1.1 Background of the study

An efficient and vibrant commercial banking sector is a vital precondition for any market economy to be successful. Especially commercial banks provide an array of services to individuals and businesses covering almost all financial needs of individuals and businesses. Commercial banks financial services cover not only financing of foreign trade, domestic trade and industries, but also facilitate smooth functioning of the payment system in the economy. A stable financial system creates a favourable environment for depositors and investors that encourages efficient financial intermediation and the effective functioning of markets and hence promotes investments and economic growth. 

1.2 Objective of the study

 To analyse the evolution and determinants of spread of interest rate in commercial banks operating in Bangladesh.

 To understand how the spread of interest rate is influenced by bank characteristics, banking industry characteristics and macro-economic variables.

1.3 Scope of the study

This report deals with the identification of the determinants of spread of interest rate. Interest rate spread varies from bank to bank. It depends on some bank specific variables, some macroeconomic variables. Whatever, in this report data of 11 years of all the listed banking organizations have been included to determine which factor actually have impacts on spread of interest rate. The results then can be applied to know why spread of interest rate in some banks is higher and vice versa. In some adverse situation of economic condition, the results can be used as a guide to set the spread of interest rate. 

Studies to find out the determinants of spread of interest rate have been focusing on some factors which include; (1) individual bank specific factors such as- liquidity position, total assets and current assets, the rate of non-performing loan, the size of the banks, the operating cost and net operating income; (2) Macroeconomic factors include Gross Domestic Product (GDP) index, inflation and policy rate. This is not that interest rate spread depends on these factors only. It may depend on some other factors such as quality of the bank management, efficiency of the banking operations etc. However, a brief review of empirical studies that were conducted previously to determine the determinants of the spread of interest rate is demonstrated below: Maureen Were and Joseph Wambua, (2013) have studied the determinant of spread of interest rate in Kenya. It is my base research paper to be used as a guideline during the preparation of my research. 

Using the panel data analysis, Maureen Were and Joseph Wambua, (2013) found significant impacts of bank-specific variables (liquidity, credit risk, bank size, ROA, operating cost, net interest income as a part of total income) on the interest rate spread. Macro-economic variables such as GDP and inflation were not found to have significant impacts on interest rate spread. Policy rate was found to have positive relationship with interest rate spread but the significance was very weak. Gambarcorta, (2004) studies factors that explain cross-sectional differences in spread of interest rate of banks in Italy. 

The study included both the micro and macro-economic variables and the variables are operating cost, credit risk, interest rate volatility, loan demand and impact of monetary policy reflected by changes in policy rate. The study revealed that short term interest rate react less to monetary policy rate changes. In addition, the long term interest rate does not also change as banks dont feel to change long term interest rate frequently. Bank size has not been found to be an influential factor to determine interest rate spread. The study of Gambarcorta also found a positive relationship between spread of interest rate and GDP and inflation. 

During the economic boom phase, the demand for loan increases where demand for deposits also increases at the same time which in turn compels the banks to increase the spread of interest rate. Operating cost and credit risk have a positive relationship with the spread of interest rate according to his study. Banks need to incur cost to analyse the loan portfolio and monitoring the performance of loan takers. The higher the cost the larger the spread of interest rate. The study also revealed that a tightening monetary policy that increases the interest rate compels the banks to increase the lending rate and thus the interest rate spread. Mannasoo, (2012) also studied the determinants of interest rate spread in Estonia. He divided the spread of interest rate into pure interest rate and the remaining part to be explained by the market structures, regulations and idiosyncratic factors of banking organizations. According to his study, money market volatility and bank risk attitude have impacts on the pure interest rate spread. Credit risk has been found to have minimal impacts on the interest rate spread. On the other hand, the higher bank liquidity has been found to cause of lower interest rate margins. 

Grenade, (2007) conducted study to find out the determinants of spread of interest rate of commercial bank by using the annual panel data of commercial banks in the Eastern Caribbean Currency Union. The study model includes factors such as regulatory Variables (statutory minimum savings rate), market power, and non-performing loan ratio; operating cost depends on net operating income, liquidity risk and real GDP. According to the study, statutory minimum savings rate market power, credit risk; operating cost and GDP have a positive relationship with spread of interest rate. 

Siddiqui, (2012) studied the determinants of spread of interest rate in Pakistan by using annual panel data of 22 commercial banks. The variables of the study include the market share, administrative expenses, liquidity risk, credit risk, net interest income as a share of total income, and return on average assets. The study has found significant positive relationship between spread of interest rate and credit risk, administrative cost and return on assets. There have been a few studies on this topic in Bangladesh. Mustafa K. Mujeri and Sayera Younus, (2009) have studied the determinants of spread of interest rate by using the profit maximization model that based on industrial organization approach. They have used panel data consist of 48 Banks from 2004 to 2008. The study revealed that, the higher non-interest income of a bank leads lowers the spread of interest rate. It also disclosed that interest rate is impacted significantly by reserve ratio, operating cost and market share of a bank. So, there is a space to work with some other variables to identify the determinants of spread of interest rate. 

I have used variables such as credit risk, liquidity, bank size, operating cost, net interest income as a part of total income, ROA, GDP, inflation and policy rate. I hope this research will provide more clear in sights and more information about the determinants of spread of interest rate.

In this report both regression analysis and descryptive analysis have been conducted. Regression analysis has been conducted to assess the impacts of determinants of the spread of interest rate. Descriptive analysis has been conducted to show the summaries and basic features of spread of interest rate and other variables related to the spread of interest rate. Regression analysis has been under-taken by using panel data of 30 listed banking organizations from 2006 to 2017. Fixed and random effects model have been tested in this report. The basic assumptions of both fixed and random effect model are; the effects not explained by the explanatory variables are driven by; (1) individual time variant factors that include management quality of bans, efficiency of operations and technical distinctions among banks; (2) period individual-invariant factors. These factors seem to be same for all banks but fluctuate over time. Dependent and independent variable: Maureen Were and Joseph Wambua, (2013) have used some variables in their studies. 

Therefore, I have selected these variables to work with. In this report the measured variable is the spread of interest rate and the independent variables include; Bank specific factors: Credit risk (CR), liquidity (LR), operating cost; net operating income after tax (OCNOI), net interest income as a part of total income (NIITI), bank size (LBS), and Return On Assets (ROA) are the bank-specific variables. Macro-economic factors: DGP, inflation (INF) rate are macro-economic variables. Monetary policy factor: Policy rate (PR) is the representation of monetary policy impact.  The empirical model is; 

IRSit = ai + Xitβ + Ztγ + εit 

Here, IRS it is the spread of interest rate for bank I at time t measured the difference between interest income and interest expenses; ai is the bank specific fixed effects represented by the unobserved variables; Xitβ is a vector of bank specific variable, Ztγ is a vector of time specific variables, and εit is the statistical error. 

Total 3 models have been developed as; Model-1: Includes only bank-specific variables – 

INRS = ai + LR+LBS+CR+NIITI+OCNOI+ROA 

Model-2: Includes only bank-specific variables + macro-economic variables – 

INRS = ai + LR +LBS +CR +NIITI+ OCNOI +ROA +GDP+INF

Model-3: Includes only bank-specific variables + macro-economic variables + monetary policy variable – 

INRS = ai + LR +LBS +CR +NIITI+ OCNOI +ROA +GDP+INF + PR

Bank-specific variables

Credit risk - The ratio of non-performing loan to total outstanding loan is taken as an indicator of credit risk. When bad debts increase at higher rate banks needs to reserve more provisions for bad debts which forces the banks to charge premium on interest of loans. As a result, spread of interest rate becomes higher. 

Liquidity - Liquidity is measured as the proportion of banks current assets to current liabilities. A bank with higher liquidity position has lower liquidity resulting no premium for liquidity risk. Paradoxically, a bank with shortage of liquidity needs to borrow funds a higher rate in emergency situations which compel the banks to charge premiums on loans resulting higher interest rate spread. 

Operating cost - Operating cost are the expenses which are related to the bank total business expenses consists interest expenses and administration expenses. Banks incur cost to select the appropriate borrowers. The cost of monitoring the loans portfolio also increases the operating cost. Therefore, the higher the financial intermediation cost, the more likely banks would charge higher interest rate on loans which in turn increases the spread of interest rate. 

Net interest income - Net interest income is the prime source of income of a bank. The profitability of a bank depends mostly on this item. Therefore, the more dependent a bank is on the net interest income for its higher profitability, the more likely that the bank will charge higher interest rate on loan thus causing the interest rate spread go higher.

Bank size - Bank size is measured as a log of total capital of the bank. A larger bank enjoys the benefit of economies of scale and advance technology which justifies that a larger bank would charge lower interest rate thus resulting in a lower interest rate spread. A larger bank is supposed to possess the control of market which implies that by exercising monopoly or oligopoly power bank can charge higher interest rate on loan thus causing higher interest rate spread. 

Return on assets - Return on assets is measured as net income divided by the total assets. It is a strong indicator of profitability on total assets. A bank with high return on assets is more likely to charge higher interest on loans which increases the interest rate spread.

Macroeconomic variables

GDP - GDP represents the Gross Domestic Product of a country in a specific year. When the economy goes well, the demand for loan increases. So, the higher demand of loan raises up the rate of interest on loans. On the other hand, in a good economic condition the rate of loan default decreases which causes the rate of interest on loans go down. So, both negative and positive relationship of spread of interest rate with GDP is observed.

Inflation - Inflation is measured as percentage of price increase from year to year. Inflation is an element of total interest rate. So, when inflation rate increases, the interest rate also increases which causes the spread of interest rate increase. 

Monetary Policy impact - Policy rate represents the monetary policy impacts on the interest rate spread. In a contractionary monetary policy situation, the interest rate goes up thus the spread of interest rate also goes up. On the other hand, in an expansionary monetary policy situation the interest rate goes down thus causing the spread of interest rate goes down.

3.1 Sources of data

The report is based on quantitative analysis. So, quantitative data is the first requirement to conduct the report. Quantitative data about bank-specific variable has been collected from the annual report of all listed banking organizations. The macro-economic data has been collected from the website of Bangladesh bank (Alam, 2020). So, all data required to conduct this report are secondary data.

4. Descriptive and empirical analysis

4.1 Descriptive analysis

Table 1: Bank-specific variables 

Fig 1: Average spread rate of interest.

During the period from 2006 to 2017 the average interest rate spread was 3.41% and the median was 3.34%. The standard deviation of spread of interest rate was also low 0.01401. The mean liquidity position was 25.24%. The average non-performing loan as a percentage of total outstanding loans termed as credit risk is 7.08%. The average net interest income as a part of total income was 244.11%. The average operating cost as a portion of net income is 270.29%. The average Return on Assets (ROA) was 0.96% (Fig 2).

During the period from 2006 to 2017 the average GDP was 6.36%. The average inflation rate was 7.49% and the average bank rate was 7.31%. The standard deviation of GDP was 0.006237. The standard deviation of inflation was 0.015013 and the standard deviation of policy rate was 0.012439 (Fig 2). 

Table 2: Macro-economic and monetary policy variables. 

Fig 2: Macroeconomic and monetary policy variables performance.

4.2 Empirical analysis

Operating cost as a portion of net operating income has a negative relationship with spread of interest rate. This result varies with the findings of previous studies such as the study of Gambarcorta, (2004). He found a positive relationship between the operating cost and spread of interest rate. However, this result is insignificant as the t-value is far less than 2. ROA has a positive relationship with interest rate spread. This result is similar with the findings of Sidiqqui, (2012). He found an effect on higher profitability behaviour on the interest rate spread.  

DGP and inflation has negative and positive relationship respectively with interest rate spread. This result is consistent with the findings of Gambarcorta, (2004). Those findings reveal that DGP can impact the spread of interest rate both positively and negatively. Gambarcorta, (2004) also found that as inflation increases, the interest rate also increases. Policy rate has a negative relationship with interest rate spread. This result is not consistent with previous results. But the t-value of this relationship is less than 2 and this relationship is insignificant at 5% level of significance. 

The result is consistent in some extent to the findings of Gambarcorta, (2004). He said that both short term and long-term interest rate is insensitive to monetary policy stance. Sometimes one reason may work behind the negative relationship that decrease of loan demand compels the banks to decrease the interest rate and thus reducing the spread of interest rate. There is a negative relationship between liquidity position and interest rate spread. This result is consistent with the findings of Mannasoo, (2012). His study revealed a negative relationship between liquidity position of a bank and the interest rate spread. There is a positive relationship between bank size and spread of interest rate. This result is congruent with the findings of Allen, (1988). He concluded that banks monopoly power has a positive impact on the interest rate spread. A positive relationship exists between credit risk and interest rate spread. This result is compliant with the studies of Sidiqqui, (2012). Sidiqqui also found a positive relationship between credit risk and spread of interest rate in commercial banks of Malawi and Pakistan. This result is also similar with the findings of Gambarcorta, (2004). This result is also similar with the findings of Mannasoo, (2012) who found a significant positive relationship between credit risk and spread of interest rate. Grenade, (2007) found a positive relationship between credit risk and interest rate spread. Net interest income as a part of total income has a positive relationship with spread of interest rate. This result is consistent with the findings of Folawewol and Tennant conducted in Sharan African countries. 

So, the regression equation according to the fixed effect is –

Model-1

INRS =0.018131 - 0.015574 * LR + 0.001420* LBS + 0.001631 * CR + 0.00244 * NIITI - 0.00133 * OCNOI + 0.281107 * ROA - 0.133098 * GDP + 0.167815 * INF - 0.069433 * PR +εit

The value of R-square for this equation is 0.728855. It means that 72% variation in the dependent variable is explained by the independent variables. Constant is 0.018131. This means that interest rate spread will be 0.018131   irrespective of independent variables. There are some unobserved variables such as quality of management, use of most advanced technology which has impacts on the variation of dependent variable. 

Model-2

INRS  =0.008195  - 0.001716 * LR  + 0.001745* LBS  + 0.002969 * CR  + 0.003904 * NIITI  - 0.002087 * OCNOI  + 0.268244 * ROA  - 0.177999 * GDP  + 0.14484 * INF  +εit

The value of R-square for this equation is 0.378449. It means that of 37.84% variability exist in the dependent variable and explained by the independent variables. Constant is 0.008195. This means that interest rate spread will be 0.008195 irrespective of independent variables. There are some unobserved variables such as quality of management, use of most advanced technology which has impacts on the variation of dependent variable. It is apparent here that when we exclude policy rate from the independent variables, the constant decreases and the coefficients of independent variables increases except inflation.

Model-3

INRS = - 0.024036 - 0.021997 * LR + 0.005312* LBS + 0.000876 * CR + 0.00235* NIITI - 0.001284 * OCNOI + 0.287678 * ROA +εit

The value of R-square for this equation is 0.740645. It means that 74% of the variability of spread of interest is accounted for by the variables in the model. Constant is - 0.024036. This means that interest rate spread will be - 0.024036irrespective of independent variables. It is apparent here that when we exclude macro-economic and policy rate variables, the impacts of bank-specific variables on the dependent variables increases. 

From the Fixed Effect, It is seen that credit risk, bank size, net interest rate income ratio, ROA is positively related to the spread of interest rate. But only net interest income, ROA has significant relationship at 10% level of significance. This result is similar with the previous studies. In contrast, liquidity position, operating cost ratio GDP and policy rate is negatively related to interest rate spread. In this respect operating cost, GDP and policy rate has significant relationship with interest rate spread. Among them liquidity position, GDP is consistent with previous studies. Operating cost and policy rate are inconsistent with previous result but insignificant at t-values and at 5% level of significance.

The authors would like to thank all co-authors for the valuable suggestions in writing this article and also all kind of support.

The authors declare no conflict of interest.