Lecturer, Northern University, Nowshera. Ph.D Scholar, Qurtuba University, Peshawar.

Transcription

1 City University Research Journal Volume 07 Number 02 July 2017 PP Lecturer, Northern University, Nowshera. Ph.D Scholar, Qurtuba University, Peshawar. C 2017 CURJ, CUSIT 317

2 Arif Hussain et al. 318 C 2017 CURJ, CUSIT

3 Risk Taking Behavior of Commercial Banks in Pakistan Independent Variables Bank Risk Dependent Variable St N ) 319

4 Arif Hussain et al. SDNPL = Standard deviation of ratio of loan loss provision to total loans. SDROE = Standard deviation of return on equity SDROA = Standard deviation of return on assets. Operational Definition and Measurement of Variables Dependent Variable Return on Assets (ROA) = Return on asset is the ratio between net profit and total assets of the firm. It shows operating efficiency of assets to generate profits. Independent Variables Standard Deviation of ROE = Standard deviation of return on equity (SDROE) is a proxy for bank risk. It is measured as standard deviation of each bank ROE based on ten years annual data. This measure is also used by Tandelilin et al (2007) and Cebenoyan and Strahan (2004) as a measure for risk management in banks. Standard Deviation of ROA = Standard deviation of return on assets (SDROA) is used as a second proxy for bankrisk. It is measured as standard deviation of each bank ROA based on ten years annual data. This measure is also used by Tandelilin et al (2007) and Cebenoyan and Strahan (2004) as a measure for risk management in banks. Standard Deviation of Non-Performing Loans = Standard deviation of non performing loans (SDNPL) is used as a third proxy bank risk.it is measured asstandard deviation of loan loss provision for loans to total loan ratio based on ten years annual data. This measure is also used by Tandelilin et al (2007) and Cebenoyan and Strahan (2004) as a measure for risk management in banks. RESEARCH METHODOLOGY This study empirically tests risk taking behavior on the performance of commercial banks in Pakistan.Secondary data was collected from the published annual reports of five large commercial banks and ten small commercial banks for a period of 2005 to Banks having more than one thousand branches were considered as large commercial banks and banks having less than one thousand branches were considered as small commercial banks. There are a total of five public sector commercial banks and twenty two private sector commercial banks registered in Pakistan. List of these banks along with their number of branches is given in appendix I. Only five commercial banks including Habib Bank Limited (HBL), United Bank Limited (UBL), National bank of Pakistan (NBP), Muslim Commercial bank (MCB) and Allied bank Limited (ABL) have more than one thousand branches and have 54.4% of the total market share.so total population based sampling technique applied for the large banks as all these banks have more than one thousand branches and included all in the data analysis.however, for the small banks random sampling technique applied as all these banks have less than one thousands branches across the country.the remaining twenty two commercial banks have less than one thousand branches. Ten commercial banks were randomly selected having less than one thousand branches. Descriptive statistics and random effect OLS regression was used for the analysis of panel data alsoindependent Sample T-Test was used for making comparison of risk taking behavior between large commercial banks and small commercial banks in Pakistan. 320

5 Multicoliniarity Test Table Multicolinearity Statistics DATA ANALYSIS The above table shows the muilticoleanarity analysis of the independent variables of this research study. The results of this study show the values tolerance and VIF within feasible ranges as per the suggestions of (O?Brien& Robert, 2007). The above tolerance values reflect that the tolerance level is moderate and good and the VIF values also showing within the feasible ranges Table1: Multicoliniarity Test Variables ROA SDSP SDROA SDNPL Table 1 shows result of multicolliniarity test. Multicolliniority shows the extreme correlation with in the independent variables of the study. According to Gujarati (2003) if the correlation with in independent variables is more than 0.8, then there will be problem of multicolliniarity in the data. As all the correlations with independent variables are less than 0.8 so there is no problem of multicolliniarity. Breusch-Pagan Test Table 2: Beusch-Pagan test Test type Critical/Standard value Reported value Table 2 shows result of Breuch-Pagan test to estimate the problem of heteroscedasticity in the data. The reported values are above than the critical value, so the data is not showing any problem of non constant variation. Hence there is no problem of heteroscedasticity in the data. DESCRIPTIVE STATISTICS Table 3 Descriptive Statistics for Large Banks and Small Banks Colinearity Statistics Tolerance VIF SDROA SDSP SDNPL ROA 1.00 SDSP Risk Taking Behavior of Commercial Banks in Pakistan SDROA SDNPL Breusch-Pagan Test

6 Arif Hussain et al. Small Banks Large Banks Variables Comments SD M SD M ROA Large banks have higher ROA SDROA Large banks have lower risk SDROE Large banks have lower risk SDNPL Large banks have lower risk Table 3 shows descriptive statistics for small commercial banks and large commercial banks. Relative comparisons of the mean values for the risk variables of SDROA, SDROE and SDNPL show that large banks have lower mean values for all the risk variables than small banks. This suggests that large banks in Pakistan assume lower risk as compared to small banks in Pakistan. The return on assets for large banks is higher than the small banks. Table 4: Summary of Independent Samples T-Tests Variables Hypothesis Decision Comment s SDROA SDROE SDNPL H3: Large commercial banks have lower risk H3: Large commercial banks have lower risk H3: Large commercial banks have lower risk Supported Supported Supported Differences and Reject H0 If sig < 0.05 then Differences and Reject H0 Differences and Reject H0 Standard Deviation of ROE (SDROE): As the probability value 0.023<0.005, we reject the null hypothesis and hence it can be inferred that based on the analysis there are significant differences between large banks and small banks SDROE. So it is concluded that large banks have lower risk. Standard Deviation of Stock Prices (SDNPL): As the probability value 0.00<0.005, we reject the null hypothesis and hence it can be inferred that based on the analysis there are significant differences between large bank and small bank SDNPL. So it is concluded that large banks have lower risk. Standard Deviation of ROA (SDROA): As the probability value 0.007<0.005, we reject the null hypothesis and hence it can be inferred that based on the analysis there are significant differences between large banks and small banks SDROA. So it is concluded that large banks has lower risk. Hausman Test The Hausman test statistic was used in order to choose between random effect and fixed effectmodel for models. The null hypothesis of the Hausman test was that the random effects model was preferred to the fixed effects model. Hausman test reported a chisquare of with a probability value of 0.906shows that the chi-square value obtained was statistically insignificant. The null hypothesis was therefore failed to reject, so random effect model was recommended. 322

7 Risk Taking Behavior of Commercial Banks in Pakistan Large Banks Small Banks Variable Standard Error T-Values Standar s s d Error T-Values SDROE (0.042) (0.026) SDROA (0.024) (0.076) SDNPL (0.013) (0.928) R-Square = 35.7% R-Square = 23.6% Wald Chi = Wald Chi =

8 Arif Hussain et al. 324

9 Risk Taking Behavior of Commercial Banks in Pakistan S/No Large Commercial Banks 1 NationalBank of Pakistan Branches Market Share 4 Allied Bank Limited % Bank of Punjab 405 4% 5 Muslim Commercial % Bank Al Habib Ltd Bank Limited 6 Meezan Bank Limited % 7 Habib Metropolitan Source: State Bank of Pakistan (SBP) website. Bank Ltd. 8 Standard Chartered Bank (Pakistan) Ltd % % 9 NIB Bank Ltd % 10 Soneri Bank Ltd % 11 Summit Bank Ltd % 12 Silkbank Ltd % 13 Dubai Islami Bank Pakistan Ltd. 14 JS Bank Ltd Al Baraka Bank (Pakistan) Ltd. 16 Bank Islami Pakistan Ltd % 1.2% 121 1% % 17 The Bank of Khyber % 18 Sindh bank % 19 Samba Bank Ltd % 20 First Women bank % 22 Burj Bank Ltd % 22 MCB Islamic Bank Ltd. Small Commercial Banks Branches Market Share % Bank Alfalah Limited % 2 Habib Bank Limited % Faysal Bank Limited 3 United Bank Limited % Askari Bank Ltd % % 325