and the loans growth rate, it can be seen
that the strongest positive correlation was observed between the loans growth
rate and the interest rate LIBOR (0.833). As it is known that with an increase
in interest rates tends to lead to reduced lending activity, in the above-shown
in this table is present to reverse the trend in the movement, i.e. where did
present the strongest positive relationships between LIBOR and credit growth
rates (0.833). Given that as a reference interest rate in B&H takes EURIBOR
and LIBOR, which serve as a benchmark in determining the average interest
rate on the market, trends in itself shows the inverse proportionality. In the
period from the first quarter of 2007 to the second quarter of 2015, we have
continued declining trend in interest rates EURIBOR and LIBOR; on the other
hand, the average interest rate in B&H does not follow the same trend, but
tends to increase. The impact of interest rates on the European money market
has the effect transmission mechanism through which departs from the
Central Bank, which holds liquid assets to short-term basis in European banks
with the highest credit ratings. This implies a relatively lower interest rate that
accompanies a high credit rating of European banks working with the Central
Bank. Considering that the CBB&H holds reserves of domestic banks on
accounts from foreign banks that interest rates on these funds are dictated by
interest rates on the reserves and excess reserves as by the reserve
requirement by the Central Bank is calculated to commercial banks. The
second channel effects of interest rates from the European market is the term
of deposits of domestic banks in the accounts of foreign banks, which in
conditions of extremely low-interest rates is absolutely unprofitable for banks
(Plakalovic, N. p 9). Also, between the loans growth rate and real GDP growth
recorded a positive correlation (0.584). This is quite reasonable and logical,
because with an increase in economic activity, this leads to an increase of
banking assets, and consequently in increase in lending activity.
Observed, on the other hand, the strongest negative correlation was observed
between the loans growth rate and growth rate of non-performing loans (-
0.620). This is quite reasonable and logical, because the banks by increasing
non-performing loans in their portfolios slowing lending activity and creating a
provision in case of default on credit debt. The movement of non-performing
loans in the banking sector of Bosnia and Herzegovina for the period: Q1
2007 - Q2 2015 shows a tendency of the linear increase until 2013, and
Alihodžić A., Plakalović N.: Determinants of Credit Growth to Nonfinancial companies..
Industrija, Vol.44, No.2, 2016 97
relative in the study by Favara weak reduction to the second quarter of 2015.
The high level of non-performing loans at several banks has led to a high
share of non-performing loans at the level of the total banking sector.
According to the results of stress tests for 2013, carried out regularly by the
Central Bank of Bosnia and Herzegovina (CBB&H), the increase in the loan
portfolio is primarily influenced by slow economic activity. On the other hand,
the increase in non-performing loans is followed as a consequence of
increased interest rates (Central bank of Bosnia and Herzegovina, Financial
Stability Report, 2013, pp. 42-43).
Table 6. Regression analysis coefficients between the following parameters:
LGR, GRNPL, GROC, RGDPG, CPI, DGR, DIR, EURIBOR, LIBOR in B&H for the
period: Q1 2007 – Q2 2015
Model
Unstandardized
Coefficients
B
Std.
Error
Standardized
Coefficients
Beta
t
Sig
Zero
order
Correlatio
ns
Partial
Part
(Constant)
5.442
8.838
-
0.616
0.544
-
-
-
GRNPL
0.097
0.123
-0.177
0.788
0.438
-0.620
0.156
0.072
GROC
0.120
0.781
-0.023
0.154
0.879
-0.022
0.031
0.014
RGDPG
4.919
0.001
0.132
0.928
0.362
0.584
0.182
0.085
CPI
0.032
0.067
0.069
0.480
0.635
0.128
0.096
0.044
DGR
0.103
0.064
0.190
1.609
0.120
0.530
0.306
0.147
DIR
0.270
0.468
-0.096
-0.576
0.570
-0.047
-0.114
-0.052
EURIBOR
0.066
0.120
0.061
0.552
0.586
0.377
0.110
0.050
LIBOR
1.485
0.336
0.903
4.422
0.001
0.833
0.662
0.403
Source: The Calculation made by the Author (SPSS 16.0)
From the table above it is clear that the loans growth rate - the LGR has the
strongest positive linear relationship to the LIBOR (0.903), following by
deposit growth rate - DGR (0.190), then with the real GDP growth rate -
RGDPG (0.132), also with the consumer price - CPI (0.069) and EURIBOR
(0.061). To its opposite, the weakest linear relationship was observed
between the growth rate of non-performing loans – GRNPL (-0.177), the
deposit interest rate - DIR (-0.096) and the growth rate of operating costs -
GROC (-0.023). The most important risk in the banking sector stands out
credit risk. This is the risk of default. Despite the rapid expansion of innovation
in the financial services sector at the turn of this century, the credit risk is an
essential reason for the insolvency of banks, because in modern business
conditions over 80% of the bank's balance sheet relating to this segment of
banking risk management. In addition to these factors that affect the amount
of credit risk should be taken into consideration and decrease the
creditworthiness of the borrower, and increase the likelihood that the bank's
clients come in no position to fulfil their obligations (Đukic, Đ. 2011, p 22). The
high level of non-performing loans at several banks has led to a high share of
Alihodžić A., Plakalović N.: Determinants of Credit Growth to Nonfinancial companies..
98 Industrija, Vol.44, No.2, 2016
non-performing loans at the level of the entire banking sector. At the end of
2007 the share of non-performing loans to total loans amounted to only 3%,
whereas at the end of the second quarter of 2015 the share of non-performing
loans of total loans amounted to 14.1%. The largest share of non-performing
loans in the portfolio of total loans was recorded in 2013, and as of 15.1%.
According to the results of the stress tests for 2013 carried out regularly by
the Central Bank of B&H to increase the poor quality of the portfolio is
primarily influenced by slow economic activity. While, the increase in non-
performing loans is followed as a consequence of increased interest rates
(Financial Stability Report, 2013, CBB&H, p 42-43). In the period from the first
quarter of 2007 to the second quarter of 2015, there was an average increase
in operating costs by approximately 5.18% on a quarterly basis, which
indirectly reflected the burden of banks assets in B&H , and in this regard the
price increase lending and consequently reduced credit activity. From the
above given table, the negative causality between interest rates on deposits
and credit growth (-0.09), is also present, which is quite logical, because with
the increase in deposit interest rates banks have adjusted their lending rates
in order to maintain the net interest margin.
6. Conclusions
This paper analyses the determinants of the loans growth rate of the banking
sector in B&H in the period between Q1 2007 - Q2 2015, using multiple linear
regression models. In the quantitative analysis, it is assumed that the loans
growth rate of the banking sector in B&H (LGR) is used as dependent
variable, and the following ones as independent variables: the growth rate of
non-performing loans, the growth rate of operating costs, real GDP growth,
consumer price index, deposit growth rate, deposit interest rate, interest rate
(EURIBOR), and interest rate (LIBOR). The null hypothesis was rejected
because it was not shown that the independent variables affect the dependent
variable.
In the study, we found that there is a very high degree of correlation between
GDP growth, which we viewed as an independent variable and rate of credit
growth. Although the highest degree of correlation is present between credit
growth and rising LIBOR and EURIBOR there is no connection between these
rates and the movement of interest rates in B&H. The reason for this is the
high level of credit risk and monopolistic banks as almost the exclusive source
of external funds for financing company in B&H. The movement of GDP has
also a high correlation. Even greater correlation is observed between the GDP
and the non-performing loans which are quite expected. A significant
slowdown in economic growth and long-term recessionary trends in the
Alihodžić A., Plakalović N.: Determinants of Credit Growth to Nonfinancial companies..
Industrija, Vol.44, No.2, 2016 99
economy of Bosnia and Herzegovina have influenced that many companies
get into trouble and cannot properly service their debts and thus affect the
growth of NPLs. Bank operating expenses show a high degree of correlation
with the movements of interest rates on bank deposits. Future research on
this topic can be expanded depending on the availability of the database, so
that the use of more appropriate explanatory variables for a longer period can
get a better analysis.
References
Duenwald, C., Gueorguiev, N., & Schaechter, A. (2005). TooMuch of Good Thing?
Credit Booms in Transition Economies: The Cases of Bulgaria, Romania, and
Ukraine. IMF Working Paper, WP/128.
Đukic, Đ. (2011). Risk management and capital in banks, Publishing Centre of Faculty
of Economics in Belgrade.
Espinoza, R., & Prasad, A. (2010). Nonperforming Loans in the GCC Banking System
and their Macroeconomic Effects.IMF Working Paper, WP/224.
Favara, G. (2003). An Empirical Reassessment of the Relationship Between Finance
and Growth. IMF Working Paper,WP/123.
Garcia-Escribano, M., & Han, F. (2015). Credit Expansion in Emerging Markets:
Propeller of Growth?. IMF Working Paper,WP/212.
Guo, K., & Stepanyan, V. (2011). Determinants of Bank Credit in Emerging Market
Economies. IMF Working Paper, WP/51.
-International Monetary Fond. (2006). Spain: Financial Sector Assessment Program-
Technical Note-Stress testing Methodology and Results. IMF Country
Report, 6(216),
Levine, R., Loayza, N., & Beck, T. (2000). Financial Intermediation and Growth:
Causality and Causes. Journal of Monetary Economics, 46, 31-77.
Magud, N., Reinhart, C., & Vesperoni, E. (2012). Capital Inflows, Exchange Rate
Flexibility, and Credit Booms. IMF Working Paper, WP/41.
Sirtaine, S., & Skamnelos, I. (2007). Credit Growth in Emerging Europe, A Cause for
Stability Concerns?. The World Bank, Policy Research Working
Paper, WPS4281.
-The Central Bank of Bosnia and Herzegovina. (2013). Financial Stability Report.
Retrieved from http://www.cbbih.ba
-The Central Bank of Bosnia and Herzegovina. (2014). Financial Stability Report.
Retrieved from http://www.cbbih.ba
