What Factors Drive Interest Rate Spread in Commercial Banks? Empirical Evidence from Bangladesh”

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Internship Report Submission
on
“What Factors Drive Interest Rate Spread in
Commercial Banks? Empirical Evidence from
Bangladesh”
Submitted By
Masud Parvej Rubel
ID: 18-131
BBA 18th Batch
Department of Finance
University of Dhaka
Date of Submission: 15 May, 2016

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Submitted To
Faculty of Business Studies
University of Dhaka
Supervised By
Md. Sajib Hossain
Assistant Professor
University of Dhaka
---------------------------------------------------------------------------------------
Signature of the Supervisor
Submitted By
Masud Parvej Rubel
ID: 18-131
BBA 18th Batch
University of Dhaka
Date of Submission: 15 May, 2016

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Letter of Transmittal
May 15, 2016
Md. Sajib Hossain
Assistant Professor,
Department Of Finance,
Faculty of Business Studies,
University of Dhaka
Subject: Submission of the internship report on What Factors Drive Interest Rate Spread
in Commercial Banks? Empirical Evidence from Bangladesh.
Dear Sir,
At first accept my heartiest honour. I am Masud Parvej Rubel (ID: 18-131), student of
Department of Finance. You have assigned me to prepare an internship paper for the course
of Internship Program. Here is my project paper that I would like to submit to you.
I, therefore, pray and hope that you would be kind enough to accept my internship report on
the given topic. In case of any further clarification or elaboration regarding these topics I
would welcome the opportunity to consult with you.
Sincerely yours,
____________
Masud Parvej Rubel
B.B.A 18th Batch
ID-18-131
Department Of Finance
University of Dhaka

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Acknowledgement
First of all, I express my deep gratitude to God for this infinite grace that allowed me to
complete this report as a part of the BBA program. A lot of effort & study has been involved
in preparing this report is a reality.
I take this opportunity to express my gratitude & heartfelt thanks to my honourable teacher
Md. Sajib Hossain, Assistant Professor of Department of Finance, University of Dhaka, who
grant me to do my internship report on what factors drive interest rate spread in commercial
banks? Empirical evidence from Bangladesh. I also express my deep sense of gratitude to the
respected teacher & supervisor for his constant supervision, moral support, valuable
instruction & helpful advice during the course of studies & research work.
His direction, critical comments criticism, generous patience greatly helped me in improving
the research capability writing skills. It would have been quite impossible to carry on the
dissertation & give it a final shape without their encouragement. It is beyond my ability to
thanks all of those marvellous people who have contributed for preparation of this report.
I would also like to thank Assistant General Manager of Janata Bank Jatrabari Corporate
Branch Md. Ahsan Ullah, Head of Credit Management Md. Nasir Uddin and other employees
of the branch for their cordial help.
Finally, I am deeply indebted to my family, teachers & friends whose invaluable support &
encouragement have done much to make this report a successful one.

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Abstract
The internship report is prepared with an aim to find the determinant factors of interest rate
spread in private commercial banks in Bangladesh. The report consists of two potions. The
first portion includes discussion on Janata Bank Limited where the writer worked as an intern
for 45 days as per the requirement. In second part, the discussion and analysis is conducted to
find the determinant factors of interest rate spread in commercial banks in Bangladesh.
Janta Bank is the second largest commercial bank in Bangladesh which was established right
after the independence of the country and was listed in the stock market of the country in
2007. The company offers a range of services and products in the form of loans and advances
and collects deposits through 907 branches of the company operating currently in Bangladesh
and four other countries. As an intern, the writer was appointed in Jatrabari Corporate
Branch of the Janata Bank where he was asked to perform his activities under Mr. Nasir
Uddin as an intern in loans and advance section of the branch.
Interest rate spread is the difference between weighted average lending and borrowing rate
and previous researchers have found that interest rate spread is determined by banks
considering some macroeconomic factors, banking sector specific factors and company
specific factors. Keeping in mind the literature review, the writer has used loan to asset ratio,
debt to equity ratio non-performing loans evaluation through credit risk, return on assets,
return on equity, net interest margin of the companies as bank specific factors, statutory
liquidity requirement as industry specific factor and GDP and Inflation as macroeconomic
variable. Secondary data sources were used to collect the data that included annual reports of
30 commercial banks for the period from 2006-2014 and prospectus of FSIBL.
The analysis of the data collected has shown that bank specific factors are significant in
determining interest rate spread along with sector specific factors while macroeconomic
variables play a very insignificant role in determining the interest rate spread of the private
commercial banks in Bangladesh.

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Table of Contents
Letter of Transmittal ..................................................................................................................3
Acknowledgement .....................................................................................................................4
Abstract ......................................................................................................................................5
Part 1: Internship at Janata Bank Limited ................................................................................10
1. Overview of Janata Bank Limited ................................................................................11
1.1 History and structure of Janata Bank .........................................................................11
1.2 Key Products and Services.........................................................................................12
1.3 Achievements.............................................................................................................15
1.4 Some key indicators of Janata Bank from 1972 to 2014 ...........................................16
2. Overview of Jatrabari Corporate Branch ......................................................................17
3. My activities and Learning as an intern at Janata Bank................................................18
Part 2:.......................................................................................................................................21
“What Factors drive interest rate spread in commercial banks? Empirical evidence from
Bangladesh”.............................................................................................................................21
1. Introduction......................................................................................................................22
2. Contemporary Banking Conditions in Bangladesh..........................................................25
3. Literature Review.............................................................................................................33
4. Data and Methodology.....................................................................................................36
4.1 Data ...........................................................................................................................36
4.2 Methodology..................................................................................................................40
5. Empirical Result...............................................................................................................42
5.1 Descriptive Statistics.................................................................................................42
5.2 Correlation Analysis..................................................................................................43
5.3 Partial Correlation Analysis ......................................................................................43
5.4 Regression Analysis ..................................................................................................44
5.5 Multicollinearity Test................................................................................................47
5.6 Fixed and Random Effect within Regression............................................................47

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5.7 Selection of appropriate effect ..................................................................................50
5.8 Pesaran Test ...................................................................................................................51
6 Findings and Conclusion..................................................................................................52
References................................................................................................................................54
Appendix..................................................................................................................................56
Appendix 1: Stata Input Data...............................................................................................56
Appendix 2: Schedule of Charges for Foreign Trade & Foreign Exchange Transaction at
Janata Bank Limited.............................................................................................................63
List of Figures:
Figure 1: Bangladesh Private sector credit for the period from 13-04-2006to 13-04-2016....28
Figure 2: Profit of 20 banks in 2014-15...................................................................................29
Figure 3: Ratio of Net NPLs to total loans ..............................................................................29
Figure 4: CAR of Banks for the period from 2010 to 2014. ....................................................31
List of Tables:
Table 1: Corporate Profile of Janata Bank Limited .................................................................12
Table 2: Some indicators of JBL from 1972 to 2014...............................................................16
Table 3: JBL Jatrabari Corporate Branch at a glance ..............................................................17
Table 4:Lending rates of Janata Bank Limited, applicable for all Branches. ..........................19
Table 5: Deposits held in Deposit Money Banks for the period between January 2012 and
January 2016 ............................................................................................................................26
Table 6: Bank Credit for the period from January 2012 to January 2016 ...............................28
Table 7: NPLs in Banks in Bangladesh against loan given .....................................................30
Table 8: NPLs against loans given by SOBs from 1990 to 2014 ............................................30
Table 9: Capital Adequacy Ratio of Banks in Bangladesh for the period 2000 to 2011 .........31
Table 10 Descriptive Statistics.................................................................................................42
Table 11: Correlation Analysis ................................................................................................43

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Table 12: Partial Correlation....................................................................................................44
Table 13: Regression Analysis.................................................................................................45
Table 14: VIF Test Result........................................................................................................47
Table 15: Fixed Effect within Regression ...............................................................................48
Table 16: Random Effect within Resgression .........................................................................49
Table 17: Hauseman Test.........................................................................................................50
Table 18: Pesaran Test .............................................................................................................51

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Part 1: Internship at Janata Bank
Limited

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1. Overview of Janata Bank Limited
1.1 History and structure of Janata Bank
Janata Bank Limited is the second largest commercial bank of the country. It’s a state owned
bank that was formed just after liberation of Bangladesh. In fact it was a combination of two
smaller banks namely United Bank Limited and Union Bank Limited. The bank has a very
wide network of 906 branches all over the country. At present its authorized capital is BDT
30,000 million and paid up capital is BDT 19,140 million. Janata Bank was converted to a
limited company on 15 November, 2007. JBL provides all services of a commercial bank.
Moreover it serves its clients with most modern banking products.
The corporate profile of the company is stated below:
Janata Bank Limited Corporate Profile
Genesis Janata Bank Limited, the 2nd largest State Owned Commercial
Bank (SCB) in Bangladesh, is playing pivotal role in overall
financial activities of the country. The Bank emerged as
‘Janata Bank’ by combining the erstwhile United Bank
Limited and Union Bank Limited under the Banks
Nationalization Order (President’s Order 26) of 1972 and was
restructured as a limited company in November, 2007. Since
inception in 1972 the Bank has commendably contributed to
the socio-economic development of Bangladesh and helped
structuring solid financial ground of the country as well. Janata
Bank runs its business with 905 branches across the country
including 4 overseas branches in United Arab Emirates.
Legal Status Public Limited Company (governed by the Bank Companies
Act 1991)
Vision To become the effective largest commercial bank in
Bangladesh to support socio-economic development of the
country and to be a leading bank in South Asia.
Mission Janata Bank Limited will be an effective commercial bank by
maintaining a stable growth strategy, delivering high quality
financial products, providing excellent customer service
through an experienced management team and ensuring good
corporate governance in every step of banking network.
Core Values  Professionalism
 Growth
 Diversity
 Dignity
 Accountability
 Integrity
Chairman Shaikh Md. Wahid-uz-Zaman
Managing Director & CEO Md. Abdus Salam

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Company Secretary Md. Mosaddake-Ul-Alam
Registered Office Janata Bhaban, 110, Motijheel Commercial Area, Dhaka-1000,
Bangladesh.
Authorized Capital (31.12.2014) BDT. 30,000 Million.
Paid up Capital (31.12.2014) BDT. 19,140 Million.
Operating Profit (31.12.2014) BDT. 10,683 Million.
Credit Rating By Alpha Credit Rating Limited (On the basis of Audited
Balance Sheet-2012,2011,2010,2009 & Other Information)
Rating Mode Long Term Short Term Government Support
AAA AR-1 Without Government Support A+ AR-2 Outlook
Stable Date of Rating 19 September’ 2013 Expiry Date 18
September’ 2014
Employees (01.05.2015) 14244
Branches 906
Subsidiay Companies 1. Janata Capital and Investment Company Limited
2. Janata Exchange Company SRL, Italy
Phone PABX 9560000, 9566020, 9556245-49, 9565041-45,
9560027-30
FAX 88-02-9554460, 9553329, 9552078
SWIFT JANB BD DH
Website www. janatabank-bd.com
E-mail md@janatabank-bd.com
Table 1: Corporate Profile of Janata Bank Limited
Source: (www.janatabank-bd.com, 2016).
1.2 Key Products and Services
Janata Bank provides all commercial banking services to its clients focusing on the national
interest and sustainable growth. The major fields of its activities may be represented as
below:
 Retail/Personal Banking
 Credit programs
 Micro Enterprises & Special Credit
 Rural Banking / Credit Program
 International Banking
 Foreign Remittance and NRB
Banking
Retail Banking
In addition to normal savings and current accounts, Janata Bank presents different deposit
schemes for retail clients. As a limited income person you may select one for yourself. The
schemes are Short term deposit, Term deposit, Sanchaya pension scheme and Deposit
pension scheme. The programs offer good terms and conditions.

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At personal level Janata Bank present some credit schemes to facilitate and up lift your
standard of living. You may have one to meet up your requirement.
Credit Programs
Janata Bank in its credit programs engulfs most of the economic activities ofBangladesh with
special attention at the thrust sectors of the country. It touches about 200 items of trades,
businesses and industries. Thrust sector items, as declared by GOB and taken care of
by JBL are:
 Agro products & agro processed
goods
 Light
Engineering products including Au
to parts and Bi-cycle
 Leather goods and shoes
 Pharmaceutical goods
 Software and ICT products
 Home textile
 Ocean going ship building
Other than the thrust sector Janata Bank provides credit for all large and medium scale
industries. The credit includes capital machinery and also running capital.
Rural Banking
The bank extends its loan facility to create employment and achieve economic growth in
rural Bangladesh. It provides loan to farmers, fish and shrimp cultivators, and micro
entrepreneurs. They may have loan for agro equipment and other expenditure related to
production. All the efforts are targeted to employment generation and self employment. Well,
all these loans are at easy terms.
Almost 80% of our population lives in rural areas. So their economic empowerment is a must
for real and sustainable growth of our economy. So this bank works simultaneously to create
employment and to alleviate poverty.
As the success of a micro credit program depends mainly on intensive supervision, the bank
sometimes provides such credit in collaboration with other agencies. Collaborating GO or
NGO provide supervisors.
Micro Enterprise & Special Credit
Our rural population is badly submerged under poverty. To bring them above the poverty
level Janata Bank has taken up a good number of financing programs. Some of these are:

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 Small Farmers & Landless
Laborers Development project
(SFDP)
 Swanirvar Credit Scheme
 Co-operative Credit for rural poor
 Lending through NGOs
 Grain Storage Credit
 Ghoroa Prokalpa/Family based
micro credit
 Women Entrepreneur Development
Credit
 Small Business
Development loan Scheme
Further to the above the bank offers some special credit programs. Those are like:
 Seed Development Program
 Loan for Handicapped/Disabled
people
 Hybrid cow Rearing Program
 Credit for Forestry and
Horticulture/Nursery
 Flower cultivation
 Goat Rearing
So it is clear that Janata Bank tries to help almost all professions of our villages. Thus it’s
contributing quite substantially in reducing poverty and increasing growth.
International Banking
Janata Bank performs in international banking for its clients through 4 overseas branches and
1198 correspondent banks around the globe. It provides credit in export and import
businesses and all other banking services related to them. So you may avail the services
from Janata Bank.
Foreign Remittance and NRB services
Janata Bank serves the expatriate Bangladeshis in sending their hard earned foreign currency
to home. In addition they may have FC accounts in the bank. Attractive deposit schemes are
also offered by the bank.
Other Products
Janata Bank has logically started internet banking for its clients. You may have a lot of
banking services being at home.
JBL has introduced Debit Card service for its clients. So you are now free from any tension
of carrying huge cash.

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‘Janata’ mean a people. Janata Bank Limited has proved its name to be very correct, through
people oriented programs and schemes. At the same time it’s contributing a lot to the national
economy.
1.3 Achievements
Some of the key achievements of the bank in recent years include the followings:
 Best Presented Annual Report Awards and SAARC Anniversary Awards for Corporate
Governance Disclosers 2013
 14th ICAB National Award for Best Presented Annual Reports 2013
 ICMAB Best Corporate Award 2014
 2013 Performance Excellence Award' by Citi Bank N. A.
 The Asian Banking & Finance Wholesale Banking Awards 2013 & Retail Banking
Awards 2013'
 Business Asia Most Respected Company Awards-2012
 The Asian Banking & Finance Awards 2012’
 The Bank of the year-2011 in Bangladesh
 World's Best Bank Award-2009 in Bangladesh
 World's Best Bank Award-2008 in Bangladesh

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1.4 Some key indicators of Janata Bank from 1972 to 2014
Some key indicators of Janata Bank is shown below for the period from 1972 to 2014 where
the amounts are presented in Crore:
Table 2: Some indicators of JBL from 1972 to 2014
Source: (Annual Report of Janata Bank, 2014).

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2. Overview of Jatrabari Corporate Branch
The head of human resource posted me in Jatrabari Corporate Branch of the company as an
intern for the period from 8th March, 2016 to 24th of April, 2016.
The location of the branch along with address, telephone number and service hours is given
in the table.
Branch Name : Jatrabari Corporate Branch
Address : Haji Abdur Rahim Bhuiyan Bhaban, Holding No. 80/C/2,
Bibir Bagicha, Jatrabari, Dhaka
SWIFT Code : JANBBDDH
Telephone : 02 7121156, 7121116
District : Dhaka
Service Hours : Sunday: 10:00 am - 5:00 pm
Monday: 10:00 am - 5:00 pm
Tuesday: 10:00 am - 5:00 pm
Wednesday: 10:00 am - 5:00 pm
Thursday: 10:00 am - 5:00 pm
Friday: Closed
Saturday: Closed
Working Days : Sunday - Thursday (Except Holidays)
Assistant General
Manager of Branch
Md. Ahsan Ullah (contact number: 01727210035)
Head of Credit
Department
Md. Nasir Uddin
Table 3: JBL Jatrabari Corporate Branch at a glance
Source: (Prepared by the writer).
The branch is working in line with the directives given by main office and the regulations set
by the administrative bodies that aim at providing banking service to the people within the
commanding area, expand business, generate savings from the people of that commanding
area, keep pace in the competitive market and contribute in profitability of JB.

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There are a number of services offered by the branch explained earlier in the bank overview
section through the following departments named Administration Department, Deposit
Collection Department, Accounts Department, Clearing & collection Department, Loan &
Advance Department, Cash Department, Foreign Exchange and Remittance department.
Key customers of the branch are business persons, retailers and individuals living in Jatrabari
area and surroundings.
3. My activities and Learning as an intern at Janata Bank
As part of my BBA internship program, Janata Bank appointed me as an intern for the period
from 8th March 2016 to 25th April 2016 for a period of 45 days. As an intern there, I was
given the opportunity to work in loans and advance department of the branch which is also
known as credit management department of the branch.
The loans and advance department of the branch keeps in mind following things regarding
credit line as per suggestion and guideline by the head office and Bangladesh bank:
 The main focus of Credit Line/Program is financing business, trade and industrial
activities through an effective delivery system.
 The branch offers credit to almost all sectors of commercial activities having
productive purpose.
 The loan portfolio of the Bank encompasses a wide range of credit programs covering
about 200 items. And the branch allocates around 170 items as per the saying of the
head of credit manager who didn’t disclosed those sectors where they do not provide
loans citing secrecy of the loans.
 Credit is also offered to 15 (fifteen) thrust sectors, as earmarked by the Government.,
at a reduced interest rate to develop frontier industries.
 Credit facilities are offered to individuals, businessmen, small and big business
houses, traders, manufactures, corporate bodies, etc.
 Loan pricing system is customer friendly.
 Prime customers enjoy prime rate in lending and other services.
 Quick appreciation, appraisal, decision and disbursement are ensured.

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Key activities that I performed as an intern under direct supervision of Mr. Nasir Uddin who
is the head of credit management and senior officer Mr. Siddikur Rahman and Mr. Rubel
Ahmed are mentioned below:
As an intern, my duty was to check whether the statements provided by the clients asking for
loans and advance were genuine or not through matching and verifying the documents from
the given sources. If the applicant had previous transaction with the bank, it was checked and
in case of new client, the reports were checked in order to make sure that the statements are
matching the standard set by the bank to issue loan. The company had a fixed chart in
practice which was followed while providing loan.
Table 4:Lending rates of Janata Bank Limited, applicable for all Branches.
Source: (www.janatabank-bd.com, 2016).
Letter of credit was also issued by this section and it was seen that most of the LC’s were
commercial letter of credit which were revolving in nature. As a result, the customers had a
good relation with the employees working under this section. I observed that LCs was mostly
provided to importers of food and raw materials importers more than any other customers.
In order to get understanding of the charges for different types of LCs a pdf file was provided
to me and asked to check the rates from the pdf file whenever they needed. The file is added
in the appendix stating the charges charged by Janata Bank for different types of LCs granted
by the branch.
In Jatrabari Corporate Branch, loans are classified as personal and business loans under the
rule stated by Bangladesh bank. If any loan is not collected for a long time, the bank
classifies the loan based on its riskiness and the time of non-collection. I had to analyse all
the loan information from the specific files of each client to sort out the files according to
their duration of overdue to put them under a classification. Then my supervisor and manager
analysed the documents and checked at my works.
Along with these activities discussed above, I have also performed some other duties that
include checking of accounts to find whether they are valid for transaction or not as the bank
Small
Industry
4.00-
10.00
13 13 13 7 13 13 13 24 13 5.00-13.0013
Housing
loan
Consumer
credit
Credit
card
Credit to
NBFIs
Others
Large & Medium
Scale Industry
Agriculture Term
Loan to
large &
Term
Loan to
small
Working Capital to Industry Export Trade
financing

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has recently introduced new account number replacing old account numbers and users are
allowed to use both accounts till 2016. Besides, entry of cheque and deposits slips number
and amount in the registers and give the serial number to those slips, atching month wise L/C
and Bills transaction value between server and register, Local Bill Payment, sorting of
Cheques, vouchers and making voucher making for foreign remittance, dealing with clients
as per the demand of client and officials, putting seals and signature.
Overall working environment at the bank was very friendly and flexible and the people
working there were really helpful and guided me with patience and helped me get a
understanding of credit management and overall other activities of the branch in those 45
days when I worked for them as an intern.

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Part 2:
“What Factors drive interest rate spread in
commercial banks? Empirical evidence from
Bangladesh”

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1. Introduction
Interest rate is the amount charged, expressed as a percentage of principal, by a lender to a
borrower for the use of assets. Interest rates are one of the most important aspects of the
economic system of Bangladesh. They influence the cost of borrowing, the return on savings,
and are an important component of the total return of many investments. Moreover, certain
interest rates provide insight into future economic and financial market activity. A modern
economy is intrinsically linked to interest rates, thus their importance on the financial
markets. Interest rates affect consumer spending. The higher the rate, the higher their loans
will cost them, and the less they will be able to buy on credit. This is how it affects inflation,
if consumer spending goes down, there will be less demand for products and services, thus
prices won't rise as rapidly. Interest rates are used by central banks as a means to control
inflation. For banks, different types of interest rates are the determining factor of their income
and expenditure through deposit collected and the disbursement made of the deposit. Hence
for banks, it is important to decide on the interest rate that it will use to collect the deposit
from the depositors and the rate at which it will provide money to the borrowers. The
difference between the incomes generated from this two is the primary source of net income
for a bank. Hence for banks, it is important to know the rate which it should charge to
generate adequate income to remain in business.
Interest rate spread is the difference between weighted average deposit rate and weighted
average lending rate. It is one of the key indicators of a firm’s profitability. High Interest rate
Spreads are an impediment to financial intermediation, as they discourage potential savers
with low returns on deposits and increase financing costs for borrowers, thus reducing
investment and growth opportunities. Higher banking spreads can have a negative impact for
businesses with less financial flexibility and in particular small and medium enterprises.
Persistent high spreads are therefore a critical indicator of the poor performing financial
system and among other things pointing to the inefficiencies in the banking regulation
framework, and can consequently slow down or hinder economic growth. This is of particular
concern for developing and transition countries where financial systems are largely bank-
based, as is the case in Bangladesh and tend to exhibit high and persistent spreads.
The dominance of banking sector in Bangladesh is so high that the dominance can make the
economic activities vulnerable and on the contrary, it also highlights the crucial role played
by this sector in resource mobilisation and economic growth of the country. Banking is the

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backbone of national economy of Bangladesh. All sorts of economic and financial activities
revolve round the axis of the bank. As the industry produces goods and commodities, so does
the bank creates and controls money-market and promotes formation of capital. From this
point of view, banking-a technical profession- can be termed as industry. Services to its
customers are the products of banking industry besides being a pivotal factor in promoting
capital formation in the country. As all economic and fiscal activities revolve round this
important ‘Industry, the role of banking can hardly be over emphasized. Interest rate spreads
represent an important element for financial stability said Churchill (2014). They form a
substantial part of bank growth. Even though there has been an increase in interest rate
spreads, little research has been done on the determinants of interest rate spreads based on
Bangladesh data. On top of their prominence in the bank performance, interest rate spreads
tend to have a number of important implications for any meaningful development of an
economy. High interest rate spreads are likely to discourage potential savers and in the
process thus limit the stable availability of funds to potential investors, Structural,
informational and institutional inefficiencies characterizes financial systems in many of the
developing and underdeveloped countries, and consequentially leading to high margins
between commercial banks’ lending and borrowing rates in countries like Bangladesh. In
Bangladesh, like many of the developing countries, high interest rate spreads are still an issue
of concern despite the liberalization of the financial sector. Elevated and volatile lending rates
are cited as main causes of higher interest rate spreads, which also leads to higher costs of
capital for borrowers. Higher interest rate spreads tend to favor and promote only those short-
term high-risk ventures, thereby reducing the potential for long-term investment opportunities
stated Barquero Romero and RodrÃguez (2015) in their research on this issue.
Interest rate spreads arise out of the core functions of financial institutions most especially the
commercial banks which include lending and deposits taking. As banks lend, they charge
interest and for attracting deposits, they offer interest on deposit as compensation for their
clients’ thriftiness and the difference between the two rates forms the spread. But what are the
key determinants that decide the interest rate spread is the key question asked in the paper.
Therefore, the main objective of this paper is firstly to investigate the determinants of interest
rate spreads in Bangladesh; secondary to analyze the relationship between macro and
microeconomic variables and IRS. This paper also seeks to ascertain how macroeconomic
and banking sector indicator affects interest rate spread in Bangladesh and offer few

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suggestions for improving the IRS in Bangladesh if needed. It will be done on the basis of
the data available for the period from 2006 to 2014.
Some research conducted on this issue has shown that a number of factors affect interest rate
spread and the determining factors deferrers from bank to bank. They observe that pure
spread is a microstructure phenomenon, which is influenced by the level of degree of bank
risk management, the size of bank transactions, interest rate elasticity and interest rate
variability. Considering the risk management by the bank, Churchill (2014) found that there
is a difference in the levels of spreads between banks that are risk averse and those that are
risk neutral. The findings were that banks that are risk-averse tend to operate with a minimal
spread unlike the risk-neutral banks. However, Akinlo and Owoyemi (2012) on the other
hand suggests that the nature of banks affects the interest rate as the risk-averse banks are
likely to raise their optimal interest rate and eventually leading to the reduction of credit
supplied. On the other hand, the macroeconomic activities such as monetary and fiscal policy
undertakings further influence both the actual and pure interest rate spread. Barquero Romero
and RodrÃguez (2015) also emphasize the role direct taxes, reserve requirements, cost of
transactions and forced investment play in shaping the interest rate spread.

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2. Contemporary Banking Conditions in Bangladesh
After the independence of the country in 1971, banking sector in Bangladesh started its
journey with six nationalized commercial banks, 2 State owned specialized banks and three
foreign banks. Currently there are 56 scheduled banks in Bangladesh who operate under full
control and supervision of Bangladesh Bank which is empowered to do so through
Bangladesh Bank Order, 1972 and Bank Company Act, 1991. Scheduled Banks are classified
into following types: State Owned Commercial Banks (SOCBs): There are 5 SOCBs which
are fully or majorly owned by the Government of Bangladesh. Specialized Banks (SDBs):
Four specialized banks are now operating which were established for specific objectives like
agricultural or industrial development. These banks are also fully or majorly owned by the
Government of Bangladesh. Private Commercial Banks (PCBs): There are 39 private
commercial banks which are majorly owned by the private entities. PCBs can be categorized
into two groups: Conventional PCBs: 31 conventional PCBs are now operating in the
industry. They perform the banking functions in conventional fashion i.e interest based
operations. Islami Shariah based PCBs: There are 8 Islami Shariah based PCBs in
Bangladesh and they execute banking activities according to Islami Shariah based principles
i.e. Profit-Loss Sharing (PLS) mode. Foreign Commercial Banks (FCBs): 9 FCBs are
operating in Bangladesh as the branches of the banks which are incorporated in abroad. There
are now 3 non-scheduled banks in Bangladesh which are: Ansar VDP Unnayan Bank,
Karmashangosthan Bank, Probashi Kollyan Bank.
The deposit and credit growth of the Scheduled banks for last five years is shown below:
Deposits held in DMBs
(Taka in Millions)
Items January, 2013 December,
2012
January,
2012
Percentage Changes of
January, 2013 over
December,
2012
January,
2012
Demand
Deposits*
481246 533857 510504 -9.86 -5.75
Time
Deposits*
4486388 4472968 4073881 0.3 10.13
Total 4967634 5006825 4584485 -0.78 8.36

Page | 26
2013
January,
2013
January, 2014 over
December,
2013
January,
2013
Demand
Deposits*
556818 553650 481246 0.57 15.7
Time
Deposits*
5239599 5253315 4486388 -0.26 16.79
Total 5796417 5806965 4967634 -0.18 16.68
2014
January,
2014
January, 2015 over
December,
2014
January,
2014
Demand
Deposits*
614369 656360 556818 -6.4 10.34
Time
Deposits*
5939068 5932156 5239599 0.12 13.35
2015
January,
2015
January, 2016 over
December,
2015
January,
2015
Demand
Deposits*
735659 752282 614369 -2.21 19.74
Time
Deposits*
6677403 6697949 5939068 -0.31 12.43
Total 7413062 7450231 6553437 -0.5 13.12
Table 5: Deposits held in Deposit Money Banks for the period between January 2012 and January 2016
Source: (bb, 2016).
The percentage growth of bank deposit rate in this period is shown below in the figure:
Bank Credit (Taka in Millions)
Items January,
2013
December, 2012 January,
2012
January, 2013 over
December,
2012
January,
2012
Advances 4124133 4161796 3573560 -0.51 15.86

Page | 27
Bills (Import
& Inlands
Bills)
224364 224360 217501 -7.29 -4.37
Investments 1110745 1061150 869114 4.67 27.8
Total 5459242 5447306 4660175 0.22 17.15
Items January,
2014
2013
January, 2014 over
December,
2013
January, 2013
Advances 4564607 4567984 4124133 -0.07 10.68
Bills (Import
& Inlands
Bills)
189655 193526 224364 -2 -15.47
Investments 1509139 1485902 1110745 1.56 35.87
Total 6263401 6247412 5459242 0.26 14.73
Items January,
2015
2014
January, 2015 over
December,
2014
January, 2014
Advances 5246843 5274637 4564607 -0.53 15.56
Bills (Import
& Inlands
Bills)
180415 176858 189655 2.01 -6.75
Investments 1753437 1776051 1509139 -1.27 17.69
Total 7180695 7227546 6263401 -0.65 14.65
Items January,
2016
2015
January, 2016 over
December,
2015
January, 2015
Advances 6016872 5976306 5246843 0.68 13.9
Bills (Import
& Inlands
Bills)
193005 198429 180415 -2.73 9.98
Investments 1704405 1741180 1753437 -2.11 -0.7
Total 7914282 7915915 7180695 -0.02 10.22

Page | 28
Table 6: Bank Credit for the period from January 2012 to January 2016
Source: (bb, 2016).
Figure 1: Bangladesh Private sector credit for the period from 13-04-2006to 13-04-2016
Source: (Tradingeconomics, 2016).
The trend shows that amount of credit disbursed by commercial banks in Bangladesh is in the
rise and is expected to grow in the near future periods.
The amount of profit generated by the commercial banks in the 2014-15 fiscal periods has
increased in comparison to previous reporting period of the companies. A list of profit
generated by twenty local commercial banks is shown below:
Bank’s profit (In crore Taka)
Bank Name 2014 2015
Islami Bank 1703 1807
Pubali 770 795
Mutual Trust bank 273 303
Bank Asia 585 605
Social Islami 470 580
Prime 662 634
NCC 385 419
IFIC 385 406
Al-Arafah 318 649
Shahajalal Islami Bank 247 275
Meghna 17 65
Southeast 829 835

Page | 29
South Bangla 32 81
Union Bank 45 112
EXIM Bank 585 660
DBBL 532 670
AB Bank 693 760
UCBL 871 833
Dhaka Bank 385 519
Premier Bank 184 225
Figure 2: Profit of 20 banks in 2014-15
Source: (Lankabd, 2016).
The list shows that these banks have exceeded the amount of profit generated by the
companies in 2014-15 sessions in comparison to 2-13-14 session which is a positive sign for
the banks operating in Bangladesh.
Non Performing Loans (NPLs) are another critical aspect of banking business in Bangladesh
as the rate is pretty high in case of state owned commercial banks in comparison to other
banks. A figure is shown below stating the NPLs to total loan for the period from January
2012 to June 2015 for different banks:
Figure 3: Ratio of Net NPLs to total loans
Source: (Banksbangladesh, 2015)

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The annual percentage of NPLs against the loan given by banks in Bangladesh for the period
from 1999 to 2015 is shown below in the table:
Year Percentage of NPLs to Total Loans
1998 40.7%
1999 41.1%
2000 34.9%
2001 31.5%
2002 28.1%
2003 22.1%
2004 17.5%
2005 13.2%
2006 12.8%
2007 14.5%
2008 9.61%
2009 7.23%
2010 6.37%
2011 5.85%
2012 9.73%
2013 8.64%
2014 9.4%
2015 9.7%
Table 7: NPLs in Banks in Bangladesh against loan given
Source: (TheGlobalEconomy, 2016).
The average value for Bangladesh during that period was 21.59 percent with a minimum of
5.85 percent in 2011 and a maximum of 41.1 percent in 1999.
The situation is much worse in case of State owned banks in Bangladesh. NPLs for the state
owned banks in Bangladesh from 1990 to 2014 are shown below in the table:
Year NPL (%)
1990 27.59
1991 26.30
1992 31.86
1993 32.23
1994 32.12
1995 31.00
1996 32.55
1997 36.57
1998 40.38
1999 45.62
2000 38.56
2001 37.02
Year NPL (%)
2002 33.73
2003 29.00
2004 25.30
2005 21.35
2006 22.94
2007 29.90
2008 25.44
2009 21.38
2010 15.56
2011 11.27
2012 23.87
2013 28.76
2014 31.2
Table 8: NPLs against loans given by SOBs from 1990 to 2014
Source: (Lankabd, 2016).

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Under Basel-II, banks in Bangladesh were instructed to maintain the minimum capital
requirement (MCR) at 10.0% of the risk-weighted assets (RWA). Under the supervisory
review process (SRP), banks were directed to maintain a level of “adequate” capital which
was higher than the minimum required capital and sufficient to cover all possible risks in
their businesses. Between 2000 and 2011 (June), the ratio of capital to risk-weighted assets
steadily increased and met the condition of adequate capital ratio in 2008. Despite a slight
reduction in 2010, the overall increasing trend of the ratio over the 11 years proved that banks
were becoming more capable to cover the possible risks and protect the depositors and
creditors.
2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011
Total 6.7 6.7 7.5 8.4 8.7 5.6 6.7 9.6 10.01 11.6 9.3 11.4
SCBs 4.4 4.3 4.1 4.3 4.1 -.4 1.1 7.9 6.9 9.0 8.9 11.7
SDBs 3.2 3.9 6.9 7.7 9.1 -7.5 -6.7 -5.5 -5.3 0.4 -7.3 -4.5
PCBs 10.9 9.9 9.7 10.5 10.3 9.1 9.8 10.6 11.4 12.1 10.1 11.5
FCBs 18.4 16.8 21.4 22.9 24.2 26.0 22.7 22.7 24.0 28.1 15.6 21.0
Table 9: Capital Adequacy Ratio of Banks in Bangladesh for the period 2000 to 2011
Source: (ADB, 2016).
Supportive statement to the table shown above for 2011 where private commercial banks had
higher NPL than state owned Banks is shown in the appendix one of the paper.
This table show that, state owned banks both commercial specialized have been performing
poorly in maintaining the CAR ratio to the minimum level while foreign commercial banks
have always outperformed in maintaining the CAR to desirable state.
Figure 4: CAR of Banks for the period from 2010 to 2014.
Source: (bb, 2016).

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In December 2014, the average capital adequacy ratio of banks in Bangladesh was 11.4
percent, while it was 16.9 percent in Sri Lanka, 17.1 percent in Pakistan and 12.8 percent in
India. The list shown above dictates that most of the banks were capable of maintaining CAR
ratio above 10 in the period.

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3. Literature Review
A number of researches were conducted by different researchers in finding out the
determinants of interest rate spread. I have incorporated the determinant factors considered
by those researchers and the outcomes of their research in this part of the paper.
The data and empirical evidence and studies that determine the interest rate spread can be
classified in three classes namely Individual Bank Specific factors that affects the interest rate
spread include operating cost, non-performing loans, return on assets, return on equity,
structure of the balance sheet, non-interest income or non-core revenues, bank size, bank
liquidity, profitability of the bank, Banking Sector Specific factors that includes degree of
competition or market concentration, regulatory requirements such as statutory reserve
requirements or regulated minimum deposit rates, competition from local, state-owned,
private and international banks, and Macroeconomic Indicators that include Real GDP rate,
inflation rate, national savings and expenditure, investment policy, rate of employment, fund
demand and supply condition, money supply, t-bill etc.
The research conducted by Niyimbanira et al (2015) on interest rate spread of South Africa
for the period from 1990 to 2012 has shown that the determinant factors he used in his
research included inflation rate, reserve requirements, Treasury bill, discount rate, money
supply (M2) and gross domestic product per capita variables as they explain the movement of
interest rate spreads. In their research, they have found a significant short term relationship
between IRS and explanatory variables while long term effects could be significantly
explained through macroeconomic variables. They also suggested that if controlled, these
variables are most likely to have the largest effects on reducing such spreads. In addition, it
suggests that the reduction in the reserve requirements prescribed by the South African
Reserve Bank would help to reduce the interest rate spreads.
Another research conducted by Folawewo and Tennant (2008) on Sub Saharan Africa using
annual data covering 33 countries, the results obtained from the paper suggest that different
market and macroeconomic policy variables play significant role in explaining variations in
IRS in the region. The variables used include government crowding out in the banking sector,
public sector deficits, discount rate, inflationary level, level money supply, reserve
requirement, level economic development, and population size. The paper show that the
extent of government crowding out in the banking sector, public sector deficits, discount rate,

Page | 34
inflationary level, level money supply, reserve requirement, level economic development, and
population size are important determinants of interest rate spreads in SSA countries.
Research conducted by Georgievska et al (2011) on Greece has used bank specific and
macroeconomic variables in their research that included bank size, market share, deposit rate,
non-performing loan, the domestic policy rate and the foreign interest rate. The results
indicate that lending rates are mostly influenced by bank size and market share and to a lesser
extent by deposit rates and non-performing loans. In addition, policy variables such as the
domestic policy rate and the foreign interest rate also appear to be quite important.
Furthermore, the bank size and the market share, as well as the differential between domestic
and foreign rates, are the most important factors affecting interest rate spreads, while the
effect of other factors is less clear-cut.
The research conducted by Khan and Khan (2010) on IRS of Pakistan for the period from
1997 to 2009 has shown that spreads of commercial banks are primarily driven by the banks’
low cost of funding; operating expenses; and opportunities to earn income from non-core
business activities. Specifically, the share of non-remunerative deposits in total deposits and
administration expense in total expense are positively correlated with banking spreads, while
the share of non-interest income in total income negatively affects banking spreads. Further,
market concentration and macroeconomic variables, such as real GDP and interest rates also
have a positive influence on commercial bank spreads in Pakistan.
Another research conducted by Grenade (2007) on Eastern Caribbean Currency Union has
found that a trend analysis of commercial banks’ interest rate spreads in the Eastern
Caribbean Currency Union (ECCU) over the period 1993 to 2003 exposes two stylized facts.
First, spreads have been strong and persistently showing little signs of narrowing and second,
foreign owned banks have been operating with larger spreads compared to their indigenous
counterparts. This study employs panel data techniques to measure the relevance of micro
and macro factors in determining commercial banks’ interest rate spreads over the period.
The results indicate that the observed spreads can be attributed to the high level of market
concentration, high operating costs and non- performing loans and the central bank’s
regulated savings deposit rate.
Some other researcher like Akinlo and Owoyemi (2012), Asmare (2014), Barquero Romero
and RodrÃguez (2015), Churchill (2014), MÃ¤nnasoo, (2013), Neal et al (2012), Peshav
(2015) and Rebei (2014) have also conducted research on the same issue but considering

Page | 35
different periods and on different countries such as Ghana, Kenya, Nigeria, Ethiopia, Estonia,
Bulgaria and Solomon Island has also shown that these macro, micro and sectors specific
factors have significant impact in determination of IRS.

Page | 36
4. Data and Methodology
4.1 Data
Data is information that has been translated into a form that is more convenient to move or
process. Just as trees are the raw material from which paper is produced, so too, can data be
viewed as the raw material from which information is obtained. In fact, a
good definition of data is "facts or figures from which conclusions can be drawn". Data,
information and statistics are often misunderstood.
Data can be collected from two sources namely primary source and secondary source.
Primary data can be explained, as information collected from sources such as personal
interviews, questionnaires or surveys with a specific intention and on a specific subject, and
observation and discussion by the researcher him or herself, which information is then
assessed by that person. It is a direct approach and, as it is tailored to particular needs, reveals
apparently, much-needed information to that company or individual who started the research;
that is, the results are used for the purpose for which they were originally intended. It can be a
lengthy process but does provide first-hand information. Secondary data is information that is
already available somewhere, whether it be in journals, on the internet, in a company's
records or, on a larger scale, in corporate or governmental archives. Secondary data allows
for comparison of, say, several years worth of statistical information relating to, for example,
a sector of the economy, where the information may be used to measure the effects of change
or whatever it is that is being researched.
In this paper, secondary data were used. The source of secondary data is the annual reports
and 30 listed private commercial banks and Prospectus of FSIBL that contained financial
statements of the banks for the period from 2006 to 2014. Among the bank specific factors
that affect the IRS the report has included loan to asset ratio, debt to equity ratio non-
performing loans evaluation through credit risk, return on assets, return on equity, net interest
margin of the companies, and excluded structure of the balance sheet, non-interest income or
non-core revenues as these variables are not significantly important in determining IRS as
shown in previous researches and from the perspective of Bangladeshi banks as well.
Along with the data collected from the bank’s annual reports and prospectus of FSIBL, this
paper also includes data from macroeconomic and banking sector specific sources as well.

Page | 37
The secondary sources of collecting these data are the website and publications published by
Bangladesh Bank.
Among different macroeconomic factors that can affect interest rate spread, this paper is
particularly considering Real GDP and inflation rate as these two variables are directly
related to and affect other macroeconomic variables. Besides, these variables can be used as
the proxy to other macroeconomic variables like national savings and expenditure,
investment policy, rate of employment, fund demand and supply condition, money supply, t-
bill rate. The reason is that, a higher rate of real GDP growth and lower inflation rate help in
increasing investment and thus prompting people to save more in banks that the banks can
use to finance others, rate of employment will increase as the economic activities are
accelerating, National expenditure will increase and investment policy of the country will be
liberalised to promote more investment. Hence these two variables will be helpful in
understanding overall macroeconomic factors that can affect interest rate spread.
The rate of minimum deposit rate and statutory reserve in banking sector is determined by
bank itself in case of deposit but a minimum rate of deposit is asked to keep by Bangladesh
Bank and statutory reserve is set by Bangladesh bank that indicates that banking sector
specific issues related to monitory and fiscal policy of the government is reflected through the
variables.
A description of the variables used in the paper is given below:
Real GDP rate: The real gross domestic product (GDP) is an inflation-adjusted measure that
reflects the value of all goods and services produced in a given year, expressed in base-year
prices. Often referred to as "constant-price," "inflation-corrected" GDP or "constant dollar
GDP". The formula for real GDP is nominal GDP divided by the deflator, or R = N/D.
The deflator is a measurement of inflation since the base year. For example, if prices rose
2.5% since the base year, the deflator is 1.025. It reports the GDP as if prices never went up
or down. That gives a more realistic assessment of growth. Otherwise, it might seem like a
country is producing more when it's actually prices that are going up.
Inflation rate: Inflation is the rate at which the general level of prices for goods and services
is rising and, consequently, the purchasing power of currency is falling. Central banks
attempt to limit inflation, and avoid deflation, in order to keep the economy running
smoothly. Inflationary expectations help banks in deciding the rate of lending and borrowing.

Page | 38
A sustainable and predictable inflationary expectation through evaluating the rate of inflation
and the changes taking place are important in determining IRS of the banks.
Return on assets: This ratio indicates how profitable a company is relative to its total assets.
The return on asset (ROA) ratio illustrates how well management is employing the company's
total assets to make a profit. The higher the return, the more efficient management is in
utilizing its asset base. The ROA ratio is calculated by comparing net income to total assets,
and is expressed as a percentage.
Return on equity: Return on Equity (ROE) is a central measure of performance in the
banking industry, which is used to allocate capital inside and across divisions. The reliance
on this metric emerged from the risk management approach to banking which underlies bank
capital regulation. Return on equity (ROE) is the amount of net income returned as a
percentage of shareholders equity. Return on equity measures a corporation's profitability by
revealing how much profit a company generates with the money shareholders have invested.
Net Interest margin: Net interest margin is a performance metric that examines how
successful a firm's investment decisions are compared to its debt situations. A negative value
denotes that the firm did not make an optimal decision, because interest expenses were
greater than the amount of returns generated by investments.
Calculated as:
Credit Risk: A credit risk is the risk of default on a debt that may arise from a borrower
failing to make required payments. In the first resort, the risk is that of the lender and
includes lost principal and interest, disruption to cash flows, and increased collection costs.
Non-performing loans to total loans ratio (NPLR) is used as an indicator of credit risk or
quality of loans. An increase in provision for loan losses implies a higher cost of bad debt
write-offs. Given the risk-averse behaviour, banks facing higher credit risk are likely to pass
the risk premium to the borrowers, leading to higher spreads. Hence the higher the risk, the
higher the pricing of loans and advances to compensate for likely loss of the banks will be.

Page | 39
Loan to Asset Ratio: The loans to assets ratio measures the total loans outstanding as a
percentage of total assets. The higher this ratio indicates a bank is loaned up and its liquidity
is low. The higher the ratio, the more risky a bank may be to higher defaults.
This figure is determined as follows:
Loans to Assets = (Loans / Total Assets)
Debt to Equity Ratio: The debt-to-equity ratio is a measure of a company's financial
leverage that relates the amount of a firms' debt financing to the amount of equity financing.
It is calculated by:
Debt to equity ratio: (firm's total liabilities/ total shareholders' equity)
The financial industry, for example, typically has a higher debt-to-equity ratio. This is due to
the fact that banks and other financial institutions borrow money to lend money, which
results in a higher debt-to-equity ratio. Other industries that are highly capital intensive, such
as services, utilities and the industrial goods sector, also tend to have higher debt-to-equity
ratios. A higher debt-to-equity ratio typically shows that a company has been aggressive in
financing its growth with debt, and there may be a greater potential for financial distress if
earnings do not exceed the cost of borrowed funds.
Statutory reserve requirements: Statutory reserves state regulated reserve requirements.
Banking companies must hold a portion of their assets as either cash or
marketable investments. Statutory reserves are the amount of liquid assets that firms must
hold in order to remain solvent and attain partial protection against a substantial investment
loss. Holding reserves reduces the risk of liquidity. It is also used as a monetary policy tool
by the central bank of the country. Current SLR rate in Bangladesh is 19.5% with CRR of
6.5%. In this paper, Statutory Liquidity Requirement is used.

Page | 40
4.2 Methodology
The paper includes two types of analysis: exploratory and regression analysis. Exploratory
analysis is done to show trends and comparative analysis of interest rate spreads and other
variables of interest. Regression analysis is undertaken to empirically investigate the
determinants of interest rate spreads by employing panel data estimation methodology on a
panel of commercial banks using annual data for the period 2006–2014. Panel data models
provide much more insights than time series models or cross section data models because it is
theoretically possible to isolate the effects of specific effects and actions. Ignoring bank-
specific effects can lead to biased or misleading results. The basic assumption of the fixed
and random effects models is that, conditional on the observed explanatory variables, the
effects of omitted (excluded) variables are driven by (i) individual time-invariant factors such
as individual-bank management style and ability, efficiency, or other technical differences
between banks; (ii) period individual-invariant factors—that is, variables that are same for all
banks at a given time but vary through time. These are variables that reflect general
conditions affecting the operations of all banks but fluctuate over time. Both the time series
and the cross section dimensions are important elements to the understanding of bank interest
spread.
The empirical model is specified as follows:
where rit is the interest rate spread for bank i in period t, computed as the difference between
lending rate and deposit rate, Xit is a vector of bank specific variables, αi is bank-specific
fixed effects capturing the impact of unobservable (omitted) effects, Zt is a vector of time-
specific variables and ɛit is the statistical disturbance term.
The equation for the fixed effects model becomes:
Yit= β1Xit+ αi+ uit
Where,
–αi(i=1….n) is the unknown intercept for each entity (nentity-specific intercepts).
–Y it is the dependent variable (DV) where i= entity and t= time.
–Xit represents one independent variable (IV),

Page | 41
–β1 is the coefficient for that IV,
–uit is the error term
The random effects model is: Yit= βXit+ α+ uit+ εit.
The rationale behind random effects model is that, unlike the fixed effects model, the
variation across entities is assumed to be random and uncorrelated with the predictor or
independent variables included in the model.
Interest rate spreads are hypothesized to be a function of bank-specific and industry-specific
variables, as well macroeconomic factors, in line with similar studies in the literature. The
bank specific variables include net interest margin, credit risk as measured by non-
performing loans to total loans ratio, return on assets, return on equity, loan to asset ratio and
debt to equity ratio. The macroeconomic variables are real GDP growth rate and inflation
rate. Panel data used in the empirical analysis is for 30 commercial banks for which complete
data on the variables used was available.

Page | 42
5. Empirical Result
5.1 Descriptive Statistics
Descriptive statistics of the analysis show the pattern of the data used in the paper.
Descriptive statistics are used to describe the basic features of the data in a study. They
provide simple summaries about the sample and the measures. The table given below shows
the mean, standard deviation, minimum and maximum value for 10 variables used in the
paper with 270 observations for each. The mean of IRS (interest rate spread) is .0334 with
standard deviation of .0156 indicating the tightness of data set in relation to the mean is not
very dispersed. The mean of GDP is .0616 while the standard deviation is .0058 indicating
that the values are tightly close to each other with insignificant deviation from the mean. The
standard deviation against the mean of the variables for SLR (Statutory liquidity rate), ROA
(return on asset), and NIM (net interest margin) is also insignificant. But in case of ROE,
NPL, LA Ratio (loan to asset ratio) and DE ratio (Debt to equity ratio), standard deviation is
greater than mean of the variables indicating the observations are highly dispersed and the
range of values widely varies which is understandable from the minimum and maximum
values of the observations. Detailed findings of the descriptive analysis are shown in the table
below:
Variable Obs Mean Std.
Dev.
Min Max
IRS 270 .0333804 .0156115 -.024 .0988
Macroeconomic GDP 270 .0615667 .0057113 .0505 .0706
Inflation 270 .0804222 .0133495 .0666 .1062
Industry Specific SLR 270 18.61111 .4589736 18 19
Company
Specific
ROA 270 .0102667 .0235704 -.229 .11
ROE 270 .1739593 .196045 -.535 2.849
NIM 270 .0240852 .0120394 -.056 .127
NPL 270 .0805941 .2792334 .0019 4.17
LARatio 270 .6796874 .2981087 0 4.989094
DEratio 270 12.42134 15.46554 -16.69036 231.038
Table 10 Descriptive Statistics

Page | 43
5.2 Correlation Analysis
Correlation analysis measures the strengths of association between two variables. The table 7
below shows the correlation between the variables used in the paper. The analysis shows that,
the degree of relationship between IRS and NIM is the strongest among all the variables with
.6199 associations between the variables. On the other hand, the degree of relationship
between LA ratio and Inflation is the weakest among all the positively related correlations as
the correlation between this two stands at 0.0077. The correlations between all the variables
are shown in table 7 below:
IRS GDP Inflation SLR ROA ROE NIM NPL LARatio DEratio
IRS 1
GDP 0.0698 1
Inflation 0.0578 0.2612 1
SLR -0.017 -0.304 0.0942 1
ROA 0.1482 -0.082 -0.0279 0.0162 1
ROE 0.0211 -0.118 -0.1194 -0.117 0.1174 1
NIM 0.6199 0.0086 0.0527 0.0383 0.5102 0.1352 1
NPL -0.022 0.0966 -0.0335 -0.084 -0.231 0.0315 -0.034 1
LARatio -0.078 -0.055 0.0077 -0.020 0.2017 0.0174 0.4776 0.0127 1
DEratio -0.037 0.06 -0.0683 -0.137 0.1023 0.3977 -0.098 0.0096 -0.066 1
Table 11: Correlation Analysis
There is also existence of negative correlation between some of the variables. Among those
variables with negative correlation, SLR and DE ratio has the most negative correlation with
a negative correlation of -.137 while IRS and SLR have the lowest negative correlation
among the variables. The extent of negative relation among the variables is not very strong.
5.3 Partial Correlation Analysis
Partial correlation is a measure of the strength and direction of a linear relationship between
two continuous variables whilst controlling for the effect of one or more other continuous
variables (also known as 'covariates' or 'control' variables). Although partial correlation does
not make the distinction between independent and dependent variables, the two variables are
often considered in such a manner. In this paper, IRS (interest rate spread) is used as the
control variable while other variables are used as the other continuous variable. The partial
and semi-partial correlation of the variables with IRS is shown below in the table.

Page | 44
Partial
Corr.
Semipartial
Corr.
Partial Corr.^2 Semipartial
Corr.^2
Significance
ValueVariable
GDP -0.0495 -0.0299 0.0024 0.0009 0.4254
Inflation 0.0083 0.005 0.0001 0 0.8936
SLR -0.1197 -0.0728 0.0143 0.0053 0.0529
ROA -0.3601 -0.2329 0.1297 0.0542 0
ROE -0.1844 -0.1132 0.034 0.0128 0.0027
NIM 0.7857 0.7662 0.6173 0.5871 0
NPL -0.075 -0.0454 0.0056 0.0021 0.2263
LARatio -0.5934 -0.4448 0.3521 0.1978 0
DEratio 0.1491 0.091 0.0222 0.0083 0.0157
Table 12: Partial Correlation
The partial correlation table shows that, insignificant negative partial correlation exists
between IRS and GDP, IRS and NPL, moderate negative partial correlation exists between
IRS and SLR, IRS and ROE, significant negative relationship exists between IRS and Loans
to Asset Ratio at -0.5936. Positive partial correlation exists between IRS and Inflation which
is very insignificant at 0.0083 and moderate positive partial correlation exists between IRS
and Debt to Equity ratio. A strong positive partial correlation exists between IRS and NIM.
Semi-partial or part correlation is also used as like partial correlation to describe the
relationship between control variable and independent variable keeping other variables as
constants which is not considered in partial correlation.
5.4 Regression Analysis
Multiple regression analysis is used in the paper and the impact of the independent variables
on the dependent variable IRS is shown in the table below:
The Annova Table the ‘Source’, looking at the breakdown of variance in the outcome
variable, defines the categories examined: Model, Residual, and Total. The Total variance is
partitioned into the variance which can be explained by the independent variables (Model)
and the variance which is not explained by the independent variables (Residual, sometimes
called Error). The Some of Square (SS) is the three source of variance that show that total
variance of the values is .06556 of which, 0.041697 portion can be explained by the model
used. df explains the ‘Degree of Freedom’ associated with sources of variance. Here, the
number of coefficients is 10 and hence the df is 10-1=9 and the residual degrees of freedom is
270-10=260. MS is the mean of squares calculated through SS divided by respective dfs.

Page | 45
Annova Table Overall Model Fit:
Number of obs = 270
F(9, 260) =50.48
Prob>F= 0
R-squared= 0.636
Adj R-squared= 0.6234
Root MSE = 0.00958
Source SS df MS
Model 0.041697 9 0.004633
Residual 0.023863 260 9.18E-05
Total .065560066 269 .000243718
Parameter Estimates
IRS Coef. Std. Err. t P>|t|
GDP -.0926909 .1160993 -0.80 0.425
Inflation .0062161 .04644 0.13 0.894
SLR -.0026952 .0013861 -1.94 0.053
ROA -.1898805 .0305079 -6.22 0.000
ROE -.0102897 .0034004 -3.03 0.003
NIM 1.347844 .0658184 20.48 0.000
NPL -.0026435 .0021798 -1.21 0.226
LARatio -.0267792 .0022528 -11.89 0.000
DEratio .0001043 .0000429 2.43 0.016
_cons .0771436 .0286444 2.69 0.008
Table 13: Regression Analysis
Overall Model Fit portion of the regression analysis shows whether the model is true for null
hypothesis of the paper or not. F(9, 260)= 50.48 and Prob>F=0 that indicates that the model
is ok as the value of Prob>F is less than .05. R-square indicates that 63.6% of the dependent
variable IRS can be explained by the independent variables used in the paper. Adj R-square
shows the same as R-sqr but adjusted by the number of cases and number of variables.
The parameters estimate explains the basic regression equation used in the paper which is
𝑟𝑖𝑡 = 𝑎𝑖 + 𝑋𝑖𝑡 𝛽 + 𝑍𝑡𝑌 + 𝜀𝑖𝑡 applying the regression equation on our model, we can
find the following regression equation:
𝐼𝑅𝑆𝑖𝑡 = .0771436 − .0926909GDP + .0062161Inflation − .0026952SLR
− .1898805ROA − .0102897ROE + 1.347844NIM − .0026435NPL
− .0267792LARatio + .0001043DERatio + 𝜀𝑖𝑡
P>|t| - This column shows the 2-tailed p-values used in testing the null hypothesis that the
coefficient (parameter) is 0. Using an alpha of 0.05:

Page | 46
 The coefficient for GDP (-.0926909) is not statistically significant at the 0.05 level since
the p-value is greater than .05.
 The coefficient for Inflation (.0062161) is not statistically significant at the 0.05 level
since the p-value is greater than .05.
 The coefficient for SLR (-.0026952) is significantly different from 0 because its p-value
is 0.05, which is smaller than 0.05.
 The coefficient for ROA (-.1898805) is significantly different from 0 because its p-value
 The coefficient for ROE (-.0102897) is significantly different from 0 because its p-value
 The coefficient for NIM (1.347844) is significantly different from 0 because its p-value is
0.000, which is smaller than 0.05.
 The coefficient for NPL (-.0026435) is not statictically significant at the 0.05 level since
the p-value is greater than .05.
 The coefficient for LAratio (-.0267792) is significantly different from 0 because its p-
value is 0.000, which is smaller than 0.05.
 The coefficient for DEratio (.0001043) is significantly different from 0 because its p-
value is 0.016, which is smaller than 0.05.
 The constant (_cons) is significantly different from 0 at the 0.05 alpha level.

Page | 47
5.5 Multicollinearity Test
Multicollinearity is a phenomenon in which two or more predictor variables in a multiple
regression model are highly correlated, meaning that one can be linearly predicted from the
others with a substantial degree of accuracy. In this situation the coefficient estimates of the
multiple regressions may change erratically in response to small changes in the model or the
data. In order to test Multicollinearity problem of the variables used for the paper, VIF
(Variance Inflation Factor) test is used. As the name suggests, a variance inflation factor (VIF)
quantifies how much the variance is inflated. Any VIF value of less than 4 indicates non-
existence of Multicollinearity problem. The result of VIF test is shown in the table below:
Variable VIF 1/VIF
NIM 1.84 0.543376
ROA 1.52 0.659857
LARatio 1.32 0.756518
ROE 1.3 0.767768
DEratio 1.29 0.775389
GDP 1.29 0.776039
SLR 1.19 0.84298
Inflation 1.13 0.887757
NPL 1.09 0.920953
Mean VIF 1.33
Table 14: VIF Test Result
Since all the VIF values of the variables are less than 4, there is no Multicollinearity problem
in the variables used for the paper.
5.6 Fixed and Random Effect within Regression
As per the requirement, fixed and random effect within the regression is calculated as the
writer wanted to know and analyze the impact of variables that vary over time through fixed
effect and variance component of the variables across entities. The analysis will help to chose
right model for the paper.

Page | 48
Fixed effects within regression are shown in the table below:
The overall R-sq of the fixed effect model is .6258 that indicates that fixed effect model can
explain 62.58% change that independent variables can do to IRS which is the dependent
variable. The value Prob>F=0 indicates that the model is ok since the value is less than .05.
Fixed-effects (within) regression Number of obs = 270
Group variable: Code Number of groups = 30
R-sq: within = 0.5872 Obs per group: min = 9
between = 0.6750 avg = 9.0
overall = 0.6258 max = 9
F(9,231) = 36.51
corr(u_i, Xb) = 0.2036 Prob > F = 0.0000
IRS Coef. Std. Err. t P>|t|
GDP -.0258992 .0897557 -0.29 0.773
Inflation .0173048 .0353752 0.49 0.625
SLR -.0021689 .0010617 -2.04 0.042
ROA -.1088129 .0346593 -3.14 0.002
ROE -.0047701 .0028182 -1.69 0.092
NIM 1.137717 .0726812 15.65 0.000
NPL -.0005974 .001853 -0.32 0.747
LARatio -.0242326 .0020582 -11.77 0.000
DEratio .0000486 .0000345 1.41 0.160
_cons .064409 .0220116 2.93 0.004
sigma_u | .00701142
sigma_e | .00727752
rho | .48138371 (fraction of variance due to u_i)
F test that all u_i=0: F(29, 231) = 7.57 Prob > F = 0.0000
Table 15: Fixed Effect within Regression
The equation used for fixed effect is ‘Yit= β1Xit+ αi+ uit’ which can be presented as follows:
𝐼𝑅𝑆𝑖𝑡 = −.0258992GDP+ .0173048Inflation − .0021689SLR − .1088129ROA
− .0047701ROE + 1.137717NIM − .0005974NPL
− .0242326LARatio+..0000486DERatio + .064409(αi) + 0.2036(uit)
The P>|t| value of the fixed effect show that SLR, ROA, NIM, and LA ratio have significant
effect on IRS statistically and the other values can insignificantly explain IRS. The rho shows
that 48.71% of the variance is due to difference across the panel data used in the paper.

Page | 49
The random effect within regression is shown in the table below:
The overall R-sq of the random effect model is .6304 that indicates that fixed effect model
can explain 63.04% change that independent variables can do to IRS which is the dependent
variable. The value Prob>F=0 indicates that the model is ok since the value is less than .05.
Random-effects GLS regression Number of obs = 270
Group variable: Code Number of groups = 30
R-sq: within = 0.5865 Obs per group: min = 9
between = 0.6832 avg = 9.0
overall = 0.6304 max = 9
Wald chi2(9) = 383.82
corr(u_i, X) = 0 (assumed) Prob > chi2 = 0.0000
IRS Coef. Std. Err. z P>|z|
GDP -.0427135 .0898408 -0.48 0.634
Inflation .0146847 .0355518 0.41 0.680
SLR -.0022982 .0010657 -2.16 0.031
ROA -.1303253 .0319752 -4.08 0.000
ROE -.0059101 .0027899 -2.12 0.034
NIM 1.191541 .0679571 17.53 0.000
NPL -.0008947 .0018209 -0.49 0.623
LARatio -.0249546 .0019993 -12.48 0.000
DEratio .0000586 .0000344 1.70 0.089
_cons .0675748 .0221062 3.06 0.002
sigma_u | .00614258
sigma_e | .00727752
rho | .41603062 (fraction of variance due to u_i)
Table 16: Random Effect within Resgression
The equation used for random effect model is ‘Yit= βXit+ α+ uit+ εit’
𝐼𝑅𝑆𝑖𝑡 = −.0427135GDP + .0146847Inflation − .0022982SLR − .1303253ROA
− .0059101ROE + 1.191541NIM− .0008947NPL − .0249546LARatio
+ .0000586DERatio + .0675748(αi) + 0(uit) + εit
The The P>|t| value of the random effect show that SLR, ROA, ROE, NIM, and LA ratio
have significant effect on IRS statistically and the other values can insignificantly explain
IRS. The rho shows that 41.60% of the variance is due to difference across the panel data
used in the paper.

Page | 50
5.7 Selection of appropriate effect
Whether fixed effect or random effect will be chosen for the paper, the writer has conducted
Hausman Test. Hypothesis used for the selection of appropriate effect selection is given
below:
H0: Random Effect Applicable
H1: Random Effect not Applicable.
The result of the Hausman Test is given below:
---- Coefficients ----
(b) (B) (b-B) sqrt(diag(V_b-V_B))
fixed1 random1 Difference S.E.
GDP -.0258992 -.0427135 .0168144 .
Inflation .0173048 .0146847 .0026201 .
SLR -.0021689 -.0022982 .0001293 .
ROA -.1088129 -.1303253 .0215123 .0133735
ROE -.0047701 -.0059101 .0011399 .0003978
NIM 1.137717 1.191541 -.0538243 .0257756
NPL -.0005974 -.0008947 .0002973 .0003432
LARatio -.0242326 -.0249546 .000722 .0004889
DEratio .0000486 .0000586 -9.92e-06 2.79e-06
b = consistent under Ho and Ha; obtained from xtreg
B = inconsistent under Ha, efficient under Ho; obtained from xtreg
Test: Ho: difference in coefficients not systematic
chi2(8) = (b-B)'[(V_b-V_B)^(-1)](b-B)
= 7.87
Prob>chi2 = 0.4461
(V_b-V_B is not positive definite)
Table 17: Hauseman Test
Since the value of Prob>chi2 = 0.4461 which is greater than .05, it will be highly risky to
ignore null hypothesis. As a result, random effect will be applied to interpret the outcomes of
the regression analysis.

Page | 51
5.8 Pesaran Test
Pesaran test has been performed in order to find serial correlation among residuals of the
regression, heteroskedasticity and cross sectional dependence of the panel data. The Pr value
of the pesaran test is .3336 that indicates that the outcome is free from cross sectional
dependence. The outcomes of Pesaran test is shown below in the table.
Pesaran's test of cross sectional independence = 0.967, Pr = 0.3336
Average absolute value of the off-diagonal elements = 0.372
Table 18: Pesaran Test

Page | 52
6 Findings and Conclusion
The empirical result of the regression analysis has given the following outcomes:
 The descriptive analysis has shown that the macroeconomic variables GDP and
Inflation had less variation and change in average value and tightly presented in a
small range while the banking sector specific variable SLR had very little deviation
from the mean of the SLR for the period used in the paper. But in case of company
specific factors, the variation and dispersion of the data from the mean is very wide
and in some cases it is highly negative and positive in terms of positive and negative
data within the variables. Hence, change in company specific variable make the
prediction of the descriptive statistics not so pleasing while it can accurately predict
macroeconomic and sector specific trends.
 The correlation analysis of the variables have shown that the correlation among the
bank specific factors are more related to each other in either positive or negative way
while they have mediocre relationship with sector specific variables and
macroeconomic variables.
 The regression analysis has shown that, Interest rate spread gets significantly affected
by banking sector specific variables and banking company specific variables rather
than macroeconomic variables. This indicates that the policy making and regulation
by banking company authority and the banks themselves decide whether the spread
will be high or low not the macroeconomic factors of the country at least in
Bangladesh. The regression analysis has also found that the extent of impact on IRS
in Bangladesh widely varies among the banks as the dispersion is high and the
dispersion can explain more variation merging with the correlation of the dataset.
 Among fixed and random effect, random effect can better present and explain the
regression which is clear from the R-sq and rho and Hausman test. This indicates that
the observed estimates of treatment effect can vary across studies because of real
differences in the treatment effect in each study as well as sampling variability
(chance). Thus, even if all studies had an infinitely large sample size, the observed
study effects would still vary because of the real differences in treatment effects. Such
heterogeneity in treatment effects is caused by differences in study populations,
interventions received, follow-up length, and other factors.
 And finally, it is found that, overall analysis reveal that bank specific factors are
significant in determining interest rate spread along with sector specific factors while

Page | 53
macroeconomic variables play a very insignificant role in determining the interest rate
spread of the private commercial banks in Bangladesh.
Although banks have been considering and emphasizing micro variables more in order to
determine their spread, the writer thinks that proper assessment of all the factors will help the
organizations to decide their spread more productively.
At the end of the paper, I would like to conclude saying that, preparing and competing this
paper has immensely helped me in understanding the private banking sector in Bangladesh,
their overall performance in last 9 years, and most significantly, what factors are kept in mind
by private banks to determine the interest rate spread.
The internship experience at Janata Bank has also been an eye opener for me as I could
differentiate between bookish knowledge and real world scenario and hopeful that this will
help me to better prepare myself for the future challenges.

Page | 54
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Appendix
Appendix 1: Stata Input Data
Bank name-year IRS GDP Inflation SLR ROA ROE NIM NPL L/A Ratio D/E ratio
ICB Islami
Bank-2006
-0.0176 0.0667 0.0716 18 -0.229 -0.535 -0.056 0.0941 0.911273 1.330343
ICB Islami
Bank-2007
0.0525 0.0706 0.072 18 0.035 0.074 0.046 0.7083 0.876428 1.109137
ICB Islami
Bank-2008
0.0309 0.0601 0.0994 18 -0.039 0.265 0.024 0.8042 0.747382 -7.73885
ICB Islami
Bank-2009
0.0238 0.0505 0.0666 18.5 -0.109 0.465 0.015 0.8099 0.706276 -5.28009
ICB Islami
Bank-2010
0.0357 0.0557 0.0731 19 -0.073 0.234 0.023 0.616 0.745904 -4.21144
ICB Islami
Bank-2011
0.0395 0.0646 0.088 19 -0.1 0.236 0.028 0.5727 0.789471 -3.37014
ICB Islami
Bank-2012
0.057 0.0652 0.1062 19 -0.07 0.122 0.033 0.6078 0.72818 -2.74542
ICB Islami
Bank-2013
0.0394 0.0601 0.077 19 -0.048 0.073 0.015 0.7331 0.684379 -2.53091
ICB Islami
Bank-2014
0.0357 0.0606 0.0699 19 -0.02 0.03 0.011 0.7752 0.65823 -2.45629
Islami Bank-
2006
0.0347 0.0667 0.0716 18 0.009 0.14 0.021 0.0343 0.755893 14.01442
Islami Bank-
2007
0.0316 0.0706 0.072 18 0.011 0.173 0.027 0.0293 0.75731 15.16054
Islami Bank-
2008
0.0435 0.0601 0.0994 18 0.012 0.19 0.032 0.0239 0.779862 15.42042
Islami Bank-
2009
0.0411 0.0505 0.0666 18.5 0.012 0.169 0.03 0.0236 0.771159 12.84209
Islami Bank-
2010
0.0404 0.0557 0.0731 19 0.014 0.191 0.031 0.0177 0.791224 13.06622
Islami Bank-
2011
0.0457 0.0646 0.088 19 0.012 0.167 0.035 0.0271 0.785335 13.10078
Islami Bank-
2012
0.0477 0.0652 0.1062 19 0.011 0.137 0.037 0.0381 0.772629 11.15734
Islami Bank-
2013
0.0364 0.0601 0.077 19 0.009 0.115 0.031 0.0371 0.739309 11.55987
Islami Bank-
2014
0.0336 0.0606 0.0699 19 0.006 0.085 0.028 0.0492 0.706568 12.98703
Jamuna Bank-
2006
0.0468 0.0667 0.0716 18 0.013 0.162 0.024 0.0503 0.634847 11.90073
Jamuna Bank-
2007
0.0249 0.0706 0.072 18 0.003 0.054 0.017 0.0506 0.62932 14.94058
Jamuna Bank-
2008
0.0306 0.0601 0.0994 18 0.015 0.222 0.018 0.0284 0.664743 13.64625
Jamuna Bank-
2009
0.0249 0.0505 0.0666 18.5 0.019 0.232 0.018 0.022 0.66257 11.24127
Jamuna Bank-
2010
0.025 0.0557 0.0731 19 0.015 0.166 0.021 0.0182 0.699862 10.08952
Jamuna Bank-
2011
0.0281 0.0646 0.088 19 0.016 0.185 0.021 0.0286 0.65162 10.93616
Jamuna Bank-
2012
0.0209 0.0652 0.1062 19 0.01 0.125 0.018 0.0973 0.507447 12.11581
Jamuna Bank-
2013
0.0121 0.0601 0.077 19 0.01 0.129 0.01 0.0759 0.591833 11.99986
Jamuna Bank-
2014
0.0162 0.0606 0.0699 19 0.01 0.125 0.011 0.0568 0.564938 11.91636
One Bank-2006 0.0298 0.0667 0.0716 18 0.11 0.228 0.127 0.0312 4.989094 1.069457
One Bank-2007 0.0324 0.0706 0.072 18 0.015 0.221 0.023 0.0367 0.717346 13.99165
One Bank-2008 0.023 0.0601 0.0994 18 0.007 0.136 0.011 0.0374 0.67663 18.16139

Page | 57
One Bank-2009 0.0312 0.0505 0.0666 18.5 0.009 0.167 0.013 0.0437 0.593525 17.72342
One Bank-2010 0.0298 0.0557 0.0731 19 0.019 0.27 0.018 0.0371 0.668675 13.45247
One Bank-2011 0.0299 0.0646 0.088 19 0.01 0.142 0.016 0.0447 0.646245 12.78883
One Bank-2012 0.0433 0.0652 0.1062 19 0.013 0.153 0.032 0.0552 0.699204 10.70891
One Bank-2013 0.0324 0.0601 0.077 19 0.012 0.152 0.029 0.0489 0.742135 11.22722
One Bank-2014 0.0375 0.0606 0.0699 19 0.013 0.17 0.036 0.0472 0.739645 11.70039
Premier Bank-
2006
0.0379 0.0667 0.0716 18 0.014 0.227 0.024 0.0491 0.761036 15.70886
Premier Bank-
2007
0.025 0.0706 0.072 18 0.002 0.032 0.02 0.0596 0.725677 12.21234
Premier Bank-
2008
0.0205 0.0601 0.0994 18 0.017 0.209 0.024 0.0455 0.782975 11.42688
Premier Bank-
2009
0.0214 0.0505 0.0666 18.5 0.023 0.235 0.02 0.0183 0.711075 9.207586
Premier Bank-
2010
0.0271 0.0557 0.0731 19 0.026 0.283 0.022 0.0466 0.679958 9.87129
Premier Bank-
2011
0.0305 0.0646 0.088 19 0.007 0.077 0.023 0.0428 0.664098 10.23133
Premier Bank-
2012
0.0356 0.0652 0.1062 19 0.007 0.084 0.021 0.0539 0.638784 10.43396
Premier Bank-
2013
0.0274 0.0601 0.077 19 0.009 0.098 0.018 0.0573 0.586092 10.25777
Premier Bank-
2014
0.0247 0.0606 0.0699 19 0.008 0.098 0.017 0.09 0.627944 11.47588
Pubali Bank-
2006
0.0545 0.0667 0.0716 18 0.014 0.187 0.04 0.0794 0.691536 11.8986
Pubali Bank-
2007
0.0629 0.0706 0.072 18 0.019 0.228 0.048 0.0498 0.706382 11.06332
Pubali Bank-
2008
0.0586 0.0601 0.0994 18 0.017 0.201 0.044 0.0356 0.687416 10.91028
Pubali Bank-
2009
0.0509 0.0505 0.0666 18.5 0.019 0.22 0.04 0.0296 0.689753 10.31315
Pubali Bank-
2010
0.0481 0.0557 0.0731 19 0.025 0.225 0.041 0.0204 0.693635 7.933507
Pubali Bank-
2011
0.0484 0.0646 0.088 19 0.014 0.138 0.04 0.0202 0.665329 8.585742
Pubali Bank-
2012
0.0468 0.0652 0.1062 19 0.008 0.09 0.038 0.0505 0.624163 9.845595
Pubali Bank-
2013
0.0275 0.0601 0.077 19 0.011 0.125 0.024 0.0594 0.591878 10.73336
Pubali Bank-
2014
0.0255 0.0606 0.0699 19 0.013 0.141 0.021 0.0625 0.597549 10.23642
Rupali Bank-
2006
0.0211 0.0667 0.0716 18 0.002 0.44 0.009 0.5544 0.599387 231.038
Rupali Bank-
2007
0.0171 0.0706 0.072 18 -0.135 1.044 0.005 0.5275 0.577588 -8.72695
Rupali Bank-
2008
0.0232 0.0601 0.0994 18 0.011 -0.107 0.012 0.3129 0.595662 -11.0759
Rupali Bank-
2009
0.0309 0.0505 0.0666 18.5 0.006 -0.299 0.02 0.2091 0.597672 -16.6904
Rupali Bank-
2010
0.03 0.0557 0.0731 19 0.005 0.042 0.017 0.1196 0.530793 7.793039
Rupali Bank-
2011
0.0463 0.0646 0.088 19 0.008 0.072 0.029 0.0594 0.528355 8.496971
Rupali Bank-
2012
0.033 0.0652 0.1062 19 0.007 0.104 0.018 0.2607 0.524144 13.8376
Rupali Bank-
2013
0.0209 0.0601 0.077 19 0.002 0.038 0.004 0.1748 0.496767 17.22561
Rupali Bank-
2014
0.0045 0.0606 0.0699 19 0.002 0.033 -0.004 0.1215 0.466705 17.0093
Shahjalal Islami
Bank-2006
0.0573 0.0667 0.0716 18 0.022 0.384 0.031 0.0019 0.726988 16.71294

Page | 58
Shahjalal Islami
Bank-2007
0.0573 0.0706 0.072 18 0.023 0.232 0.036 0.0062 0.727294 9.168483
Shahjalal Islami
Bank-2008
0.0483 0.0601 0.0994 18 0.018 0.227 0.028 0.0044 0.728018 11.54132
Shahjalal Islami
Bank-2009
0.0357 0.0505 0.0666 18.5 0.018 0.217 0.023 0.0094 0.746056 10.95967
Shahjalal Islami
Bank-2010
0.0325 0.0557 0.0731 19 0.026 0.307 0.022 0.0191 0.779692 10.67699
Shahjalal Islami
Bank-2011
0.0387 0.0646 0.088 19 0.012 0.163 0.026 0.0189 0.766305 12.60803
Shahjalal Islami
Bank-2012
0.0552 0.0652 0.1062 19 0.013 0.181 0.03 0.0296 0.732728 12.88975
Shahjalal Islami
Bank-2013
0.0466 0.0601 0.077 19 0.011 0.119 0.024 0.0647 0.708612 10.33678
Shahjalal Islami
Bank-2014
0.0403 0.0606 0.0699 19 0.006 0.064 0.024 0.0787 0.666787 10.05653
SIBL-2006 0.0311 0.0667 0.0716 18 0.003 0.059 0.015 0.0493 0.777639 19.07905
SIBL-2007 0.0452 0.0706 0.072 18 0.006 0.09 0.016 0.0492 0.669759 13.74009
SIBL-2008 0.0687 0.0601 0.0994 18 0.007 0.108 0.022 0.0438 0.669307 14.96311
SIBL-2009 0.0674 0.0505 0.0666 18.5 0.011 0.121 0.025 0.0319 0.664833 10.24398
SIBL-2010 0.0593 0.0557 0.0731 19 0.012 0.153 0.027 0.0476 0.670991 12.02851
SIBL-2011 0.0655 0.0646 0.088 19 0.012 0.11 0.028 0.0393 0.642062 7.971858
SIBL-2012 0.0724 0.0652 0.1062 19 0.013 0.144 0.033 0.0333 0.662071 10.30995
SIBL-2013 0.0558 0.0601 0.077 19 0.01 0.113 0.031 0.0535 0.679362 10.39547
SIBL-2014 0.0532 0.0606 0.0699 19 0.012 0.157 0.032 0.0456 0.701846 11.66018
Southeast Bank-
2006
0.0205 0.0667 0.0716 18 0.017 0.18 0.02 0.0397 0.766156 9.615338
Southeast Bank-
2007
0.0257 0.0706 0.072 18 0.019 0.199 0.024 0.0377 0.748238 9.4762
Southeast Bank-
2008
0.0154 0.0601 0.0994 18 0.011 0.121 0.016 0.0412 0.742549 10.03419
Southeast Bank-
2009
0.0097 0.0505 0.0666 18.5 0.017 0.165 0.012 0.0373 0.687785 8.945734
Southeast Bank-
2010
0.0209 0.0557 0.0731 19 0.021 0.161 0.02 0.0426 0.713144 6.686008
Southeast Bank-
2011
0.011 0.0646 0.088 19 0.012 0.099 0.013 0.0351 0.678704 7.158347
Southeast Bank-
2012
0.0099 0.0652 0.1062 19 0.009 0.083 0.011 0.0447 0.668534 8.599699
Southeast Bank-
2013
0.0068 0.0601 0.077 19 0.015 0.154 0.009 0.0394 0.610435 9.074758
Southeast Bank-
2014
0.0132 0.0606 0.0699 19 0.016 0.156 0.013 0.0364 0.621579 8.640483
Standard Bank-
2006
0.0388 0.0667 0.0716 18 0.021 0.199 0.033 0.0098 0.749327 8.556548
Standard Bank-
2007
0.0206 0.0706 0.072 18 0.015 0.125 0.018 0.0152 0.754314 7.294622
Standard Bank-
2008
0.0306 0.0601 0.0994 18 0.019 0.192 0.028 0.0187 0.794786 8.985613
Standard Bank-
2009
0.0249 0.0505 0.0666 18.5 0.016 0.181 0.022 0.0183 0.776634 10.60685
Standard Bank-
2010
0.0277 0.0557 0.0731 19 0.021 0.243 0.026 0.0196 0.776992 10.80665
Standard Bank-
2011
0.0322 0.0646 0.088 19 0.017 0.189 0.029 0.0219 0.738223 9.909361
Standard Bank-
2012
0.0312 0.0652 0.1062 19 0.014 0.162 0.025 0.025 0.64974 10.51967
Standard Bank-
2013
0.0225 0.0601 0.077 19 0.009 0.109 0.021 0.035 0.679365 10.75474
Standard Bank-
2014
0.0298 0.0606 0.0699 19 0.009 0.104 0.025 0.0355 0.672048 11.23845

Page | 59
The City Bank-
2006
0.0386 0.0667 0.0716 18 0.005 0.095 0.025 0.0487 0.648931 17.74656
The City Bank-
2007
0.0437 0.0706 0.072 18 0.007 0.119 0.019 0.063 0.549446 15.96214
The City Bank-
2008
0.0441 0.0601 0.0994 18 0.007 0.094 0.026 0.0624 0.602665 12.54236
The City Bank-
2009
0.0526 0.0505 0.0666 18.5 0.011 0.14 0.027 0.0718 0.568697 12.03952
The City Bank-
2010
0.0474 0.0557 0.0731 19 0.021 0.162 0.039 0.044 0.663673 6.891192
The City Bank-
2011
0.0429 0.0646 0.088 19 0.018 0.115 0.038 0.034 0.662792 5.481966
The City Bank-
2012
0.0429 0.0652 0.1062 19 0.006 0.044 0.036 0.075 0.636425 6.218832
The City Bank-
2013
0.0395 0.0601 0.077 19 0.003 0.027 0.033 0.081 0.615803 7.112932
The City Bank-
2014
0.0305 0.0606 0.0699 19 0.01 0.076 0.029 0.059 0.658413 6.931372
Trust Bank-2006 0.038 0.0667 0.0716 18 0.012 0.228 0.019 0.0132 0.626192 17.23444
Trust Bank-2007 0.0487 0.0706 0.072 18 0.008 0.111 0.022 0.0271 0.593203 13.10311
Trust Bank-2008 0.0396 0.0601 0.0994 18 0.012 0.147 0.03 0.0252 0.715468 11.33331
Trust Bank-2009 0.0333 0.0505 0.0666 18.5 0.011 0.163 0.017 0.0264 0.602566 13.43637
Trust Bank-2010 0.0291 0.0557 0.0731 19 0.022 0.257 0.026 0.0241 0.732693 10.56798
Trust Bank-2011 0.026 0.0646 0.088 19 0.012 0.159 0.018 0.0281 0.708145 12.13789
Trust Bank-2012 0.0414 0.0652 0.1062 19 0.002 0.027 0.02 0.0427 0.608258 13.06457
Trust Bank-2013 0.0167 0.0601 0.077 19 0.003 0.045 0.012 0.0312 0.708304 15.43127
Trust Bank-2014 0.022 0.0606 0.0699 19 0.009 0.153 0.019 0.0245 0.75333 16.47739
UCBL-2006 0.0417 0.0667 0.0716 18 0.015 0.242 0.033 0.0353 0.158266 15.60033
UCBL-2007 0.0371 0.0706 0.072 18 0.016 0.26 0.032 0.0492 0.109957 14.99522
UCBL-2008 0.0427 0.0601 0.0994 18 0.012 0.174 0.031 0.0462 0.685955 13.77903
UCBL-2009 0.0425 0.0505 0.0666 18.5 0.01 0.164 0.029 0.0263 0.681804 14.85914
UCBL-2010 0.0372 0.0557 0.0731 19 0.017 0.279 0.03 0.012 0.720949 15.60659
UCBL-2011 0.0405 0.0646 0.088 19 0.017 0.184 0.031 0.0179 0.684731 9.567357
UCBL-2012 0.0453 0.0652 0.1062 19 0.008 0.087 0.032 0.0359 0.656576 10.40781
UCBL-2013 0.0431 0.0601 0.077 19 0.014 0.15 0.031 0.0403 0.658972 10.0033
UCBL-2014 0.0372 0.0606 0.0699 19 0.014 0.164 0.03 0.0399 0.655121 10.80435
Uttara Bank-
2006
0.0988 0.0667 0.0716 18 0.006 0.083 0.022 0.134 0.211525 14.14585
Uttara Bank-
2007
0.0633 0.0706 0.072 18 0.008 0.167 0.021 0.1013 0.273471 20.54437
Uttara Bank-
2008
0.0414 0.0601 0.0994 18 0.019 0.309 0.032 0.0546 0.635499 14.84354
Uttara Bank-
2009
0.0264 0.0505 0.0666 18.5 0.015 0.178 0.024 0.0521 0.548347 10.5912
Uttara Bank-
2010
0.0272 0.0557 0.0731 19 0.019 0.18 0.023 0.0354 0.597564 8.459219
Uttara Bank-
2011
0.0337 0.0646 0.088 19 0.017 0.172 0.025 0.032 0.554983 9.096729
Uttara Bank-
2012
0.0168 0.0652 0.1062 19 0.01 0.127 0.014 0.0432 0.49581 11.60954
Uttara Bank-
2013
0.009 0.0601 0.077 19 0.01 0.123 0.007 0.0585 0.490725 11.34546
Uttara Bank-
2014
0.0181 0.0606 0.0699 19 0.01 0.115 0.016 0.0584 0.52793 10.50465
Bank Asia-2006 0.0258 0.0667 0.0716 18 0.016 0.244 0.022 0.0227 0.730209 14.63204
Bank Asia-2007 0.0264 0.0706 0.072 18 0.017 0.256 0.025 0.0244 0.740371 13.91264

What Factors Drive Interest Rate Spread in Commercial Banks? Empirical Evidence from Bangladesh”

What Factors Drive Interest Rate Spread in Commercial Banks? Empirical Evidence from Bangladesh”

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