Forum microcredit-interest-rates-and-their-determinants-june-2013 1
THE BEHAVIOR OF BANK NET INTEREST MARGIN1
1. THE BEHAVIOR OF BANK NET INTEREST MARGIN IN JORDAN:
THE IMPACT OF INTEREST RATE LIBERALIZATION AND TAX
REDUCTION
By
Jamileh “Mohammad Walid” Izzat “Ali Moustafa”
Supervisor
Dr. Ghassan Omet, Prof.
This thesis was submitted in partial fulfillment of the requirements for
the Master's Degree in Finance
Faculty of Graduate Studies
The University of Jordan
April,2015
2. COMMITTEE DECISION
This thesis “The Behavior of Bank Net Interest Margin in Jordan: The impact of interest
Rate Liberalization and Tax Reduction” was approved on 29/4 / 2015.
Examination CommitteeSignature
Dr. Ghassan Omet (Supervisor) ……………….
Prof. of Finance
Dr. Diana Abu-Ghunmi (Member) ……………….
Assistant Professor of Finance
Dr. Adel Bino (Member) ……………….
Assistant Professor of Finance
Dr. Adel Sharkas (Member) ……………….
Associate Prof. of Finance
Deputy Governor / The Central Bank of Jordan
4. iv
ACKNOWLEDGMENTS
I wish to express sincere gratitude to my supervisor Prof.Ghassan Omet for guidance,
valuable advice, support, and assistance in finding data. I am also grateful to all research
workshop professors for their useful comments. Finally, special thanks to my parents and
my friends for their moral support.
5. v
TABLE OF CONTENTS
Subject Page
Committee Decision ……………………………………………..…………………. ii
Dedication ……………………………………………............................. …. …….. iii
Acknowledgment…………………………………………….. …… ……………... . iv
List of Contents……………………………………………….......... …………….... v
List of Tables……………………………………………………………………....... vi
Abstract ………………………………………………………................................... vii
Chapter One: INTRODUCTION………..…………………....................................... 1
1.1 Introduction……………………………………………………............................ 2
1.2 Research Problem ……………………………………………… ……………….. 4
1.3 Research Importance………………………………………………………………. 5
1.4 Research Objective ……………………………………………………………….. 5
Chapter Two: LITERATURE REVIEW..…. ………………….................................... 6
2.1 Overview of Jordanian Banking Sector………………………... …......................... 7
2.2 Bank Net Interest Margin …………………………………. .................................. 10
Chapter Three: DATA, METHODOLOGY AND
EMPIRICAL RESULTS…………………………………………... ………………... 13
3.1 Introduction……………………………………………………. ………………... 14
3.2 Research Theoretical Framework…………………………………………........... 15
3.3 Descriptive Statistics……………………………………………………….....….. 15
3.4 The Econometric Approach…………………………………… ………………… 19
3.5 Research Hypotheses………………………………………………………........... 20
3.6 Empirical results and Discussion…………………………………………… ….... 21
Chapter Four: CONCLUTIONS AND RECOMMENDATIONS…………………….. 28
References…………………………………………………………............................... 31
Appendices……………………………………………………….................................. 33
Abstract (in the second language)…………………………………............................... 34
6. vi
LIST OF TABLES
Table Page
1. Banks In Jordan 8
2.Cumulative Data of Jordanian Banks 9
3.Descriptive Statistics 16
4. Descriptive Statistics 17
5. Descriptive Statistics 18
6.Regression Results 22
7. Regression Results 23
8. Regression Results 24
9. Regression Results 25
10. Sample Banks 33
7. vii
THE BEHAVIOR OFBANK NET INTEREST MARGIN IN
JORDAN: THEIMPACTOF INTEREST RATE LIBERALIZATION
AND TAX REDUCTION
By
Jamileh “Mohammad Walid” Izzat “Ali Moustafa”
Supervisor
Dr. Ghassan Omet, Prof.
ABSTRACT
The effectiveness of the banking system in channeling funds from surplus to deficit units
is often gauged by examining the net interest margin. In this regard, it is interesting to
note that since the early 1980s, the Jordanian banking sector has witnessed two major
changes in laws and regulations. These are the 1989 interest rate liberalizationand the
1996 tax rate reduction in the corporate tax from 55% to 35%. This study investigates the
potential impact of these important changes in the behaviour of bank net interest margin,
within the context of the Jordanian banking industry over the period 1982-2013. It
assesses to what the extent the relatively high and escalating bank interest margins, in this
sector can be attributed to low efficiency or non competitive market conditions,
controlling for the bank specific and macroeconomic environment factors. Based on a
sample consist of 12 banks operating in Jordan over the study period, the results indicate
that bank interest margins have remained relatively high and rapidly increasing over time.
9. 2
1.1 Introduction
Following the classical arguments by Schumpeter (1934) and Robinson (1952) about the role of
financial systems in economic growth, a large number of papers have examined this issue.
Indeed, this literature has coined the term “financial development”.
To compare countries in terms of financial development, one must be able to rank them in terms
of the impact of each country’s financial system on, for example, the efficiency of the allocation
of resources, and on monitoring managers. Naturally, such an exercise is ideal and difficult to do.
As a major part of any financial system, and the fact that financial intermediaries (banks) are
economically important, one should not be surprised that the financial economics literature
contains many papers which examine the performance of banks in terms of various issues,
including the determinants of net interest margin, determinants of accounting performance,
impact of foreign banks on the performance of local banks, determinants of bank credit,
determinants of bank capital, and others. Moreover, bank interest margins can have major
economic implications. For example, it can be argued that wide interest margins push up the cost
of capital, thereby reducing feasible capital investment opportunities. Similarly, wide margins can
signify the existence of problems (inefficiency and moral hazard) in the banking industry. Given
these arguments, many studies examined the performance of the banking industry in terms of net
interest margins and their determinants.
In reality banks’ net interest rate margins (NIM) represent a vital component of profitability and
typified a summary measure of bank net interest return of which interest margin reflects both the
10. 3
volume and mix of a banks’ assets and liabilities, and covers the cost of intermediation function.
Thus, a wide deposit-lending interest rate spread could be indicative of banking sector
inefficiency or a reflection of the level of financial development (Folawewol and Tennant 2008).
Embedded in the spread is the information on the efficiency of financial intermediation,
profitability, monetary policy impact, among others.
Relative to the above, it is interesting to note that since the 1980s the Jordanian banking sector
has witnessed two major changes in laws and regulations. These are the 1989 interest rate
liberalization and the 1996 tax reduction in the corporate tax from 55 percent to 35 percent.
A large body of literature exists on the potential impact that interest rate liberalization has had on
uncovered interest rate parity. However, it can also have important effects on domestic bank
spreads by providing economies of scale and scope and increasing competitive pressures. One of
the expected benefits of financial liberalization and deepening of the financial sector is the
narrowing of the interest rate spreads– the difference between the interest rate charged to
borrowers and the rate paid to depositors. This is predicated given the understanding that
liberalization enhances competition and efficiency in the financial sector.
Despite the liberalization of the financial sector, high interest rate margins are still an issue of
concern in a number of countries, including Jordan. The empirical results show that bank-specific
factors play a significant role in the determination of interest rate margins. These include bank
size based on bank assets, credit risk as measured by non-performing loans to total loans ratio,
liquidity risk, return on average assets and operating costs. The impact of macroeconomic factors
11. 4
such as real economic growth and inflation is not significant. Similarly, the impact of policy rate
as an indicator of monetary policy is found to be positive but weak. On average, big banks have
higher margins compared to small banks. There is need for explore policy options meant to
enhance competition in the industry and measures to break market dominance will be one such
option. Further, the banking sector needs to explore internal as well as industry-driven strategies
that counter some of the bank-specific factors associated with higher spreads. These could range
from diversification of products to investment in cost-saving and efficient forms of technology.
This thesis attempts to measure the impact (if any) of the above-mentioned changes (interest rate
liberalization and tax reduction) on the Jordanian banking sector in terms of net interest margin.
The result indicates that the 1989 interest rate liberalization had no impact on bank net interest
margin, while the 1996 corporate tax rate reduction, reduced bank net interest margin, but net
interest margins remained relatively high and increasing over time.
1.2 Research Problem
This thesis examines the issue of net interest margin in the Jordanian banking sector spans over
the period 1982-2013.The main research questions are as follows:
Did the 1989 interest rate liberalization have any significant impact on net interest margins?
Did the 1996 income tax reduction have any significant impact on net interest margins?
12. 5
1.3 ResearchImportance
The fact that net interest margin is one known measure of bank efficiency, it is important to
measure it in the Jordanian banking sector and. In addition, it is also important to learn from the
experience of the 1989 interest rate liberalization and the 1996 tax reduction in terms of their
impact on this measure. Indeed such experience should be useful not only in understanding what
really determines bank’s net interest margin , but also in guiding the government in any future
changes in corporate tax policy.
1.4 Research Objectives
This thesis has three main objectives. These are briefly outlined below:
A- To measure net interest margin that exist in the Jordanian banking sector.
B- To investigate whether or not the 1989 interest rate liberalization had any significant impact
on net interest margins.
C- To investigate whether or not the 1996 income tax reduction had any significant impact on net
interest margins?
14. 7
2.1Overview of Jordanian Banking Sector
The banking sector in Jordan –as in many countries –is considered one of the main pillars of the
Jordanian economy. In spite the difficult events that have taking place since the beginning of the
year 2011 following the Arab spring, the Jordanian banking sector of 26 banks, 15 listed on
Amman Stock Exchange (ASE) witnessed a healthy activity growth during the year 2013, with
total assets growing of 9% yearly in 2013 to reach JD 54,912,998,990 at the end of December
2013, and proving more than twice higher than that recorded during the last year.
The primary source of income of Jordanian banks arises from interest income and commissions
paid out on deposits and loans. Since the beginning of the 2013, all banks reported growth in their
interest income. The banks featured of high liquidity, invested sufficient portion in claims on the
public sector, specifically in government securities, and adequately capitalized to face potential
pressure on funds.
Total deposits the main activity driver of banks in Jordan , accounting to two thirds of total
balance sheets at end-December 2013.total deposits progressed by 11%on a yearly basis to reach
JD 35,544,453,854 at year –end 2013,and this is four times higher than that registered during
2012.
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Table 1. BanksIn Jordan
Bank Name Ticker Origin Type
Arab Bank ARAB National Commercial
Arab Banking Corporation ABCO National Commercial
Arab Jordan Investment Bank AJIB National Commercial
Bank Al-Etihad UBSI National Commercial
Bank Of Jordan BOJX National Commercial
Cairo Amman Bank CABK National Commercial
Capital Bank Of Jordan EXFB National Commercial
Invest Bank INVB National Commercial
Jordan Ahli Bank AHLI National Commercial
Jordan Commercial Bank JCBK National Commercial
Jordan Kuwait Bank JOKB National Commercial
Societe General De Banque Jordanie SGBJ National Commercial
The Housing Bank For Trade And Finance THBK National Commercial
Jordan Islamic Bank JOIB National Islamic
Jordan Dubai Islamic Bank JDIB Foreign Islamic
Islamic International Arab Bank Not listed Foreign Islamic
Banque Audi Not listed Foreign Commercial
Blom Bank Not listed Foreign Commercial
City Bank Not listed Foreign Commercial
Egyptian Arab Land Bank Not listed Foreign Commercial
HSBC Not listed Foreign Commercial
National Bank Of Abu-Dhabi Not listed Foreign Commercial
National Bank Of Kuwait Not listed Foreign Commercial
Rafidian Bank Not listed Foreign Commercial
Standard Chartered Not listed Foreign Commercial
Al-Rajhi Bank Not listed Foreign Islamic
The largest consistent of the consolidated assets of Jordanian banks is credit facilities granted. At
the end of 2013, the total credit facilities granted amounted to JD 24,341,154,121.Up from JD
23,367,007,166 the prior year. While banks boasted higher deposits during 2013,lending
activities grew more or less satisfactory but fell short of that during last year. The credit facilities
from a currency aspect show that local currency lending contributed to two thirds of the total
lending of the Jordanian banking sector, while those in foreign currencies were responsible for
the remaining third.
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It’s worth pointing out that there is an increase in the lending activity of Jordanian Banks in 2013
by 7%, its almost to the benefit of the resident private sector, but fell short of that during the
previous year. the rise in total credit facilities was mostly owed to higher lending to the
construction sector, followed by lending to general trade, industry and mining sectors, among
others.
Table 2. Cumulative Data of Jordanian Banks in JD
2010 2011 2012 2013
Net interest income 1,233,204,022 1,291,294,892 1,435,729,365 1,557,317,208
Net commission income 294,550,850 314,925,918 335,242,194 336,611,855
Total assts 48,477,966,019 50,516,950,642 52,024,825,201 54,912,998,990
Customers Deposits 30,882,139,663 32,564,590,886 33,375,933,379 35,544,453,854
Banks & Financial Institutions
Deposits 4,789,628,894 4,769,802,734 4,567,019,027 4,025,788,906
Direct credit facilities 21408,367,027 22,020,352,390 23,367,007,166 24,341,154,121
Paid In Capital 2,099,314,955 2,231,229,558 2,359,442,179 2,406,100,000
17. 10
2.2Bank Net Interest Margin
Many developing countries have adopted financial liberalization measures in order to make their
banking systems more efficient. However, despite this measure, bank net interest margins have
remained wide. Several arguments have been advanced to this behavior. These include
monopolistic behavior (Barajas et al., 2000), absence of bank deposit insurance, high reserve
requirements (Saunders and Schumacher, 2000), high non-financial (operating) costs and
macroeconomic instability in terms of inflation (Brock and Rojas-Suarez, 2000).
As mentioned above, many papers examine the determinants of bank net interest margin. These
papers include Brock and Rojas-Suarez (2000), Moore and Craigwell (2002), Drakos (2003),
Chirwa and Mlachila(2004), Doliente (2005), Valverde and Fernandez (2007), Hawtrey and
Liang (2008), Claeys and Vennet (2008), Beck and Hesse (2009), Marinkovic and Radovic
(2010), Maudos and Solis (2009), Oreiro and de Paula (2010), Perera et al. (2010), Souza-
Sobrinho (2013).
The above-mentioned research papers estimate a version of the following model:
Yi,t = αi + Xitβ +εi,t i = 1,..., n, t = 1, ..., T (1)
Where
Yi, t is net interest margin (interest income minus interest expense divided by total assets) of bank
i at time t, while Xit represents the vector of k explanatory variables, and is the disturbance term.
Some of the explanatory variables include bank size, ratio of personnel expenses to total assets,
18. 11
ratio of interest expenses to total deposits, ratio of other operating expenses to total assets, ratio of
equity capital to total assets, net loans to total assets, real GDP growth rate, and others.
Barjas et al. (1999) examine the source of high intermediation spreads observed in the Colombian
banking sector over the pre-liberalization period (1974-1988)and the post liberalization period
(1991-1996)found mix results, liberalization increased banking sector competitiveness, lower
market power, and reduced financial taxation from its 1970s level.
Relative to the literature which examines the determinants of net interest margin, it is useful to
note that the classical paper by Demirguc-Kunt and Huizinga (1999) investigated the
determinants of bank interest margins (spread) using bank-level data for 80 countries. The set of
regresses (independent variables) that they used include variables that account for bank
characteristics, macroeconomic conditions, bank taxation and underlying legal and institutional
indicators.
Based on their empirical results, they report that the ratios of equity to total assets and loans to
total assets impact bank interest margins positively. Similarly, it is found that overhead costs and
inflation lead to an increase in interest margins.
As far as Arab banks are concerned, Ben Naceur and Goais (2001) and Ben Naceur (2003), Ben-
Khedhiri et al. (2005) and Mensi (2010), Ben-Khediri and Ben-Khediri (2011) examined the
Tunisian banking sector in terms of its net interest margin and the results indicate that “bank-
specific variables and regulatory changes are the most relevant factors in explaining Tunisian
19. 12
banks interest differential. Finally, macroeconomic variables do not seem to influence bank
margins” (Ben-Khedhiri et al., 2005). Similarly, Lebanese banks have been examined by Hamadi
and Awdeh (2012).
21. 14
3.1 Introduction
This study examines the impact of interest rate liberalization and tax reduction on the behavior of
bank’s net interest margins within the context of the Jordanian banking industry.
To carry out the analysis, the researchers managed to collect the annual data for a total of 12
banks during the period 1982-2013. This sample is based on the availability of the adequate
information. However, due to missing observations for some banks,a restricted sample covering
12 banks over the same period is employed.
The data base is compiled from the financial statements of banks. The names of the banks
included in the data base are given in the appendix. The Macroeconomic indicators are taken
from Central bank of Jordan. The main banks indicators provided in the data base are:
The natural logarithm of total assets (SIZE),Total operating expenses to total assets (OVERH),
Equity capital to total assets (CAP),Total credit (loans) to total assets (LOANS), andNet
commission income to total assets (COMM).
As well as macroeconomic indicators which included are: Real GDP growth rate
(GROWTH),Inflation rate (INF).Both descriptive statistics and regression analysis are
undertaken.
22. 15
3.2 Research Theoretical Framework
The dependent and independent variables used in this thesis are defined as follows:
The Dependent Variable:
Net Interest Margin: [Interest Income – Interest Expense] / Total Assets
The Independent Variables:
The natural logarithm of total assets (SIZE)
Total operating expenses to total assets (OVERH)
Equity capital to total assets (CAP)
Total credit (loans) to total assets (LOANS)
Dummy variables for the 1989 interest rate liberalization and the 1996 tax reduction
Net commission income to total assets(COMM)
Real GDP growth rate (GROWTH)
Inflation rate (INF).
3.3Descriptive Statistics
The descriptive statistics for the data base are provided in table3 and 4. Based on the reported
figures, one can see that the average net interest rate margin over the sample period was equal to
2.32% about 0.07% points lower than the median margin.
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There is a fair bit of variation in the margin across banks, with the highest margin for the banking
system 5.91%,reported for the Arab bank in 1995. In contrast,the lowest net interest margin was
equal to 0.02% reported again by the Arab bank in 1999.
To provide further analysis table 3 calculates the sample means, the results.
Table 3. Descriptive Statistics
Mean Median Maximum Minimum SD Observations
NIM .023207 .023927 .059058 .000229 .010631 384
SIZE 19.83517 19.71553 23.9235 15.88212 1.631237 384
OVERH .042573 .034843 .136045 0 .026781 384
CAP .076494 .055055 .394241 .00349 .067840 384
LOANS .441848 .433076 .739034 .188723 .110118 384
COMM .008506 .007729 .065707 .000994 .006083 384
INF .049079 .0352 .2571 -.0068 .050636 384
GROWTH .044023 .042 .187 -.135 .046251 384
DUMLIB .710938 1 1 0 .453918 384
DUM TAX .5 .5 1 0 .500652 384
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Table 4. Descriptive Statistics
year Mean
NIM
Mean
SIZE
Mean
OVERH
Mean
CAP
Mean
LOANS
Mean
COMM
Mean
INF
Mean
GROWTH
1982 .027 18.029 .07151 .0961 .5227 .8337 .0723 .0695
1983 .025 18.162 .07304 .0875 .5055 .6183 .0502 .02
1984 .025 18.298 .07072 .0786 .5157 .5533 .0385 .086
1985 .019 18.401 .06802 .0737 .5022 .4623 .0298 .035
1986 .019 18.525 .06806 .0655 .4983 .4989 0 .07
1987 .019 18.618 .06691 .0652 .4984 .4904 -.002 .029
1988 .019 18.747 .06674 .0600 .5032 .7406 .0661 -.019
1989 .019 18.860 .06093 .0582 .4251 .4528 .2389 -.1166
1990 .024 18.871 .06427 .0561 .4548 .0851 .1509 .01208
1991 .027 19.137 .05229 .0415 .3894 .1300 .0748 .02233
1992 .024 19.320 .04748 .0409 .3949 .2162 .0364 .1738
1993 .028 19.401 .04789 .0431 .4351 .4813 .0359 .0406
1994 .029 19.528 .04389 .0511 .4568 .4077 .0352 .05
1995 .029 19.561 .04368 .0576 .4901 .4077 .0235 .062
1996 .029 19.648 .04221 .0561 .5059 .4215 .065 .021
1997 .020 19.772 .04089 .0659 .4863 .3991 .0304 .033
1998 .023 19.827 .04064 .0699 .5212 .3680 .0309 .03
1999 .024 19.934 .03749 .0643 .4855 .3012 .0061 .034
2000 .022 20.179 .03134 .0834 .3675 .2623 .0067 .042
2001 .024 20.253 .03238 .0832 .3852 .2047 .0177 .053
2002 .023 20.260 .03442 .0894 .3639 .2098 .0183 .058
2003 .025 20.247 .03454 .0889 .3719 .2089 .0163 .042
2004 .023 20.454 .02696 .1125 .3807 .1754 .0336 .086
2005 .026 20.705 .02380 .1020 .4183 .1288 .0349 .081
2006 .029 20.858 .02041 .0848 .4580 .1585 .0625 .081
2007 .028 21.002 .02311 .0884 .4582 .1761 .0539 .082
2008 .032 21.081 .02340 .0904 .4893 .1912 .1493 .072
2009 .029 21.166 .02447 .0896 .4523 .1855 -.007 .055
2010 .032 21.240 .02482 .0873 .4505 .1598 .0501 .023
2011 .030 21.281 .02814 .1129 .4630 .1426 .0441 .026
2012 .031 21.352 .02722 .1076 .4739 .1403 .048 .027
2013 .028 21.455 .02158 .1025 .4523 .1271 .059 .028
To provide further analysis of the trends in the two indicators, Table5 calculates the sample
means of net interest margins for the 12 banks grouping as well as for year intervals:1982 to 1989
, 1982to 1996,1990to1995,and 1997 to 2013. The means are also reported for each group,as well
as the entire sample period for a comparison purposes.
25. 18
The results provided in Table 5 indicate that when interest rate liberalization applied was adopted
in 1990, the average NIM was equal to 2.4% with 0.5% higher than average of 1989, and lower
than the average NIM for the period over 1982-1989 by .2%.
In addition, in 1997 the average NIM was equal to 2% which is a decrease by 0.9% in response to
tax reduction than the average NIM during the 1996,and lower by 0.96% lower than the period
1982-1996.
To find the impact of tax reduction after liberalization the average NIM of 2.71% for the period
1990-1996 indicate that average NIM decreased by .02%.
Table 5. Descriptive Statistics
Year interval 1982-2013 1982-1989 1982-1996 1990-1996 1996-2013
NIM MEAN .023207 .026184 0.0295 0.0271 .0247
DUM LIB
MEAN
.711 0 .462 1 1
DUM
TAXMEAN
.5 0 0 0 1
While these changes interest rate policies and tax rate have been significant,to a large degree, this
has not been reflected in a significant reduction in net interest margins. Indeed Table 5 suggests
that interest rate margins have risen in Jordanian banks in the period after 1996.
26. 19
3.4 The Econometric Approach
The previous results present only a cursory analysis of the relationship between net interest rate
margins,interest rate liberalization and tax reduction. There are a number of other factors that
may impact on interest rate margins. To effectively take account these factors, the panel data
model is estimated that utilizes both the time-series and cross- sectional dimensions of the data
base by using thefixed effect model. Practically, this is the preferred estimationsince the
Hausman specification test rejects the random effects model.
The regression model therefore is estimated as follow:
NIMi,t = α0 + β1SIZEi,t + β2OVERHi,t + β3CAPi,t + β4LOANSi,t + β5COMMi,t+ β6GROWTHt+
β7INF,t+ β8DUMi,t+ εi,t
Where i denotes the bank and t denotes the time period.
NIMi, t: the net interest rate margin
SIZE: is the natural logarithm of total assets.
OVERH: is a total operating expense to total assets.
CAP: is equity capital to total assets.
LOANS: is total credit (loans) to total assets.
COMM is net commission income to total assets.
GROWTH is real GDP growth rate.
INF is the inflation rate.
DUM is a liberalization dummy variable which is equal to 1 for the period 1982-1990 and 0
otherwise. Also, a dummy variable tax is (1) for the period 1982-1996 and0 otherwise.
27. 20
It is necessary to note here that the regression model used treating the data as pooled observations
and therefore,assumes that the residual are not correlated either across different time periods or
cross different banks during the same or different time periods.(i.e. Observations are
homoskedastic and not serially correlated).
3.5Research Hypotheses
Main Hypotheses:
H0: The 1989 interest rate liberalization has had no impact on bank net interest margin.
H0: The 1996 tax reduction has had no impact on bank net interest margin.
Secondary-Hypotheses:
H0(1): Larger banks do not have narrower net interest margin.
H0(2): Banks with greater operating expenses do not have narrower net interest margin.
H0(3): Banks with stronger equity base do not have narrower margin.
H0(4): Banks with high liquidity do not have wider margin.
H0(5): More diversified banks tend to have worse performance.
H0(6): Economic growth does not positively impact net interest margin.
H0(7): Inflation rate does not positively impact net interest margin.
28. 21
3.6 Empirical results and Discussion
This section of the study provides the estimation results for equation to identify whether the
results obtained are sensitive to the estimation approach employed.
Basic regression results:
To estimate the relationship between the variables and NIM, and for further analysis for the
impact of interest rate liberalization and tax reduction on bank’s net interest margins adopted two
regression models, Table 6 ,7,8 and 9 reports the results of two sets of regression models of the
determinants of the net interest margin .
The first model includes bank-specific variables.
The second model drops all bank-specific and macroeconomic variables. Consider significant
variables at level 5% or less, and other wise insignificant. Overall, the estimation results come as
follow:
1-The impact of interest rate liberalization:
To estimate the impact of 1989 interest rate liberalization on bank’s net interest margin, Table 6
reportsthe results of regressing the net interest margin on its’ various determinants for the banks
under study ,and regression results of NIM with all bank-specific and macroeconomic variables,
including the dummy variable of net interest liberalization during the period 1982-2013.
29. 22
Table 6. Regression Results (1982-2013)
The estimation results indicate that the coefficient of interest rate liberalization is negative but not
statistically significant, in both regression models. While three bank specific variables: total assets,
equity capital, and commission income was highly significant with appositive relationship with bank
net interest margin.
To ensure our results , we lagged dependent variable ,the bank net interest margin ,as well as
five banking industry specific variables : Bank assets, overhead expenses , capital equity , total
credits and commission income in addition to macro economic variables . the regression results
show same result except that Real growth of GDP have a significant impact on NIM with a
Variable Coefficient t-Statistic Probability Variable Coefficient t-Statistic Probability
α -.076112 -4.602242 0 α -0.076965 -5.105007 0
SIZE .004131 4.851882 0 SIZE .004197 5.232554 0
OVERH .046324 .758086 .4489 OVERH .046136 .763981 .4454
CAP .071612 5.647282 0 CAP .071485 5.61438 0
LOANS .01487 1.33055 .1842 LOANS .014705 1.316902 .1887
COMM .400084 4.06391 .0001 COMM .401104 4.080526 .0001
DUM
LIB
-.000061 -.038805 .9691 DUM LIB -.000724 .050288 .9599
Effect specification
R-squared : .567249
Adjusted R-squared: .5477149
F-statistic : 28.22075
Durbin-Watson stat : 1.005506
INF -.004175 -.488591 .6254
GROWTH .000724 .050288 .9599
Effect specification
R-squared : .56766
Adjusted R-squared: .545093
F-statistic : 25.15419
Durbin-Watson stat : 1.31501
30. 23
coefficient of 1.7% and positive relationship, and that support the primary hypothesis that the
1989 interest rate liberalization has had no impact on bank net interest margin.
The estimation results summarize in table seven as follow:
Table 7. Regression Results (1983-2013)
2- The impact of tax reduction:
To estimate the impact of 1996 Tax rate reduction in the corporate tax from 55% to 35% on
bank’s net interest margin, table 8 reports the results of regressing the net interest margin on its
various determinants, for the banks under study ,and regression results of NIM with all bank-
specific and macroeconomic variables, including the dummy variable of Tax during the period
1982-2013.
Variable Coefficient t-Statistic Probability Variable Coefficient t-Statistic Probability
α -.069641 -4.490798 0 α -.074705 -4.384682 0
SIZE(-1) .003933 5.234112 0 SIZE(-1) .004251 4.91989 0
OVERH(-1) .026973 .523273 .6011 OVERH(-1) .027908 .543053 .5874
CAP(-1) .081059 5.994566 0 CAP(-1) .080446 5.952444 0
LOANS(-1) .003933 5.234112 0 LOANS(-1) .007872 .922141 .3571
COMM(-1) .358744 3.206811 .0015 COMM(-1) .357881 3.451215 .0006
DUM LIB(-
1)
.00063 .350996 .7258 DUM LIB(-
1)
-.000802 -.461885 .6444
Effect specification
R-squared : .598628
Adjusted R-squared: .579353
F-statistic : 31.05736
Durbin-Watson stat : 1.041452
INF(-1) -.006893 -.760722 .4473
GROWTH
(-1)
.017007 2.647004 .0085
Effect specification
R-squared : .606569
Adjusted R-squared: .585333
F-statistic : 28.5628
Durbin-Watson stat : 1.036926
31. 24
Table 8. Regression Results (1982-2013)
The estimation results indicate that the coefficient of Tax reduction is positive and statistically
significant , in both regression models. In addition to the three bank specific variables: total
assets, equity capital, and commission income, also highly significant with appositive
relationship with bank net interest margin.
To ensure our results , we lagged dependent variable ,the bank net interest margin ,as well as
five banking industry specific variables: Bank assets, overhead expenses, capital equity , total
credits and commission income in addition to macro economic variables . the regression results
show same result except that In addition to tax and three bank variables, Real growth of GDP
have a significant impact on NIM with a coefficient of 1.8% and positive relationship. The
estimation results summarize in table seven as follows:
Variable Coefficient t-Statistic Probability Variable Coefficient t-Statistic Probability
α -.050255 -2.7008882 .0072 α -.050247 -2.714664 .007
SIZE .002729 3.083287 .0022 SIZE .002723 3.004232 .0028
OVERH .051476 .83777 .4027 OVERH .051831 .865209 .3875
CAP .065241 4.939674 0 CAP .065201 4.939386 0
LOANS .015818 1.526365 .1278 LOANS .015787 1.525235 .1281
COMM .379932 3.985752 .0001 COMM .379419 3.92113 .0001
DUM
TAX
.003862 2.480738 .0136 DUM TAX .003877 2.569036 .0106
Effect specification
R-squared : .576739
Adjusted R-squared: .55708
F-statistic : 29.33619
Durbin-Watson stat : .997321
INF .000836 .094699 .9246
GROWTH .00147 .118813 .9055
Effect specification
R-squared : .576768
Adjusted R-squared: .554677
F-statistic : 26.10785
Durbin-Watson stat : .99948
32. 25
Table 9. Regression Results (1983-2013)
3.The bank-specific characteristics:
- (OVERH):
For the total operating expense to total asset (OVERH) ratio, considering the eight sets of
regression model, the overall result implies that the relationship between overhead –to-asset ratio
and bank’s net interest margin within the Jordanian context is positive, but statically not
significant.In principal the higher the overhead cost in the banking sector the larger the required
spreads to compensate the additional costs. The Jordanian commercial banks would have the
chance to pass overhead cost to their clients by charging higher interest rate on loans or pay lower
interest rates on deposits.
Variable Coefficient t-Statistic Probability Variable Coefficient t-Statistic Probability
α -.057845 -3.51861 .0005 α -.059651 -3.412197 .0007
SIZE(-1) .003328 4.525129 0 SIZE(-1) .003392 4.163886 0
OVERH(-1) .027209 .53236 .5948 OVERH(-1) .032745 .62315 .5336
CAP(-1) .077596 5.913273 0 CAP(-1) .077313 5.879535 0
LOANS(-1) .00916 1.112815 .2665 LOANS(-1) .00902 1.09824 .2729
COMM(-1) .347651 3.085808 .0022 COMM(-1) .347795 3.34652 .0009
DUMTAX(
-1)
.002094 2.024391 .0437 DUMTAX(
-1)
.001798 1.784079 .0353
Effect specification
R-squared : .601255
Adjusted R-squared: .582107
F-statistic : 31.39919
Durbin-Watson stat : 1.040843
INF(-1) .004053 -.417138 .6768
GROWTH
(-1)
.016526 2.927741 .0036
Effect specification
R-squared : .608259
Adjusted R-squared: .587114
F-statistic : 28.76598
Durbin-Watson stat : 1.04459
33. 26
- (CAP):
The equity capital to total assets ratio (CAP), which proxies the risk aversion degree of the bank ,
considering the eight sets of regression model , shows as highly significant and a positive
impact in its relationship with the bank net interest margin .such conclusion is in line with
previous evidences i.e., Berger (1995) and Dermerguc-kunt and Huizingua (1999). In general ,the
finding indicate that well-capitalized banks in the Jordanian banking sector support lower
expected bankruptcy cost for themselves and their client, which reduce their cost of capital ,and
lower profit variability.
- (LOANS):
Total credit (loans)to total assets ratio(LOANS) considering the eight sets of regression model,
hasn’t the expected impact on the bank’s net interest margin, since the coefficient of this ratio is
positive but not significant across all specifications ,reflecting less care monitoring acts made by
banks to ward their lending process. under these conclusion there is no chance that banks seek
growth by relaxing credit selection and monitoring. However, that banks seems to be able to
maintain higher levels of nonperforming loans , thereby less profits and margins. This finding
implies also that gaining more loans (increasing market share)would likely to increase the interest
margin.
34. 27
- (SIZE):
The result shows that the relationship considering the eight sets of regression model, between the
size and bank’s net interest margin is positive and highly significant. this finding suggest that
larger banks tend to gain higher margins ,that is, the Jordanian banks operating at significant scale
of economies,(Balloul,2004).overall ,the size proxy result confirms that little cost saving can be
achieved by increasing the size of the banking firm(Berger et al.,1987).yet significant scale of
economies can be reported for the banks whose asset size extend well into wide range
,(shuffer,1985).
- (COMM):
The result show that net commission income to total asset ratio considering the eight sets of
regression model, have a positive relationship with bank’s net interest margin ,with a significant
impact.
4. Macroeconomic Variables:
The regression results show that macroeconomic developments have insignificant effect on the
Jordanian bank’s net interest margins.
- (GROWTH):
The real growth rate in GDP has appositive impact on bank’s net interest margins , but not
significant ,indicating that movements to deregulation together with technology advances would
lead to improvements in the overall banking businesses ,causing higher spread ,and hence higher
net interest margins.
35. 28
- (INFALTION):
The inflation rate have a positive impact, but not significant. In inflationary environment ,banks
costs generally rise leading to higher borrowing costs for the private sector , suggesting that
banks tend to profit from inflationary environment, by charging higher loan interest rates,and
therefore ,higher net interest margins.
37. 29
This study has investigated the impact of interest rate liberalization and tax reduction on the
behavior of bank net interest margin in Jordan over the period 1982-2013.
The major finding of our investigation is that the 1989 interest rate liberalization had no impact
on bank interest rate margin, while the 1996 reduction in tax rate paid by the banking sector from
55% to 35% have a significant impact on it, and reduced bank’s net interest margin but not
consider a significant reduction in it, and its remained high and increasing overtime.
Other findings suggest that: bank specific variables explain a substantial part of the within-
country variation in bank net interest margins. High net interest margin tend to be associated with
banks that hold a relatively high amount of capital, we also found a significant role for both the
capital to asset ratio and commission income to asset ratio in the observed levels of interest
margins.
These finding underline the importance of capital adequacy rules as means to prevent banks from
taking excessive risks, and as a tool for maintaining depositor’s confidence. Furthermore, these
findings indicate that more lending results in wider margins, and reflects the bank enhanced
ability to integrate risk considerations in their loan pricing behavior.
In addition to bank-specific characteristics, macroeconomic indicators, such as inflation and real
growth rate in GDP, have no impact on bank’s net interest margins. This finding may suggest that
Jordanian banks work out of macroeconomic conditions.
38. 30
Our results suggest a number of policy recommendations for the banks and policy makers in
Jordan’s banking sector. The most pressing avenue for reform appears to implement further
liberalization to the sector, simultaneously; the authorities should ensure that strong and binding
capital adequacy rules are enforced and that banks are supervised effectively in order to maintain
systemic stability.
Further, the banking sector needs to explore internal as well as industry-driven strategies that
counter some of the bank-specific factors associated with higher spreads. These could range from
diversification of products to investment in cost-saving and efficient form of technology.
39. 31
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41. 33
APPENDIX
Table 10. Sample Banks
Bank Name Ticker Origin Type
Arab Bank ARAB National Commercial
Arab Jordan Investment Bank AJIB National Commercial
Bank Al-Etihad UBSI National Commercial
Bank Of Jordan BOJX National Commercial
Cairo Amman Bank CABK National Commercial
Invest Bank INVB National Commercial
Jordan Ahli Bank AHLI National Commercial
Jordan Commercial Bank JCBK National Commercial
Jordan Kuwait Bank JOKB National Commercial
Societe General De Banque
Jordanie
SGBJ National Commercial
The Housing Bank For Trade
And Finance
THBK National Commercial
Banque Audi Not listed Foreign Commercial
