American Finance & Banking Review Vol. 6, No. 1; 2021 ISSN 2576-1226 E-ISSN 2576-1234 Published by CRIBFB, USA 26 RELATIVE STANDING OF ROE AND ROCE IN EFFECTIVE LIQUIDITY MANAGEMENT: EVIDENCE FROM BANGLADESHI COMMERCIAL BANKS Dr. Nazneen Jahan Chaudhury Associate Professor Department of Business Administration International Islamic University Chittagong, Chattogram, Bangladesh E-mail: nazneenchy@yahoo.com https://orcid.org/0000-0002-1172-3576 Received: September 23, 2021 Accepted: November 12, 2021 Online Published: November 27, 2021 DOI: 10.46281/amfbr.v6i1.1459 URL: https://doi.org/10.46281/amfbr.v6i1.1459 ABSTRACT This study has been designed for examining the effectiveness of liquidity management through the relative standing of ROE and ROCE of Nationalized Commercial Banks in Bangladesh for the duration of 2008–2018. Six NCBs are selected purposively as sample. The study relies on a balanced panel data set of 66 observations which are gathered from the annual reports of banks and analyzed by random effects regression model. However, the research only examined a few variables. The empirical results reveal that the selected NCBs have been portraying better standing in case of ROE than ROCE in effective liquidity management. The value of R2 of ROE is 75.25%; it signifies that the explanatory measures could clarify 75.25% of the variations in ROE. Among the liquidity measures, Assets/Shareholders Equity has highly significant negative effect; Tier 1 Capital/Risk Weighted Assets has highly significant positive effect; Deposits/Assets have some significant positive and Bank Size in terms of Deposits has some significant negative effect on ROE of the selected NCBs. Keywords: Bangladesh, Commercial Bank, Effective Liquidity Management, ROE, ROCE. JEL Classification Codes: E44, G14, G21, O16. PRELUDE Banking system is one of the major components of financial system for ensuring its continued existence. According to Wilner (2000), efficient banking system acts as a means for the accumulation of deposit funds and investing those funds in a productive manner. Without effective liquidity management, banks with intense foundation and bright future may not be profitable (Jose et al., 1996). Therefore liquidity management involves the strategic administration of inflows and outflows of banks’ funds that will concurrently maintain liquidity, profitability and solvency of banks. Agbada and Osuji (2013) articulated that with a view to achieving these conflicting objectives, liquidity management requires to be efficient in the https://orcid.org/0000-0002-1172-3576 https://www.cribfb.com/journal/index.php/amfbr American Finance & Banking Review Vol. 6, No. 1; 2021 27 circulation of liquidity compatible with a preferred level of cash without twisting the profitability and functions of the bank. Banking structure of Bangladesh Bangladesh has an assorted banking sector of 60 scheduled banks consisting of 06 Nationalized Commercial Banks, 03 Specialized Banks, 42 Private Commercial Banks and 09 Foreign Commercial Banks. Out of 42 Private Commercial Banks, 32 banks are interest based whereas 8 are interest free (www.bb.org.bd/fnansys/bankfi.php). LITERATURE REVIEW Basel Committee on Banking Supervision (2008) explained that bank’s sustainability is dependent on the liquidity position as it measures the role of bank in maintaining cash flow. According to Central Bank of Barbados (2008), liquidity problem may usually influence a bank’s profits and capital and exceptional circumstance, due to liquidity problem a solvent bank may become insolvent. Jenkinson (2008) found that liquidity problem simultaneously affects both the performance and reputation of a bank. According to Aspachs et al. (2005), banks can use three methods to indemnify against liquidity risks. Such as (i) seizing bumper of liquid assets (ii) relying on interbank market (iii) relying on central bank-a lender of last resort. Hirigoyen (1985) agreed that low liquidity leads to low profitability. Chandra (2001) claimed that usually high liquidity acts as a signal of financial strength. AssafNeto (2003) argued that both high and low liquidity are undesirable. According to Goddard et al. (2004), holding liquidity causes an opportunity cost and thereby having a negative consequence on profit making ability of banks. Gup and Kolari (2004) claimed that bank management should extend a liquidity plan that makes a balance between risks and returns. Koch (1992); Sufian and Chong (2008) believed that as maintenance of liquidity bears both risk and return, a trade-off between liquidity and profit base can minimize the conflict. Repullo (2003) found that liquidity management depends on hybrids of theories that are typically employed to obtain optimality. Considering Shiftability theory, Dodds (1982) suggested that assets must meet three conditions-“shiftability, marketability or transferability” in order to ensure convertibility of the assets. Based on Anticipated Income theory, Nzotta (1997) identified two fundamental factors-earning capability and creditworthiness of a borrower which can be regarded as the undertaking for assuring sufficient liquidity. According to Liability Management theory, Emmanuel (1997) suggested that the central bank or sister banks can come forward to lend money if other banks urgently require funds. He also propagated a very conservative outlook when he asserted that the banks do not lend money for long term, due to the long payback period. Hence Commercial Loan theory is only applicable for short period, self- liquidating loans. Agbada and Osuji (2013) experienced that the soundness of banks can be enhanced by efficient liquidity management. According to Kurawa and Abubakar (2014); Obida and Owolabi (2012), liquidity management measures the growth and financial performance of a bank. As per Nwankwo (1991), liquidity management requires assessing liquidity needs and meeting up those needs at all times without incurring any significant costs. It is asserted that adequate liquidity at normal market interest rate is crucial for both large and small banks to meet all types of liabilities. It is also said that adequate liquidity may help a bank to face three kinds of liquidity risks: (i) risk of funding (ii) default risk (iii) risk of failure to honor maturity obligations of customers. http://www.bb.org.bd/fnansys/bankfi.php https://www.cribfb.com/journal/index.php/amfbr American Finance & Banking Review Vol. 6, No. 1; 2021 28 According to Lartey et al. (2013), there is a very insignificant but positive association between optimum levels of liquidity and profit base. According to Osborne et al. (2012), the association between liquidity and profit base becomes more positive in the distress of banking sector. Arif and Anees (2012); Datta et al. (2011); Adebayo et al. (2011) observed that profit base is significantly influenced by liquidity in the form of deposits. Rauch et al. (2010) found that profit base is negatively associated with liquidity. Other things held constant, adequate liquidity can improve profit base of banks (Bernanke, 2008). Flannery and Rangan (2008) asserted that due to sudden shock or regulatory requirements, if liquidity of banks exceeds their optimum level reduces profit base only. Jahangir et al. (2007) argued that loan deposit ratio works as an important determinant of banks’ profitability. Hossain (2000) indicated that high percentage of fixed to total deposits influence the profitability performance of NCBs. Lucy et al. (2018) found that liquidity has significant positive effect on ROCE. Agbada and Osuji (2013) explored that adequate capital is a must for maximizing ROCE. Raza, Farhan, and Akram (2011) affirmed that ROCE is one of the major measures to measure profitability. Alshatti (2015) recommended that quick ratio and investment ratio are positively associated with ROE whereas capital ratio and liquid asset ratios are negatively associated with ROE. According to Bassey (2015), cash ratio, loan to deposit ratio, current ratio, loan to asset ratio and liquid ratio are significantly related with ROE. Olarewaju and Adeyemi (2015) stated that there is no causal relationship between loan deposit ratio and ROE. According to Abdullah and Jahan (2014), all other things held constant, the more liquid bank tends to have lower ROE. Tabari, Ahmadi, and Emami (2013) acknowledge that ROE is one of the substitutes to measure profit base of a bank. Ramadan et al. (2011) showed that there is an association between ROE and the efficacy of credit management. According to Ahmed et al. (2006), in order to fortify the economic conditions of a country, NCBs must improve their performance evaluation metrics such as NPL, ROA and ROE. Siddique (2004) recognized that NPL is one of the outcomes of poor bank fund management. In the above sections the researcher has conducted an extensive review of literatures over banks’ liquidity management nationally and internationally. It is found that maximum studies have been conducted over management of liquidity and banking performance, liquidity- profitability relationship, and role of liquidity on banks’ profitability. However, relative standing of profitability measures in effective liquidity management in Bangladesh remains an unexplored area. Hence, the present study has been carried out to evaluate the relative standing of ROE and ROCE of NCBs in efficient liquidity management. OBJECTIVES OF THE STUDY The key objective of this study is to analyze the relative prominence of ROE and ROCE in effective liquidity management of NCBs. This objective basically attempts:  To evaluate the descriptive features of both liquidity and profitability measures of respective banks;  To analyze the liquidity measures that influence both the ROE and ROCE;  To measure the association between liquidity measures and selected profitability measures;  To appraise the comparative position of ROE and ROCE in ensuring effective liquidity management of selected NCBs; https://www.cribfb.com/journal/index.php/amfbr American Finance & Banking Review Vol. 6, No. 1; 2021 29 THEORETICAL FRAMEWORK Independent Variables (Liquidity Indicators) Dependent Variables (Profitability indicators) Figure 1. Theoretical Framework METHODOLOGY OF THE STUDY Research Design The study is descriptive as well as analytical in nature. It is descriptive as it demonstrated the effectiveness of liquidity management of NCBs in Bangladesh through the measures of relative standing of its ROE and ROCE. This study is analytical in the sense that it carried out a panel data analysis for testing hypothesis and interpreting relationship by analyzing available information. Basically, the study intends to provide an appropriate strategy for the effective liquidity management of NCBs in Bangladesh. Hypotheses of the Study 𝐻01: There is no statistically significant relationship between liquidity and ROE of NCBs 𝐻11: There is a statistically significant relationship between liquidity and ROE of NCBs 𝐻02: There is no statistically significant relationship between liquidity and ROCE of NCBs Market rate of Interest TAs/SE T1C/RWA A LQA/TAs RRP/TLs ROE & ROCE LQAs/TDs BDO/TAs TDs/TAs NPL/GLA Bank Size https://www.cribfb.com/journal/index.php/amfbr American Finance & Banking Review Vol. 6, No. 1; 2021 30 𝐻12: There is a statistically significant relationship between liquidity and ROCE of NCBs Specification of the Model Model 1: ROE= A+ β1 (TAs/SE) + β2 (T1C/RWA) + β3 (LQA/TAs) + β4 (RRP/TLs) + β5 (LQA/TDs) + β6 (BDO/TAs) + β7 (TDs/TAs) + β8 (NPL/GLA) + β9 (MRI) + β10 (BSZ) + e Model 2: ROCE= A+ β1 (TAs/SE) + β2 (T1C/RWA) + β3 (LQA/TAs) + β4 (RRP/TLs) + β5 (LQA/TDs) + β6 (BDO/TAs) + β7 (TDs/TAs) + β8 (NPL/GLA) + β9 (MRI) + β10 (BSZ) + e Where, ROE and ROCE are the dependent variables, A is the constant term, β’s measures the coefficient of explanatory variables, variables in the parenthesis are the explanatory variables and ‘e’ denotes the stochastic disturbance term. Table 1. Elucidation of dependent and independent variables and their replacements Source: Compiled by the researcher from the annual reports of banks Choice of Population, Sample Size and Sampling method According to Bangladesh Bank, the no. of scheduled NCBs in Bangladesh is 06. Accordingly the researcher opted for 06 NCBs purposively. Collection and Analysis of Data The study is mainly dependent on secondary data that have been gathered from yearly published information of selected NCBs. This balanced panel data sets of 66 observations throughout the period of 2008-2018 have been evaluated by some descriptive statistics, pairwise correlation, ratio analysis and ultimately, random effects regression model. Variables Formula/ Definition Unit Dependent Variables ROE Net income/ Shareholders equity % ROCE EBIT/(Total assets-current liabilities) % Independent Variables TAs/SE Total assets/Shareholders equity % TIC/RWA Tier 1 capital/Risk weighted assets % LQA/TAs Liquid asset/Total assets % RRP/TLs Reverse Repo Purchase/Total liabilities % LQA/TD Liquid asset/Total deposits % BDO/TAs Balance due other banks/Total assets % TDs/TAs Total deposits/Total assets % NPL/GLA Nonperforming loan/Gross loan & advances % MRI Market rate of interest % BSZ Bank size in terms of total deposits Natural logarithm of total deposit https://www.cribfb.com/journal/index.php/amfbr American Finance & Banking Review Vol. 6, No. 1; 2021 31 FINDINGS AND DISCUSSIONS Analysis of Features of Liquidity Indicators and Profitability Indicators of selected NCBs Table 2. Descriptive Analysis of related variables Measu res ROE ROC E TAs / SE TIC / RW A LQ A/ TAs RR P/ TLs LQ A/ TD BD O/ TAs TDs / TAs NPL/ GLA MRI BSZ Mean 0.18 1.99 17.4 4 5.14 9.22 5.30 12.7 4 1.20 80.3 2 18.90 11.7 8 5.54 Range 301.1 8 19.77 68.6 0 30.9 5 12.6 6 5.98 18.8 7 5.44 15.5 2 29.98 4.19 1.19 Max. 41.28 9.85 52.8 7 9.78 17.2 5 9.64 26.1 7 5.44 85.9 3 35.28 13.7 5 6.04 Min. - 259.9 0 -9.92 - 15.7 3 - 21.1 7 4.59 3.66 7.30 0.00 70.4 1 5.30 9.56 4.85 Std. Dev. 43.70 2.83 10.2 8 5.52 2.87 1.08 4.27 1.29 3.78 7.60 1.32 0.30 CV 247.4 5 1.42 0.59 1.07 0.31 0.20 0.34 1.08 0.05 0.40 0.11 0.05 Notes: i) Data have been compiled by the researcher ii) Analysis Mode: SPSS (version 24.0) From the above analysis the study has found that the selected banks have maintained the highest average liquidity ratio i.e 80.32% in terms of TDs/TAs which is authenticated by standard deviation of 3.78%, and range of 15.52%; and the lowest average liquidity ratio i.e 1.20% in terms BDO/TAs which is authenticated by standard deviation of 1.29%, and range of 5.44% during study periods. Between these two liquidity ratios, TDs/TAs indicates minimum risk in terms of CV i.e 0.05%. It has been observed that average rate of profitability in terms of ROE and ROCE is 0.18% and 1.99% respectively. Between two profitability indicators, the maximum & minimum ratio of ROE has shown maximum fluctuation during the study periods. This situation is authenticated by standard deviation of 43.70%, and range of 301.18%. It indicates that selected banks are exposed to more risk in generating profit in terms of ROE than ROCE while managing liquidity. This signifies that selected NCBs should give due consideration to ROE particularly in making profit while constructing liquidity management policies & implementing thereof. Regression Analytical Tests Normality Test https://www.cribfb.com/journal/index.php/amfbr American Finance & Banking Review Vol. 6, No. 1; 2021 32 Table 3. Shapiro-Wilk Test for Normality Variable p value ROE/ROCE 0.12 / 0.08 TAs/SE 0.08 TIC/RWA 0.43 LQA/TAs 0.06 RRP/TLs 0.20 LQA/TD 0.22 BDO/TAs 0.11 TDs/TAs 0.06 NPL/GLA 0.58 MRI 0.18 BSZ 0.21 Notes: i) Data have been compiled by the researcher ii) Analysis Mode: STATA (version 12.0) From table 3, it is clear that the data used in this study is normally distributed as p value > 0.05. Multicollinearity Test Table 4. Analysis of Correlation between Liquidity indicators and Profit base of selected NCBs ROE RO CE TAs/ SE TIC/ RWA LQA/ TAs RRP/ TLs LQA/ TD BDO/ TAs TDs/ TAs NPL/ GLA MRI BSZ ROE 1 ROC E .101 1 TAs/ SE - .572** - .352* 1 TIC/ RWA .378* -.178 .312* 1 LQA/ TAs .037 -.165 .160 .157 1 RRP/ TLs .079 -.173 -.055 .136 .356* 1 LQA/ TD .099 -.077 .098 .268 .788** .226 1 BDO/ TAs .065 .237 - .394* * - .483** .105 .043 -.023 1 TDs/ TAs .126 -.192 .006 -.073 .435** .235 .196 .347* 1 NPL/ -.258 -.144 .144 -.190 .038 .205 -.004 -.113 .017 1 https://www.cribfb.com/journal/index.php/amfbr American Finance & Banking Review Vol. 6, No. 1; 2021 33 GLA MRI -.237 .201 .057 -.219 -.348* -.181 - .481** .182 -.212 -.067 1 BSZ -.047 - .464* * .287 .488** .184 .409** .222 - .490** .168 .333* - .324* 1 Notes: i) Data have been compiled by the researcher ii) Analysis mode: SPSS (version 24.0) iii) *Correlation is significant at the 5% level ** Correlation is significant at the 1% level From table 04, it is observed that as the correlation between the variables is below the maximum limit of 0.80, so the variables are beyond multicollinearity problem which is supported by Kennedy (2008). Another important method of identifying multicollinearity is the Variance Inflation Factor (VIF). According to Gujarati and Sangeetha (2008), if the VIF value exceeds 10, the variable is considered to be highly collinear. The VIF test result for all the explanatory variables are shown in appendix 1A where there is no existence of multicollinearity problem as the VIF value of the variables is less than 10. Heteroskedasticity Test White’s heteroskedasticity test is applied to measure the difficulty of heteroskedasticity in a linear regression model (Gujarati, 1995). The outcomes of both analysis indicate that there is no evidence for the existence of heteroskedasticity, as the calculated values 44.00 < the critical value 79.49 as shown in appendix 1B and 1C. Test of Autocorrelation One of the most popular tests for the detection of autocorrelation is Wooldridge (2002) statistic which signifies that there is no autocorrelation, as presented below: Table 5. Wooldridge Test for Autocorrelation ROE ROCE Ho: no first –order autocorrelation F (1, 3) = 4.733 Prob > F = 0.1178 Ho: no first –order autocorrelation F (1, 3) = 1.736 Prob > F = 0.2792 Notes: i) Data have been compiled by researcher ii) Analysis mode: STATA (version 12.0) Hausman Specification Test A Hausman Test (1978) has been applied to measure the appropriateness of Random versus Fixed effects model which is reported in appendix 1D and 1E. After running the Hausman test, both Prob>chi2 value of ROE and ROCE are 0.3881 and .8494 respectively, which are greater https://www.cribfb.com/journal/index.php/amfbr American Finance & Banking Review Vol. 6, No. 1; 2021 34 than 0.05. Therefore the Random Effects model is statistically appropriate for both the model of the study. Random Effect (RE) tests on Model 1 (ROE) and Model 2 (ROCE) Table 6. Position of ROE and ROCE in the Effectiveness of Liquidity Management Variables Model 1 (ROE) Model 2 (ROCE) Constant 79.3944 23.9873* TAs/SE -3.2398*** -.0787 TIC/RWA 6.0589*** .0709 LQA/TAs .1159 -.1708 RRP/TLs -.4326 .0154 LQA/TD -.5235 .1532 BDO/TAs -3.5083 -.0177 TDs/TAs 3.1273** -.032 NPL/GLA .5269 .0333 MRI -2.5484 .3275 BSZ -49.2252** -4.2098* F 10.03 1.271 R2 .7525 .2493 Adjusted R2 .5925 .0530 No. of observations 66 66 Notes: i) Data have been compiled by researcher ii) Analysis mode: STATA (version 12.0) iii) Standard errors in parentheses p* < 0.10, p** < 0.05, p*** < 0.01 From RE regression Model 1, it has been observed that the variables TAs/SE & TIC/RWA are significant at 1% level and TDs/TAs & BSZ at 5% level. The rest of the variables are found insignificant. The value of R2 is 75.25%; it signifies that the explanatory variables could clarify 75.25% of the variations in ROE. F value of statistics is also found significant. F value of statistics is also found significant. From RE regression Model 2, it has been observed that almost all the explanatory variables are found insignificant even BSZ as it is significant at 10% level. The value of R2 is 24.93%; it signifies that the explanatory variables could clarify only 24.93% of the variations in ROCE. F value of statistics is also found insignificant. These imply that standing of ROE compared to ROCE is more significant in the effectiveness of liquidity management of selected NCBs in Bangladesh. Accordingly, in case of Model 1 the null hypothesis is rejected and alternative hypothesis is accepted. That is, there is a statistically significant association between ROE and liquidity of NCBs. On the other hand, the null hypothesis of Model 2 is accepted indicating that there is no statistically significant association between ROCE and liquidity of NCBs. https://www.cribfb.com/journal/index.php/amfbr American Finance & Banking Review Vol. 6, No. 1; 2021 35 CONCLUSION AND RECOMMENDATIONS The study is attempted to figure out the relative standing of ROE and ROCE in the effectiveness of liquidity management of NCBs in Bangladesh. It is found that ROE represents better standing than ROCE in case of effective liquidity management. The ROE is mainly influenced by TAs/SE, TIC/RWA, TDs/TAs and BSZ liquidity measures. Among the explanatory measures, TAs/SE has highly significant negative and TIC/RWA has highly significant positive effect on ROE; TDs/TAs has some significant positive and BSZ has some significant negative effect on ROE of the selected NCBs. The conclusion recommends that NCBs that can increase its core capital will act as a defender in protecting consumers against unexpected losses and to exude financial strength. Papa (2012) said that banks can simply drive up ROE by holding relatively higher levels of Tier 1 capital. According to Abugamea (2018); Ramadan et al. (2011), profitability in terms of ROE tends to be associated with well capitalized banks. Abugamea (2018) also asserted that ROE is inversely related to deposits which is supported by the ratio BSZ in terms of total deposits. But higher deposits to assets ratio is linked with improved financial sufficiency, as deposits are the stable sources of fund for funding assets (Mwangi et al., 2015). There is a common phenomenon that banks’ profitability is extensively affected by its higher total assets provided the assets are financed by stock rather than debt. Ramadan et al. (2011) showed that there is an association between ROE and the efficacy of credit management. Based on the empirical assessment, the researcher recommends that NCBs should accept a more professional liquidity management strategy to insure such conflicting objectives of banks- liquidity, profitability and solvency. Agbada and Osuji (2013) articulated that with a view to achieving these conflicting objectives, liquidity management requires to be efficient in the circulation of liquidity compatible with a preferred level of cash without twisting the profitability and functions of the bank. Without effective liquidity management, banks with intense foundation and bright future may not be profitable (Jose et al., 1996). LIMITATIONS OF THE STUDY The study has considered a limited no. of variables and only four selected NCBs in Bangladesh as sample. Therefore the size of the sample might be increased for measuring the actual effect of exogenous variables on the dependent variable. 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APPENDICES Appendix-1 A: VIF Results Variable VIF value Tolerance LQA/TAs 3.92 0.26 LQA/TDs 3.57 0.28 BSZ 2.64 0.38 BDO/TAs 2.28 0.44 TIC/TRW 1.97 0.51 TDs/TAs 1.83 0.55 MRI 1.57 0.64 RRP/TLs 1.53 0.65 TAs/SE 1.47 0.68 NPL/GLA 1.46 0.68 Mean VIF 2.22 Notes: i) Data have been compiled by researcher ii) Analysis mode: STATA (version 12.0) Appendix-1 B: White’s Heteroskedasticity Test on ROE Source Chi2 df p Heteroscedasticity 66.00 43 0.4290 Skewness 31.78 10 0.0004 Curtosis 0.89 1 0.3460 Total 76.67 54 0.0229 Notes: i) Data have been compiled by researcher ii) Analysis mode: STATA (version 12.0) Appendix-1C: White’s Heteroskedasticity Test on ROCE Source Chi2 df p Heteroscedasticity 66.00 43 0.4290 Skewness 8.99 10 0.5330 Curtosis 1.50 1 0.2212 Total 54.49 54 0.4559 Notes: i) Data have been compiled by researcher ii) Analysis mode: STATA (version 12.0) https://www.cribfb.com/journal/index.php/amfbr American Finance & Banking Review Vol. 6, No. 1; 2021 40 Appendix-1D: Hausman Test on ROE ROE Coefficients b Fixed B Random b-B Differences sqrt (diag(V_b- V_B)) SE X1: TAs/SE -3.2444 -3.2398 -.0047 .1409 X2: TIC/TRW 5.8043 6.0589 -.2546 .2472 X3: LQA/TAs 1.9815 .1159 1.8656 1.1810 X4: RRP/TLs .2120 -.4326 .6446 1.7642 X5: LQA/TD .3758 -.5235 .8993 .6923 X6: BDO/TAs -6.4881 -3.5083 -2.9798 2.2446 X7: TDs/TAs 3.5190 3.1273 .3917 .4181 X8: NPL/GLA .6512 .5269 .1242 .8021 X9: MRI -2.9912 -2.5484 -.4428 .8258 X10: BSZ -102.4167 -49.2252 -53.1915 31.7284 Notes: i) Data have been compiled by the researcher ii) Analysis Mode: STATA (version 12.0) iii) b = consistent under Ho and Ha; obtained from xtreg B= inconsistent under Ha, efficient under Ho; obtained from xtreg iv) Test: Ho: difference in coefficients not systematic Chi2 (3) = (b-B)1[(V_b-V_B)^(-1)] (b-B)=3.02 Prob>chi2 = 0.3881 Appendix-1E: Hausman Test on ROCE ROCE Coefficients b Fixed B Random b-B Differences sqrt (diag(V_b-V_B)) SE X1: TAs/SE -.0784 -.0787 .0002 .0153 X2: TIC/TRW .0804 .0709 .0095 .0269 X3: LQA/TAs -.1229 -.1708 .0480 .1283 X4: RRP/TLs .0717 .0154 .0563 .1917 X5: LQA/TD .1267 .1532 -.0264 .0752 X6: BDO/TAs .1107 -.0177 .1284 .2439 X7: TDs/TAs -.0016 -.0320 .0304 .0454 X8: NPL/GLA .0108 .0333 -.0225 .0872 X9: MRI .3137 .3275 -.0138 .0897 X10: BSZ -4.3824 -4.2098 -.1726 3.4475 Notes: i) Data have been compiled by the researcher ii) Analysis Mode: STATA (version 12.0) iii) b = consistent under Ho and Ha; obtained from xtreg B= inconsistent under Ha, efficient under Ho; obtained from xtreg iv) Test: Ho: difference in coefficients not systematic Chi2 (3) = (b-B)1[(V_b-V_B)^(-1)] (b-B)=0.80 Prob>chi2 = 0.8494 https://www.cribfb.com/journal/index.php/amfbr American Finance & Banking Review Vol. 6, No. 1; 2021 41 AUTHOR CONTRIBUTIONS Conceptualization: Nazneen Jahan Chaudhury Data curation: Nazneen Jahan Chaudhury Formal analysis: Nazneen Jahan Chaudhury Funding Acquisition: Nazneen Jahan Chaudhury Project Administration: Nazneen Jahan Chaudhury Software: Nazneen Jahan Chaudhury Validation: Nazneen Jahan Chaudhury Writing – Original Draft: Nazneen Jahan Chaudhury Writing – Review & Editing: Nazneen Jahan Chaudhury CONFLICT OF INTEREST STATEMENT The authors declare that they have no competing interests. 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