Monetary policy collision on the performance of banking sector in India

Abstract

Purpose

The study aims to identify the impact of monetary policy tools on the performance of banks in India, and this could be an excellent suggestion to the regulators in framing the favourable interest rates which would meet the macroeconomic objectives of the Indian economy.

Design/methodology/approach

The design adopted in this study is descriptive and analytical research. Correlation and regression analysis is used to determine the relationship between bank rate (BR) and the performance of public sector banks in India. The sample chosen for this study is the public sector banks actively performing in India.

Findings

The performance is measured by taking three factors, and they are deposits, loans and advances (L&A) and total asset value of the banks. All three factors have shown an impact of BR on them during the five years. L&A affected the least amongst the three factors, but the other two were significantly impacted by the change in BR by the Reserve Bank of India. So, there should be a favourable fluctuation in the BR which will bring flexibility in the banking system, and they can perform well in the economy and the central bank also can concentrate on the macro-economic situation in the country.

Originality/value

This paper helps in giving suggestions to the Central bank, researchers, financial institutions to look into the financial performance and monetary policy rates and the central bank also can concentrate on the macro-economic situation in the country.

Citation

Nikhil, B. and Deene, S. (2023), "Monetary policy collision on the performance of banking sector in India", Vilakshan - XIMB Journal of Management, Vol. 20 No. 1, pp. 154-165. https://doi.org/10.1108/XJM-11-2020-0200

Introduction

The contribution of financial sector reforms towards economic growth and development is tremendous. Banks play a vibrant role in the economy by regulating the price liquidity by accumulating a large number of small deposits and giving credit to those who require money. The regulator of the banking system in India is the Reserve Bank of India, which is also called the central bank or the apex bank of India. The Reserve Bank of India regulates the money supply and price liquidity in the economy and also concentrates on controlling inflation in the marketplace. Central banks will monitor the liquidity with the help of commercial banks working in the economy. The quantitative tools decided by the monetary policy are implemented on commercial banks to regulate the money supply and price liquidity in the economy. The monetary policy rate varies according to the financial situation of the economy as and when required. For this monetary policy, the committee is framed and the committee will decide the rates bi-monthly (earlier was quarterly) in India. As and when the rate changes that should be adopted by every commercial bank in the economy. Sometimes the rates are increased to reduce the price liquidity in the economy and vice-versa. Hence, the central bank plays a vital role in balancing the liquidity and issuing new notes to the economy. Decock defined the central bank as “It is a banking system in which a single bank has either a complete or a residual monopoly of note issue.”

Commercial banks play a vital role in circulating the money across the economy, i.e. they will balance between the one who has more money to invest and one who needs money. The primary objective of banks is to collect savings or idle cash from the public by providing a specified rate of interest. The same money is lent to the public at a higher rate of interest. In the words of Crowther, “Bank is an institution that collects money from those who have in spare or who are saving it out of their income and offer this money out to those who require it.” The other objectives are to create awareness about savings amongst the people, to concentrate on profit maximisation, to expedite investment, to build capital through savings, to maintain economic stability, to extend service to customers, to assist the government for trade and business and socio-economic development, to extend assistance and suggestion to the government on economic issues.

Public sector banks are the commercial banks which come under the scheduled banks of the Reserve Bank of India. These are called the public sector because the Government of India does the majority of the investment. The governments share will be more than or equal to 51% of the total investment. After so many mergers and acquisitions now, only 12 banks are working as public sector banks.

Monetary policy is the policy framed and controlled by the central bank of India with the help of the monetary policy committee. The committee will hold the meeting bi-monthly and will decide the rates of the monetary policy. The tools under the monetary policy are cash reserve ratio, statutory liquidity ratio, repo and reverse repo rate, marginal standing facility, bank rate (BR), etc., in which BR and Repo rate will decide the credit system by the committee and banks. The tools mentioned are quantitative tools which are announced by the committee, and all the commercial banks should adopt the selected rates in India, i.e. either it may be public sector or private sector banks. The rates decided by the committee will help the economy to control liquidity and inflation.

There are two types of monetary policy situations, and they are expansionary and contractionary policy. Expansionary monetary policy helps in supplying the money to the economy by reducing the interest rates when there is less liquidity. Hence, it is used during a time of recession. Contractionary monetary policy helps in reducing the excess liquidity and inflation in the economy by increasing interest rates so that the money supply will become limited and automatically the inflation comes down.

Statement of the problem

Banks play a dominant role in providing credit facilities to the private sector in the economy. The primary source of fund for the private sector is the banks (major part) in terms of different types of credit. Then, also the banks face a lot of problems from the rules and regulations from central banks and government policies in the economy. Hence, this study is made to identify the impact of monetary policy tools on the performance of banks in India, and this could be an excellent suggestion to the regulators in framing the favourable interest rates which would meet the macroeconomic objectives of the Indian economy.

Research question

RQ1.

Does the monetary policy rate have any significant impact on the total asset value (TAV) of public sector banks in India?

RQ2.

Does the monetary policy rate have any significant impact on the deposit mobilisation (DM) of public sector banks in India?

RQ3.

Does the monetary policy rate have any significant impact on the loans and advances (L&A) of the public sector banks in India?

Objective of the study

Regular change in the policy rate by the central bank will have some kind of impact on the performance of the public sector and other commercial banks. Financial performance may get affected due to frequent change in rates. This study will focus on the influence of policy rates on the financial performance of public sector banks in India.

Therefore, the objectives of the study are as follows:

• Whether the monetary policy rate (BR) will significantly influence the TAV of public sector banks in India.

• Whether the monetary policy rate (BR) will significantly impact the DM of the public sector banks in India.

• Whether the monetary policy rate (BR) will significantly influence the L&A of the public sector banks in India.

Hypothesis of the study

The hypothesis of the study is framed as under:

HA1.

There is no significant relationship between the monetary policy rate and TAV of public sector banks in India.

HA2.

There is no significant relationship between the monetary policy rate and DM of public sector banks in India.

HA3.

There is no significant relationship between the monetary policy rate and L&A of public sector banks in India.

Scope of the study

The study covers the problem which is generally faced by all the banks in India and also amongst the world. The study highlights the relationship between the BR and the dependent variables which represents the financial position of the banks and how the financial performance of the banks are getting affected are discussed the study cover the period from 2015–2020. In this period, how BR fluctuations have impacted the financial position like TAV, DM and L&A of the public sector banks in India.

Significance of the study

The study highlights the impact of the monetary policy rate (BR) on the financial performance of public sector banks in India, which helps the banks to decide about the credit facilities to be given further. The essential factors like TAV, L&A and DM are taken in this study which shows the financial situation of the banks and how they are impacted due to a regular change in the monetary policy rate by the central bank.

Operational definition of terms

Financial performance: It refers to analyse the strength and weakness of a firm concerning its financial statements. It is performed to find out the profitability, financial position and creditability of the banks.

BR: BR is the rate at which banks provide credit facilities to private firms. It is the minimum interest rate charged by commercial banks. The BR will be decided by the monetary policy committee of the Reserve Bank of India according to the financial situation in the economy.

DM: It shows the average mobilisation of deposits of the banks in the economy. Deposits are the bank accounts which allow the account holder to make a demand on their banks’ deposits.

L&A: These are the debts given to the customers of the bank. The loan represents a debt provided by the banks for more than a year. The advance represents the fund offered as a debt which should be repaid within a year.

TAV: It means the current total value of the assets available in the banks, including existing assets. The depreciation will be deducted early, and the value of the asset at present is termed as a TAV of the banks.

Literature review

Ghonasgi (1969) study has highlighted the contribution of the central bank and monetary policy for the growth of the economy. The primary purpose of this study was to highlight the significant developments during the year 1967–1968. During this period, so many changes were adopted for developing the economy. It has briefed about all the policies and new measures taken by the central bank in India.

Anik and Kashyap (1992) study used the relative movements in the bank loans, and commercial paper to offer confirmation on the existence of a loan supply, network of monetary policy transmission. The study found that tighter monetary policy leads to a shift in firms mix of external financing-commercial paper issuance rises. At the same time, bank loans fall, suggesting that loan supply has indeed been reduced. This shows that bank and non-bank source of finance are also not perfect substitutes of business. They also found that this view of the transmission mechanism can help explain why interest rate spreads involving commercial papers rates have had considerable predictive power for many measures of economic activity.

In their study it explained that the financial sector and, in particular, the banking industry plays an important role in the allocation of capital resources and risk sharing of future flows in an economy Luis and Ahumada (2004). From a macroeconomic perspective, the nature of banking activities and banks position as intermediaries makes these institutions relevant to the transmission of monetary policy. Overall, this study says that a number of macroeconomic and microeconomic works on the subjects of monetary policy transmission and the regulation of the banking industry.

In her article “Monetary policy: its impact on the profitability of banks in India” using various instruments of monetary policy has made a detailed evaluation of the profitability of the banks in India Rao (2006). The study says that the Reserve Bank would continue to keep a constant watch on the domestic and external situation. Monetary policy is guided by the objective of provision of adequate liquidity to meet credit growth and support investment demand in the economy whilst monitoring carefully the movements in the price level. The policy stance continues to be one of the preferences for a soft and flexible interest rate environment within the framework of macroeconomic stability.

Tarapore (2007) explains about the dilemmas and challenges of formulating a favourable monetary policy and studies the implications of the changing dimensions of monetary policy on the different parameters determining the bank’s growth rate in the article “Impact of Monetary policy on a banks growth path”. It was found in this article that it could take 50 years or more for the private sector and foreign banks to predominate in the Indian banking sector. Whilst mergers are desirable and necessary, this by itself would not suffice. The article also warns that the banks in India are going to face severe adjustment problems. S.S Tarapore’s message to banks is: Please take care of yourselves and the rest of the economy will take care of itself. The banks should not immolate themselves in pursuit of the interests of an expanding economy.

Has briefed about, How far is the short-run monetary policy effective in influencing the demand for bank credit and thereby the pace of economic activity in India and other emerging market economies (EMEs) B L Pandit (2011). This study focusses on how, amongst other factors, change in a monetary policy variable like the policy rate in India and six other EMEs, will influence the firms’ demand for non-food bank credit, which in the short run reflects the pace of potential economic activity in the industrial sector. The study concludes that a change in policy rates, the behaviour of lending and deposit rates very clearly shows that the Policy Rate Channel of the transmission mechanism, itself a hybrid of the traditional interest rate channel and credit channel, is working in India and other EMEs.

The article accesses various parameters to credit risk management as it affects banks financial performance Danson Musyoki (2011). The study discloses that all the selected parameters have a reverse impact on the banks financial performance concerning the other indicators of credit risk management. The study recommends advising the commercial banks to design and formulate strategies that will not only reduce the exposure of the banks to credit risk but will but also boost profitability and effectiveness of the banking sector.

The purpose of the study is to examine the financial performance of the State Bank of India (SBI), which is a public bank Industrial Credit and Investment Corporation of India (ICICI), which is a private bank Anurag (2012). The research done here is in a descriptive and analytical nature. In this study, the data used is secondary data. The comparison done between two banks is based on ratios such as credit-deposit ratio and net profit margin ratio the findings of the study says that public bank is performing well and financially sound than the private bank. Still, ICICI is managing well than SBI in the context of deposits and expenditure.

This thesis has concluded that there exists a long-run relationship between the variables in the model Ayodele (2014). Explicitly, the findings revealed that exchange rate and interest significantly influenced commercial banks’ lending whilst liquidity ratio and money supply exert a negative effect on commercial banks’ loan and advances. The primary conclusion drawn is that monetary policy instruments are not adequate to stimulate commercial bank L&A in the long-run. In contrast, banks’ total credit is more responsive to the cash reserve ratio. Here the author suggests that monetary authority should make efforts to develop indirect monetary instruments and exercise appropriate control over the monetary sector.

In the study “Does Monetary policy affect bank risk?” it is explained that, the effect of relatively loose monetary policy on bank risk through large panel including quarterly information from listed banks operating in the European Union and the USA Yener Altunbasa (2014). The study identified that low-interest rates over an extended period of time contributed to an increase in bank risk. The results are robust to other factors that might have influenced bank risk-taking, including financial innovation, booming asset prices, the intensity of financial regulation, investors’ risk perception, bank-specific characteristics and competition policies.

In their study they highlighted the effect of monetary policy on the financial performance of commercial banks listed in the Nairobi Securities Exchange (NSE) in Kenya Nyamute (2016). They went through a descriptive survey of the commercial banks listed in NSE. The finding of the study states that the monetary tools had varying degrees of relationship with the financial performance of the commercial banks listed in NSE. Id on the NSE. It also states that the open market operations rates were positively correlated whilst central bank rate and Cash reserve ratio (CRR) rates are negatively correlated with the commercial bank’s list.

Kovtun (2017) article aims to find the monetary policy instruments that influence the development or degradation of the regional banking sector in Russia. The study helps to see the different commercial bank responses to changes in conducted monetary policy. Ordinary Least squares estimator and generalised least squares techniques were used to assess the effect of macroeconomic shocks and instruments of banking supervision on lending activity. The results said that the interest rate does not affect the lending activity in most of the regions.

In the case study entitled “Monetary policy and commercial banks credit performance: Evidence from United Bank of Africa (UBA) PLC” explained that the model expresses bank monetary policy represented by monetary policy ratio, CRR, statutory liquidity ratio and whilst return on assets (ROA) is used as a proxy for banks credit performance Dare (2017). The study reveals a positive but statistically insignificant relationship between monetary policy rate and UBA Plc. ROA. The analysis further showed negative and statistically insignificant relationships between cash reserve requirement, liquidity ratio and ROA. A probable cause for a statistically insignificant relationship is commercial banks’ low rate of compliance with the Central Bank of Nigeria’s monetary policies.

Have highlighted the monetary transmission, which helps to maintain inflation and growth Acharya (2017). The study briefed about the data which says that the pass-through from policy rate changes to bank lending rates has been slow and muted. This lack of adequate monetary transmission remains a key policy concern for the Reserve Bank as it blunts the impact of its policy changes on economic activity and inflation.

The study has examined the effect of monetary policy regimes on the performance of commercial banks Ndubuaka Victor (2017). They divided the study as structural adjusted programme (SAP) period (1986–1999) and post-SAP period (2000–2013). They found in their research that, monetary policy rate during the SAP period did not have an impact on the TAV, DM, L&A and credit to the private sector whilst monetary policy rates during the post-SAP period has a significant impact on the TAV, DM, L&A and credit to the private sector, respectively.

The prime purpose of this study is to find the effects of monetary policy instruments on commercial banks turnover ratio in an attempt to find out the true nature and the extent to which monetary policy instruments have been successful in impacting on banking performance in Nigeria Onoh (2017). The research reveals that the tools of monetary policy are useful on bank performance, and it also says that if the instruments are jointly used then, the strategies will be helpful.

The study involves the analysis of standard and non-standard monetary policy the profitability of banks Carlo Altavilla (2018). In this study proprietary, as well as commercial data on individual euro area bank balance-sheets and market prices are used. The results of the study explains about that easing in monetary policy – decrease in short-term interest rates/a flattening of the yield curve – is not associated with lower banks’ profits once there is a control in the endogeneity of the policy measures to expected macroeconomic and financial conditions. The prolonged period of low policy rates has a negative impact on banks’ profits which, however, can be occurred after a long time period and is counterbalanced by improved macroeconomic conditions.

Onodugo (2018) paper examines the impact of the monetary policy regime on the performance of commercial banks in Nigeria. The study says that the policy system during the SAP period has no major effect on TAV, DM, L&A and Banks Credit. However, the policy regimes during the post-SAP period is having a substantial impact on TAV, DM, L&A and Banks Credit. The study concludes that monetary policy rates and also lending rates have a substantial and positive impact on the performance of Nigerian (deposit money) banks.

In this study, the generalised method of moments estimator is used to understand the relationship between monetary policy and the profitability of the banks in New Zealand Vijay Kumar (2020). The finding of the study explains that an increase in short-term rate leads to an increase in the banks profit. In addition, also an increase in long-term interest rates reduces the profitability of banks. The study used monetary policy variables, capital adequacy ratio, non-performing loan ratio and cost to income ratio as the determinants of the profitability of banks in New Zealand. The results says that only the capital adequacy ratio has a positive impact on the profitability of banks, whereas the non-performing loan ratio and cost to income ratio have a negative impact on the profitability of banks.

Research methodology

In this chapter, the research design and methodology adopted are outlined for the study. It includes research design, population and sample size of the study, data collection methods and data analysis of the study.

Research design

The design adopted in this study is descriptive and analytical research. Descriptive research design helps in collecting information about the current status of the phenomena to describe what exists in respect to variables. The study uses time-series data. Descriptive research design is used because it addresses the objectives of the study in investigating the relationship between the variables of the study. Correlation and regression analysis is used to determine the relationship between BR and the performance of public sector banks in India.

Population and sample of the study

The population of the study is all the commercial banks working in India which are again categorised into various forms such as public sector banks, private sector banks and nationalised banks. The sample chosen for this study is the public sector banks actively performing in India. As on date, there are 12 public sector banks actively working in India after mergers and acquisitions.

Data collection

The data necessary for the study was collected from secondary sources. The secondary data collected were used to identify the relationship between dependent and independent variables. The data collected for the study is for five years, i.e. from 2016–2020.

The secondary data were collected from the official website of the Reserve Bank of India, i.e. from DataBase of Indian Economy and the official sites of the selected banks’ balance sheet. Along with the above-said websites, moneycontrol.com and Center for Monitoring Indian Economy are also used.

To check whether the data collected is normally distributed or not, normality tests are done. Kolmogorov-Smirnov test and Shapiro-Wilk test are used to check the normality of the data collected.

Analytical model

The study uses a regression model to find the relative significance of each variable identified in the study. The coefficient of correlation (R) is used to determine the strength of the relation between the variables. The format of the model is as under:

Model

• TAV = α + β(BR) + €

• DM = α + β(BR) + €

• L&A = α + β(BR) + €

Whilst:

TAV = total asset value;

DM = deposit mobilisation;

L&A = loans and advances;

BR = bank rate;

α = intercept;

β = coefficient of the explanatory variable (slope); and

€ = error term in the model.

Data analysis

Normality test

Kolmogorov-Smirnov test.

The Komlogorov-Smirnov test explains about the normal distribution of the data collected. If the p-value is lesser than the the standard value i.e. 0.05 than there is no normal distribution amongst the data collected and if the p-value is greater than 0.05 (standard value) then it can be concluded that the data collected is normally distributed. The TAV has a p-value of 0.200 which is greater than 0.05 which explains that there is a normal distribution amongst the data collected. Also, DM, L&A and BR have a p-value of 0.200, 0.065 and 0.200, respectively, which are above the standard value of 0.05, and hence can be concluded that there is a normal distribution amongst the data collected.

Shapiro-Wilk test.

The Shapiro-Wilk test explains about the normality of the data. In this test, if the p-value is greater than the value 0.05, then we can consider that the data collected is normal and if the p-value is below 0.05, the data is significantly deviating from the normal distribution. In the above table, the p-value of TAV is 0.992 which is above the standard value of 0.05. So, it is clear that the data is normal. In the case of DM, L&A and BR also the p-values are 0.945, 0.081 and 0.780, respectively which explains that the values are above 0.05 (standard value), and hence it is concluded that the data collected are normal.

In data analysis, the collected data will be analysed and interpreted in line with the study which is to determine the impact of monetary policy (BR) on the financial performance of public sector banks in India.

The above table explains that the relation between the dependent and independent variable is strong and significant as R is 0.897 and R² is 0.803, i.e. 80.3%. The correlation is strong (significant) but negative. The BR has a negative coefficient (−0.36), and hence an increase in BR leads to a decrease in the DM of public sector banks. The relation is significant at the 5% probability level as evidenced by the student t-test. Also, p-value (0.039) < 0.05 (less than 0.05) shows the relationship is strong and significant at a 5% probability level. Hence, from this analysis, it can be concluded that BR during the selected period had a significant impact on the performance of public sector banks in India.

Table 3 explains that the relation between the dependent and independent variable is average (weak) as R is 0.598 and R² is 0.358, i.e. 35.8%. The correlation is strong (significant) but negative. The BR has a negative coefficient (−0.019), and hence an increase in BR leads to a decrease in the L&A of public sector banks. The relationship is not significant at the 5% probability level as evidenced by the student t-test. Also, p-value (0.287) > 0.05 (greater than 0.05) shows the relationship is weak and not significant at a 5% probability level. Hence, from this analysis, it can be concluded that BR during the selected period had no significant impact on the performance of public sector banks in India.

Table 4 explains that the relation between the dependent and independent variable is strong and significant as R is 0.930 and R² is 0.865, i.e. 86.5%. The correlation is strong (significant) but negative. The BR has a negative coefficient (−0.36), and hence an increase in BR leads to a decrease in TAV of public sector banks. The relation is significant at the 5% probability level as evidenced by the student t-test. Also, p-value (0.022) < 0.05 (less than 0.05) shows the relationship strong and significant at a 5% probability level. Hence, from this analysis, it can be concluded that BR during the selected period had a significant impact on the performance of public sector banks in India.

Interpretation

The impact on the performance of the public sector banks as and when there is a change in BR is analysed. Before analyzing the impact, normality tests were tested using Kosmogorov-Smirnov normality test and Shapirowilk normality test. Both the tests explained that there exists a normal distribution amongst all the variables selected in this study.

Table 2 clearly explains that there is a significant impact of BR on the DM of the public sector banks in India, and there is a negative correlation between DM and the BR. The above-made analysis also said that there is no significant relationship between the L&A of public sector banks and the BR. Even the correlation was average or standard, but R² was weak. BR will slightly impact the L&A of the public sector banks. Table 4 also describes that there is a significant and robust relationship between the BR and TAV of the public sector banks in India. The correlation was strong but negative, and the relation between the variables was significant. Hence, from the overall analysis, it can be concluded that the BR has a substantial impact on the performance of the public sector banks in India by taking the factors like DM, L&A and TAV.

Conclusion

The BR, considering the crucial monetary policy rate, has a significant impact on the performance of public sector banks in India for five years (2016–2020). The performance is measured by taking three factors, and they are deposits, L&A and TAV of the banks. All three factors showed that there is an effect of BR on them during these five years. L&A affected the least amongst the three factors, but the other two (TAV and DM) were significantly impacted by the change in BR by the Reserve Bank of India. So, there should be a favourable fluctuation in the BR which will bring flexibility in the banking system, and they can perform well in the economy and the central bank also can concentrate on the macro-economic situation in the country.

Recommendations

Based on the findings and conclusion of the study, the recommendations are put forward. Primarily, the monetary policy rates alone as an instrument will not be effective in generating and simulating the economic activity level desired in the banking sector. Proper planning and timing are very much effective in framing the policies based on the economic conditions in the economy. Apart from qualitative tools, there are qualitative tools which also helps in regulating the flow/fluctuation of money supply and inflation in the economy, hence, that should not be neglected. The combination of both quantitative, as well as qualitative tools will give positive results to the banks and to the economy at large. The policymakers (monetary policy committee) should govern the monetary tools to ensure that they are effective in producing and stimulating the level of economic activities desired in the banking sector. At last political intervention in the banking sector is unfavourable to the growth and well-being of the banking sector, hence, should be minimised.

Suggestion for further research

The study still has a wide gap to be filled. There are various factors which represent the credit and financial performance of public sector banks, which are other than the selected variables in this study. The duration of the study can also be extended as per the requirement of the study. Also, one can study the effectiveness of the monetary policy on the entire commercial banks in the economy and also can go for nationalised banks, private sector banks, Microfinance banks and Regional Rural Banks in India. Even one can take more policy rates such as marginal standing facility and repo rate for identifying better impact of policy rates on banks performance in India.

Table 1.

Showing the normality of the data

Tests of normality
	Kolmogorov-Smirnov			Shapiro-Wilk
	Statistic	Df	Sig.	Statistic	df	Sig.
TAV	0.154	5	0.200	0.994	5	0.992
DM	0.177	5	0.200	0.982	5	0.945
L&A	0.337	5	0.065	0.800	5	0.081
BR	0.179	5	0.200	0.956	5	0.780

Table 2.

Showing the regression analysis between BR and DM of public sector banks during the period from 2016–2020

Coefficienta
Model	Unstandardised coefficients B Sth error		Standardised coefficients Beta	t	Sig.	R	R2
(Constant)	5.977	0.072		82.926	0.000	0.897	0.803
BR	−0.36	0.010	−0.897	−3.523	0.039

Note:

^aDependent variable: DM

Table 3.

Showing the regression analysis between BR and L&A of public sector banks during the period from 2016–2020

Coefficienta
Model	Unstandardised coefficients B Sth error		Standardised coefficients Beta	t	Sig.	R	R2
(Constant)	5.714	0.102		55.975	0.000	0.598	0.358
BR	−0.019	0.015	−0.598	−1.292	0.287

Note:

^aDependent variable: L&A

Table 4.

Showing the regression analysis between BR and TAV of public sector banks during the period from 2016–2020

Coefficienta
Model	Unstandardised coefficients B Sth error		Standardised coefficients Beta	t	Sig.	R	R2
(Constant)	6.080	0.060		102.104	0.000	0.930	0.865
BR	−0.038	0.009	−0.930	−4.390	0.022

Note:

^aDependent variable: TAV