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\title{Determinants of Financial Performance of Commercial Banks in Bangladesh: An Empirical Study on Private Commercial Banks}
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             \author[1]{Nilanjan Kumar  Saha}

             \author[2]{Prodip Chandra  Bishwas}

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\date{\small \em Received: 6 June 2021 Accepted: 2 July 2021 Published: 15 July 2021}

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\begin{abstract}
        


The banking sector is one of the most important financial sectors of an economy and they play a vital role to strengthen the whole economy and its growth. The regulation of banking in developing countries has increasingly focused on attaining financial stability and soundness. The study focused on the determinants of the financial performance of the private commercial banks in Bangladesh.

\end{abstract}


\keywords{financial stability; financial performance; assets utilization; ROA; ROE; ROCE; NIM.}

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\let\tabcellsep& 	 	 		 
\section[{Introduction}]{Introduction}\par
he banking sector is one of the most significant financial sectors of an economy and they play an indispensable role to strengthen the whole economy and its growth. Economic growth is one of the final goals of any economic system and the development of the financial sector accelerates economic growth \hyperref[b23]{(Petkovski and Kjosevski, 2014)}. This sector is also a very important sector for a country as it helps to formulate capital and accelerate the investment, create the medium of exchange, help in export and import, control the credit, promote industrial development and also implement the monetary policy of the government. Therefore, the stability and the solvency of the bank have to be checked so that it can earn enough profit to survive in the long run. Banking sector stability appears to be an important driver of GDP growth and a stable banking sector reduces real output growth uncertainty \hyperref[b13]{(Jokipii and Monnin, 2013)}. The financial sector of Bangladesh constitutes banks, nonbank financial institutions (NBFIs), and insurance companies. Among them, the banking sector is the prime one. The banking sector of Bangladesh is growing day by day and it constitutes the core position in the country's financial sector. Therefore, it is very important to check the determinants of the financial performance of this sector as the financial performance is the main concern that is needed to run this sector smoothly. The bankers' committee of Bangladesh Bank fixes the planned allocation of resources among sectors and regions to attain balanced local sector development \hyperref[b14]{(Kamal, 2006)}. 
\section[{II.}]{II.} 
\section[{Literature Review}]{Literature Review}\par
The financial sector of a country especially Banks and Non-Bank Financial Institutions (NBFIs) plays a very vital role in an economy. It helps to mobilize more savings, create a strong flow of funds, and a better productive expenditure in the economy of a country. The sectorial extension rate of Gross Domestic Product (GDP) in the financial sector for the financial year 2016-2017 and 2017-2018 was 3.91 percent and 3.93 percent respectively (Bangladesh Bureau of Statistics, 2019). As this sector has a great impact on the economy of Bangladesh, the financial performance of this sector has received a lot of attention in recent years. According to \hyperref[b30]{(Teshome, Debela, and Sultan, 2018)}, Capital Adequacy H 1 : Bank Size has a positive and significant relationship with the banks financial performance.\par
According to Udom and Onyekachi R. (2018) capital adequacy strongly and actively incite, promote, and grow the financial performance of commercial banks and that adequacy of capital and adequate management can interpret to improved performance. There is a positive and significant relationship between Capital Adequacy and Financial Performance \hyperref[b4]{(Amahalu and et al., 2017;}\hyperref[b0]{Adekunle Muraina, 2018)}.). They also recommend that banks should avoid overreliance on debt, as an increase in the proportion of debt in the capital structure increases the financial risk and the risk of financial distress and bankruptcy. In contrast, according to  {\ref Çekrezi and et al. (2015)} capital adequacy has a negative influence on the bank's financial performance. 
\section[{H 2 : Capital Adequacy has a positive and significant relation with the banks financial performance}]{H 2 : Capital Adequacy has a positive and significant relation with the banks financial performance}\par
A study on Kenyan bank revealed that there is a negative relationship of banks profitability with liquidity while capital adequacy ratio, assets quality, and management efficiency directly affect the bank's financial performance (Kamande, Zablon and Ariemba, 2016). Another study done by Ongore and Kusa (2013) stated that the financial performance of commercial banks in Kenya is motivated mainly by board and management decisions. A paper done by Frederick, (2014) showed that Management efficiency, operating expenses, capital adequacy, interest income, and inflation are significant factors affecting the performance of domestic commercial banks in Uganda. Another paper based on Bangladeshi commercial banks has done by \hyperref[b33]{Yesmine and Bhuiyah (2015)} scrutinized that asset utilization and operating efficiency have a significant positive impact on the bank's financial performance. Another study had done on the Tunisian banking sector found that bank performance is positively correlated to capitalization, privatization, and quotation while bank size, concentration index, and efficiency are negatively related (Nouaili, Abaoub and Ochi, 2015; Bayoud, Sifouh and Chemlal, 2018). A study done on Kenyan banks suggested that commercial banks needed to embrace financial management practices in order to achieve targeted financial performance \hyperref[b18]{(Mujuka, 2018)}. H 3 : Management Efficiency has a positive and significant relation with the banks financial performance.\par
The leverage ratio evaluates a company's debt level and it has an impact on the bank's financial performance. A study done on Indian commercial banks (Al-Homaidi et al., 2018) revealed that leverage ratio is a highly significant variable of profitability in the context of Indian commercial banks. According to Pradhan and Khadka (2017) banks' profitability is negatively related to the leverage ratio. 
\section[{H 4 : Leverage ratio has a positive and significant relation with the banks financial performance.}]{H 4 : Leverage ratio has a positive and significant relation with the banks financial performance.}\par
A nonperforming loan (NPL) is a sum of obtained money upon which the borrower has not made the programmed payments for an itemized time. Kingu, Macha and Gwahula (2018) discovered that the appearance of non-performing loans is negatively linked with the level of profitability in commercial banks in Tanzania. It is also found that there is a negative relationship between non-performing loans and the bank's financial performance \hyperref[b1]{(Akter and Roy, 2017)}. 
\section[{H 5 : Non-performing loan ratio has a negative and significant relation with the banks financial performance.}]{H 5 : Non-performing loan ratio has a negative and significant relation with the banks financial performance.}\par
Loan loss provision is a set of expenses that has to be stored as an allowance for the uncollected loans and loan payments. This provision is often used for potential losses arising from bad debts, customer defaults, and renegotiated of a term loan. Holding less loan loss provision and tremendous profitability moreover, bank deposits, and its advances also play an important role in the durability and profitability of banks \hyperref[b29]{(Tahir, Ahmad and Aziz, 2014)}. Many studies show that there is a negative impact of loan loss provision on the bank's financial performance (Alhadab and Alsahawneh, 2016; Mustafa, Ansari and Younis, 2012).\par
of Sri Lanka \hyperref[b28]{(Swarnapali, 2014)}. \hyperref[b9]{Chouikh and Blagui (2017)}; \hyperref[b26]{(Sufian and Chong, 2008)} examined the determinants of bank's performance on Tunisian banks and found that there is a significant and negative relationship between bank's financial performance and board size of banks while other variables like privatization, capital-to-assets ratios, and macroeconomic variables.  {\ref Rekik and Kalai (2017)} analyzed the determinants of bank profitability and efficiency in conventional banks. They found that cost efficiency has little impact on profitability and profit efficiency. They also found that almost all the banks are below the optimal size. leverage ratio to enhance their profitability. In contrast, it is also found that both inner and outer factors have a powerful influence on the profitability \hyperref[b12]{(Gul, Irshad and Zaman, 2011)}.\par
Research run on Sri Lankan Licensed Commercial Banks (LCBs) explored that banks performance in Sri Lanka only affected by the operating expenses and bank size while credit ratio, liquidity ratio, and capital strength ratio are not statistically significant and do not contribute towards the performance of LCBs Loans (NPLs), Loan Loss Provision (LLP), Leverage Ratio (LR) have a negative and statistically significant influence. They suggested that Ethiopian banks should manage their loan, be cost-efficient, and fix their H 6 : Loan loss provision ratio has a negative and significant relation with the banks financial performance.\par
H 7 : GDP has a negative and insignificant relationship with the banks financial performance. H 8 : Inflation has a negative and insignificant relationship with the banks financial performance.\par
Sufian and Habibullah (2009) investigate the performance of 37 Bangladeshi commercial banks between 1997 and 2004. Their conclusions recommended that bank-specific characteristics, in special loan intensity, credit risk, and cost have positive and significant influences on bank performance, while non-interest income displays a negative relationship with bank profitability. Their study also found that the impact of size is not uniform across the various measures employed and macroeconomic indicators have no significant influence on bank profitability except inflation. 
\section[{III.}]{III.} 
\section[{Methodology a) Research Design}]{Methodology a) Research Design}\par
This study is based on secondary data retrieved from the published financial statements of the sampled private commercial banks of Bangladesh listed in the Dhaka Stock Exchange (DSE) from the year 2008 to 2017. The study uses a panel data regression model because of its advantages. Panel data discuss the behavior of each bank over time and across space. 
\section[{b) Sample of the Study}]{b) Sample of the Study}\par
In Bangladesh, 57 scheduled banks are comprising 4 state-owned banks, 39 privately-owned banks, 9 foreign banks, and 5 are specialized banks.   
\section[{d) Model Specification}]{d) Model Specification}\par
The following models are developed based on the variable of the study:ROA it = ? + ? 1 CAR it + ? 2 Size it + ? 3 LR it + ? 4 LLP it + ? 5 MER it + ? 6 NPLs it + ? 7 GPD it + ? 8 IR it + ? it ??. . (1) ROE it = ? + ? 1 CAR it + ? 2 Size it + ? 3 LR it + ? 4 LLP it + ? 5 MER it + ? 6 NPLs it + ? 7 GPD it + ? 8 IR it + ? it ??.\par
. (  {\ref 2})ROCE it = ? + ? 1 CAR it + ? 2 Size it + ? 3 LR it + ? 4 LLP it + ? 5 MER it + ? 6 NPLs it + ? 7 GPD it + ? 8 IR it + ? it ??. . (3) NIM it = ? + ? 1 CAR it + ? 2 Size it + ? 3 LR it + ? 4 LLP it + ? 5 MER it + ? 6 NPLs it + ? 7 GPD it + ? 8 IR it + ? it ??. .\textbf{(4)}\par
Where, ? ? = Interpret ? ROA it = 
\section[{Empirical Analysis and Results}]{Empirical Analysis and Results}\par
The study uses 10 years of data from the year 2008 to 2017 of 20 private commercial banks (PCBs) of Bangladesh. We run panel regression, Hausman test, and trend analysis to analyze the financial performance of PCBs of Bangladesh. 
\section[{a) Trend Analysis of Financial Performance of Private Commercial Banks in Bangladesh}]{a) Trend Analysis of Financial Performance of Private Commercial Banks in Bangladesh}\par
The following figure shows the trend of the financial performance of the private commercial banks in Bangladesh from the year 2008 to 2017 as expressed by average Return on Assets (ROA), Return on Equity (ROE), Return on Capital Employed (ROCE) and Net Interest Margin (NIM).   
\section[{b) Analysis of stata output}]{b) Analysis of stata output}\par
To analyze the hypotheses, a panel regression was run by the stata, a statistical data analysis software. The results of the analysis are discussed here. 
\section[{i. Results of Model 1}]{i. Results of Model 1}\par
The Hausman test for the first model as described by equation (1) (Table \hyperref[tab_6]{4}.1) that the p-value is equal to 0.5092. It follows that we do not reject the null hypothesis that there is no misspecification. As a result, the model 1 will be estimated using the Random Effect (RE) model. According to the model estimation output, all the independent variables in model 1 except inflation are statistically insignificant as that their p-values are greater than 5 percent. The interpret (The Constant) is also statistically not significant. Therefore, ROA as an indicator of bank performance is not statistically explained by the underlying determinants. However, some coefficient estimate signs are in line with the underlying hypotheses. Here, LLP, NPL, and GDP are not statistically significant, but their coefficient estimate signs are as predicted by the hypotheses.\par
The rejection, acceptance and partially acceptance of the hypotheses are recapitulated in Table \hyperref[tab_6]{4}  As shown in Table \hyperref[tab_6]{4}.5 below, the estimation of the underlying model 2 leads to the following results. 
\section[{Table 4.5: Model 2 Estimation using Fixed Effects}]{Table 4.5: Model 2 Estimation using Fixed Effects}\par
According to the model estimation output, all the independent variables in model 2 except CAR and MER are statistically significant as that their p-values are lower than 5 percent. The interpret (The Constant) is also statistically significant. Therefore, ROE as a proxy of bank performance is statistically explained by the underlying determinants. However, some coefficient estimate signs are in line with the underlying hypotheses. Here, H4, H5, and H6 are fully in line with the underlying hypotheses.\par
The rejection, acceptance and partially acceptance of the hypotheses are recapitulated in Table \hyperref[tab_6]{4}.6 Table \hyperref[tab_6]{4}.6: Summary of the hypotheses Acceptance or Rejection: Model 2 
\section[{d) Results of Model 3}]{d) Results of Model 3}\par
The Hausman test for the first model as described by equation (  {\ref 3}) shows (Table \hyperref[tab_6]{4}.7) that the pvalue is equal to 0.0082. It follows that we do reject the null hypothesis that there is misspecification. As a result, the model 3 will be estimated using the Fixed Effect (FE) model.  
\section[{c) Results of Model 2}]{c) Results of Model 2}\par
The Hausman test for the first model as described by equation (  {\ref 2}) shows (Table \hyperref[tab_6]{4}.4) that the pvalue is equal to 0.3863. It follows that we can't reject the null hypothesis that there is no misspecification. As a result, the model 2 will be estimated using the Random Effect (RE) model. Model 3 shows that all the independent variables except LLP, NPL, and inflation are statistically significant as that their p-values are lower than 5 percent. The interpret (The Constant) is also statistically significant. Therefore, ROCE as an indicator of bank performance is statistically explained by the underlying determinants. However, some coefficient estimate signs are in line with the underlying hypotheses. Here, all the determinants are partially confirmed by the model.\par
The rejection, acceptance and partially acceptance of the hypotheses are recapitulated in Table \hyperref[tab_6]{4}.9 Table \hyperref[tab_6]{4}.9: Summary of the hypotheses Acceptance or Rejection: Model 3 
\section[{e) Results of Model 4}]{e) Results of Model 4}\par
The Hausman test for the fourth model as described by equation ( \hyperref[formula_1]{4}) shows (Table \hyperref[tab_6]{4}.10) that the pvalue is equal to 0.9162. It follows that we do not reject the null hypothesis that there is no misspecification. As a result, the model 4 will be estimated using the Random Effect (RE) model. Amongst the four models, the first one is eliminated because it is statistically insignificant. The remaining models are model 2, model 3, and model 4, wherein, bank performance is measured by ROE, ROCE, and NIM respectively. Model 1 has an R 2 equal to 0.3554 which means 35.54 percent of the dependent variable is explained by the independent variables. Model 2 has an R 2 equal to 0.3621 which means 36.21 percent of the dependent variable is explained by the independent variables. Model 3 has an R 2 equal to 0.2991 which defines 29.91 percent of the dependent variable is explained by the independent variables. Model 4 has an R 2 equal to 0.1071 which means 10.71 percent of the dependent variable is explained by the independent variables. Therefore, Model 2, where ROE is the dependent variable has been chosen as it has the highest R 2 .\par
V. 
\section[{Findings of the Study}]{Findings of the Study}\par
The experimental findings from the analysis are disputed below: 1. The empirical findings of the study suggest that all the bank-specific determinants have a great influence on the financial performance of private commercial banks (PCBs) in Bangladesh.   
\section[{Recommendations}]{Recommendations}\par
The banking sector of Bangladesh is a growing sector and it plays an important role in the economic growth of Bangladesh. The following recommendations are based on the empirical findings of the study.\par
1. Banks should be more careful about ensuring high asset quality to achieve better financial performance. 2. Banks should concentrate on the management level of the banks as the better financial performance is related to a better management skill as described by the efficiency structure theory. 3. It is recommended to use an optimum level of debt for finance as it has a significant effect on the financial performance of private commercial banks in Bangladesh. 4. The authority should develop a better policy that leads the banking sector of Bangladesh to enhance the resilience, robustness, stability, and efficiency. A stable banking sector leads to a stable financial performance for the banks. 5. The authority of the respective banks should be careful about their capital including tier 1 capital and tier 2 capital as capital adequacy has a positive impact on the financial performance of the banks. 6. Banks should address more and more new products and services as it leads to profitable banking. It is also added that banks with relatively more advanced technologies achieve better financial performance over its peers. 7. Banks should emphasize finding a better way to obtain the optimal utilization of the resources 8. Banks can also ensure better financial performance by increasing the amount of non-interest income and bank size as bank size has a significant impact on the financial performance of the PCBs in Bangladesh.\par
VII. 
\section[{Conclusion}]{Conclusion}\par
The banking sector of Bangladesh is a growing financial sector of the country and it has a strong impact on the economy of Bangladesh. Banks also play a remarkable role in generating employment opportunities, enhancing financial resources, and the overall development of a country. Bank's financial performance is the result of the bank's internal roles, regulation, policies, activities, effectiveness, efficiency, and overall performance in the monetary terms. Banks are the most integral part of the financial sector of any country as they dominate the financial sector by contributing much to the economic growth of the country. The banking sector of Bangladesh is the largest sector of the financial sector of the country as there are 57 running commercial banks. It contributes to enlarge the industrial activities and investment activities. Therefore, this study focus on the determinants of the financial performance of private commercial banks in Bangladesh. It finds that leverage and capital adequacy has a positive influence on the financial performance of PCBs in Bangladesh. During the periods of the study, bank size has a significant influence on the financial performance of the banks. The concerned authority should develop strong and efficient rules, regulations, and policies for a better, stable, and efficient banking sector. Based on the above discussion it can be ended that private commercial banks of Bangladesh should focus on high asset quality, strong management, asset utilization, increased non-interest income, and efficient utilization of the operating expenses for their better financial performance, stability, and soundness. \begin{figure}[htbp]
\noindent\textbf{} \par 
\begin{longtable}{}
\end{longtable} \par
 
\caption{\label{tab_0}}\end{figure}
 \begin{figure}[htbp]
\noindent\textbf{31} \par 
\begin{longtable}{P{0.2283878504672897\textwidth}P{0.5789135514018692\textwidth}P{0.04269859813084112\textwidth}}
Dependent Variables\tabcellsep Measurement\tabcellsep Notation\\
1. Return on Equity\tabcellsep ?????? ???????????? ?????????? ???????????????????? ? ?? ????????????\tabcellsep ROE\\
2. Return on Assets\tabcellsep ?????? ???????????? ?????????? ????????????\tabcellsep ROA\\
3. Net Interest Margin\tabcellsep ???????????????? ???????????? ? ???????????????? ???????????????? ?????????? ????????????\tabcellsep NIM\\
4. Return on Capital Employed\tabcellsep ?????????????? ???????????? ???????????????? ?????? ?????????? ???????????????????? ? ?? ???????????? + ???????? ???????? ??????????\tabcellsep ROCE\\
Independent Variables\tabcellsep Measurement\tabcellsep Notation\\
1. Bank Size (Total Assets)\tabcellsep Total Assets\tabcellsep Size\\
2. Non-Performing Loan Ratio\tabcellsep ?????????? ?????????? ? ???????????????????? ?????????? ?????????? ??????????\tabcellsep NPLs\\
3. Loan Loss Provision Ratio 4. Leverage Ratio\tabcellsep ?????????? ???????? ???????? ?????????????????? ?????????? ?????????? ?????????? ???????? ?????????? ???????????????????? ? ?? ????????????\tabcellsep LLP LR\end{longtable} \par
  {\small\itshape [Note: 5. Capital Adequacy Ratio???????? ?? ?????????????? + ???????? ???? ?????????????? ?????????? ???????? ??????????????? ???????????? CAR]} 
\caption{\label{tab_1}Table 3 . 1 :}\end{figure}
 \begin{figure}[htbp]
\noindent\textbf{} \par 
\begin{longtable}{}
\end{longtable} \par
  {\small\itshape [Note: it = Leverage Ratio of bank i at time t ? LLP it = Loan Loss Provision Ratio of bank i at time t ? MER it = Management Efficiency Ratio of bank i at time t ? NPLs it = Non-performing Loan Ratio of bank i at time t ? GPD it = Gross Domestic Product (GDP) at time t ? IR it = Inflation rate at time t ? ? it = Error term IV.]} 
\caption{\label{tab_2}}\end{figure}
 \begin{figure}[htbp]
\noindent\textbf{41} \par 
\begin{longtable}{P{0.1435064935064935\textwidth}P{0.31277056277056275\textwidth}P{0.15454545454545454\textwidth}P{0.02207792207792208\textwidth}P{0.0975108225108225\textwidth}P{0.11958874458874459\textwidth}}
\tabcellsep \multicolumn{3}{l}{Hausman test for Model 1}\tabcellsep \\
Test Summary\tabcellsep \multicolumn{2}{l}{Chi-Sq. Statistic}\tabcellsep \multicolumn{2}{l}{Chi-Sq. d.f}\tabcellsep P-value\\
Cross-section random\tabcellsep 6.26\tabcellsep \tabcellsep 7\tabcellsep \tabcellsep 0.5092\\
\tabcellsep \multicolumn{4}{l}{Model 1 Estimation using RE}\\
Variable\tabcellsep Coefficient estimate\tabcellsep \multicolumn{2}{l}{Standard error}\tabcellsep z-statistic\tabcellsep P-value\\
Constant\tabcellsep .4766875\tabcellsep .5894122\tabcellsep \tabcellsep 0.81\tabcellsep 0.419\\
LLP\tabcellsep -.0345634\tabcellsep .0238477\tabcellsep \tabcellsep -1.45\tabcellsep 0.147\\
CAR\tabcellsep .0276288\tabcellsep .024352\tabcellsep \tabcellsep 1.13\tabcellsep 0.257\\
NPL\tabcellsep -.0038738\tabcellsep .0088307\tabcellsep \tabcellsep -0.44\tabcellsep 0.661\\
SIZE\tabcellsep -6.19e-07\tabcellsep 3.87e-07\tabcellsep \tabcellsep -1.60\tabcellsep 0.110\\
MER\tabcellsep -.0005846\tabcellsep .0005551\tabcellsep \tabcellsep -1.05\tabcellsep 0.292\\
LR\tabcellsep -.0001667\tabcellsep .000095\tabcellsep \tabcellsep -1.75\tabcellsep 0.080\\
Inflation\tabcellsep .1410019\tabcellsep .0208599\tabcellsep \tabcellsep 6.76\tabcellsep 0.000\\
GDP\tabcellsep -.0120971\tabcellsep .0701581\tabcellsep \tabcellsep -0.17\tabcellsep 0.863\end{longtable} \par
 
\caption{\label{tab_4}Table 4 . 1 :}\end{figure}
 \begin{figure}[htbp]
\noindent\textbf{43} \par 
\begin{longtable}{P{0.059500000000000004\textwidth}P{0.312375\textwidth}P{0.142375\textwidth}P{0.33575\textwidth}}
\tabcellsep \tabcellsep .3\tabcellsep \\
\tabcellsep \multicolumn{3}{l}{Summary of the hypotheses Acceptance or Rejection: Model 1}\\
Determinants\tabcellsep Statistical significance\tabcellsep Coefficient estimate sign\tabcellsep Hypothesis confirmed, partially confirmed, or rejected\\
LLP\tabcellsep Insignificant\tabcellsep Negative\tabcellsep H 6 partially confirmed.\\
CAR\tabcellsep Insignificant\tabcellsep Positive\tabcellsep H 2 partially confirmed.\\
NPL\tabcellsep Insignificant\tabcellsep Negative\tabcellsep H 5 partially confirmed.\\
SIZE\tabcellsep Insignificant\tabcellsep Negative\tabcellsep H 1 is rejected.\\
MER\tabcellsep Insignificant\tabcellsep Negative\tabcellsep H 3 is rejected.\end{longtable} \par
  {\small\itshape [Note: C]} 
\caption{\label{tab_5}Table 4 . 3 :}\end{figure}
 \begin{figure}[htbp]
\noindent\textbf{4} \par 
\begin{longtable}{P{0.7691371681415929\textwidth}P{0.08086283185840708\textwidth}}
The above figure 4.1 has shown an erratic trend\tabcellsep NIM show that it is profitable to invest in the private\\
of the financial performance of the private commercial\tabcellsep commercial banks in Bangladesh.\\
banks in Bangladesh. It shows that among the\tabcellsep \\
performance indicators Net Interest Margin (NIM) shows\tabcellsep \\
consistent performance over the period. The average\tabcellsep \\
NIM is almost the same in all the year. Return on Assets\tabcellsep \\
(ROA) also shows a consistent performance of the\tabcellsep \\
banks. On the other hand, Return on Equity (ROE) and\tabcellsep \\
Return on Capital Employed (ROCE) are in a declining\tabcellsep \\
position over the years. The ROE and ROCE were 16.06\tabcellsep \\
percent and 31.19 percent in the year 2008 respectively\tabcellsep \\
and they declined at 11.32 percent and10.73 percent\tabcellsep \\
respectively in the year 2017. This is happened because\tabcellsep \\
of an increase in the amount of total shareholder's\tabcellsep \\
equity and total long term debts of the banks. ROA and\tabcellsep \\
\multicolumn{2}{l}{2: Model 1 Estimation using Random Effects}\end{longtable} \par
 
\caption{\label{tab_6}Table 4 .}\end{figure}
 \begin{figure}[htbp]
\noindent\textbf{44} \par 
\begin{longtable}{}
\end{longtable} \par
 
\caption{\label{tab_7}Table 4 . 4 :}\end{figure}
 \begin{figure}[htbp]
\noindent\textbf{} \par 
\begin{longtable}{P{0.08551160791057609\textwidth}P{0.42536543422184003\textwidth}P{0.13886500429922613\textwidth}P{0.07454858125537403\textwidth}P{0.008770421324161651\textwidth}P{0.06285468615649183\textwidth}P{0.054084264832330184\textwidth}}
\tabcellsep \tabcellsep \multicolumn{3}{l}{Hausman test for Model 2}\tabcellsep \\
\tabcellsep Test Summary\tabcellsep \multicolumn{2}{l}{Chi-Sq. Statistic}\tabcellsep \multicolumn{2}{l}{Chi-Sq. d.f}\tabcellsep P-value\\
Year 2021\tabcellsep Cross-section random\tabcellsep 7.42\tabcellsep \tabcellsep 7\tabcellsep \tabcellsep 0.3863\\
28\tabcellsep \tabcellsep \multicolumn{4}{l}{Model 2 Estimation using RE}\\
Volume XXI Issue II Version I\tabcellsep Variable Constant LLP CAR NPL SIZE MER LR Inflation GDP\tabcellsep Coefficient estimate 22.78143 -.7137877 -.1686205 -.1966541 -.0000108 -.0078263 .0025548 1.091984 -1.725821\tabcellsep \multicolumn{2}{l}{Standard error 5.842831 .2407248 .2410095 .0966913 4.09e-06 .0056661 .0009634 .2028876 .697543}\tabcellsep t-statistic 3.90 -2.97 -0.70 -2.03 -2.63 -1.38 2.65 5.38 -2.47\tabcellsep P-value 0.000 0.003 0.484 0.042 0.009 0.167 0.008 0.000 0.013\\
( ) C\tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \\
Global Journal of Management and Business Research\tabcellsep \multicolumn{6}{l}{Summary of the hypotheses Acceptance or Rejection: Model 2 Determinants Statistical significance Coefficient estimate sign Hypothesis confirmed, partially confirmed, or rejected LLP Significant Negative H 6 is confirmed. CAR Insignificant Negative H 2 is rejected. NPL Significant Negative H 5 is confirmed. SIZE Significant Negative H 1 partially confirmed. MER Insignificant Negative H 3 is rejected. LR Significant Positive H 4 is confirmed. Inflation Significant Positive H 8 is rejected.}\\
\tabcellsep GDP\tabcellsep Significant\tabcellsep Negative\tabcellsep \tabcellsep \multicolumn{2}{l}{H 7 partially confirmed.}\\
© 2021 Global Journals\tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \end{longtable} \par
 
\caption{\label{tab_8}}\end{figure}
 \begin{figure}[htbp]
\noindent\textbf{410} \par 
\begin{longtable}{P{0.85\textwidth}}
© 2021 Global Journals\end{longtable} \par
  {\small\itshape [Note: C]} 
\caption{\label{tab_10}Table 4 . 10 :}\end{figure}
 \begin{figure}[htbp]
\noindent\textbf{4} \par 
\begin{longtable}{P{0.85\textwidth}}
8: Model 3 Estimation using Fixed Effects\end{longtable} \par
 
\caption{\label{tab_11}Table 4 .}\end{figure}
 \begin{figure}[htbp]
\noindent\textbf{47} \par 
\begin{longtable}{P{0.2640776699029126\textwidth}P{0.3796116504854369\textwidth}P{0.09902912621359224\textwidth}P{0.10728155339805825\textwidth}}
\tabcellsep \multicolumn{2}{l}{Hausman test for Model 3}\tabcellsep \\
Test Summary\tabcellsep Chi-Sq. Statistic\tabcellsep Chi-Sq. d.f\tabcellsep P-value\\
Cross-section random\tabcellsep 19.00\tabcellsep 7\tabcellsep 0.0082\end{longtable} \par
 
\caption{\label{tab_12}Table 4 . 7 :}\end{figure}
 \begin{figure}[htbp]
\noindent\textbf{412} \par 
\begin{longtable}{P{0.11076487252124645\textwidth}P{0.2046742209631728\textwidth}P{0.08427762039660057\textwidth}P{0.2046742209631728\textwidth}P{0.12039660056657224\textwidth}P{0.12521246458923513\textwidth}}
\tabcellsep \tabcellsep \multicolumn{2}{l}{Model 4 Estimation using RE}\tabcellsep \tabcellsep \\
Variable\tabcellsep Coefficient\tabcellsep estimate\tabcellsep Standard error\tabcellsep z-statistic\tabcellsep P-value\\
Constant\tabcellsep \multicolumn{2}{l}{.4317311}\tabcellsep .9435643\tabcellsep 0.46\tabcellsep 0.647\\
LLP\tabcellsep \multicolumn{2}{l}{.1042474}\tabcellsep .208323\tabcellsep 2.65\tabcellsep 0.008\\
CAR\tabcellsep \multicolumn{2}{l}{.0121749}\tabcellsep .0376943\tabcellsep 0.32\tabcellsep 0.747\\
NPL\tabcellsep \multicolumn{2}{l}{-.040469}\tabcellsep .0205358\tabcellsep -1.97\tabcellsep 0.049\\
SIZE\tabcellsep \multicolumn{2}{l}{-9.71e -07}\tabcellsep 7.51e -07\tabcellsep -1.29\tabcellsep 0.196\\
MER\tabcellsep \multicolumn{2}{l}{-.0008081}\tabcellsep .0009497\tabcellsep -0.85\tabcellsep 0.395\\
LR\tabcellsep \multicolumn{2}{l}{.0005289}\tabcellsep .0001595\tabcellsep 3.32\tabcellsep 0.001\\
Inflation\tabcellsep \multicolumn{2}{l}{.0639343}\tabcellsep .0308005\tabcellsep 2.08\tabcellsep 0.038\\
GDP\tabcellsep \multicolumn{2}{l}{.208323}\tabcellsep .112287\tabcellsep 1.86\tabcellsep 0.064\end{longtable} \par
 
\caption{\label{tab_14}Table 4 . 12 :}\end{figure}
 \begin{figure}[htbp]
\noindent\textbf{4} \par 
\begin{longtable}{}
\end{longtable} \par
  {\small\itshape [Note: 11: Model 4 Estimation using Random Effects 8. Loan loss provision ratio has an insignificant and negative relation with ROA and ROCE but this VI.]} 
\caption{\label{tab_15}Table 4 .}\end{figure}
 		 		\backmatter   			 
\subsection[{Acknowledgement}]{Acknowledgement}\par
This study gives acknowledgement to a paper previously published titled "The Determinants of Bank Performance: The case of Tunisian Listed Banks" by Aziz et. al., (2017). 			  			  				\begin{bibitemlist}{1}
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\end{document}
