Factors affecting productive efficiency of Vietnam joint stock commercial bank for industry and trade

Fixed assets/Total asset has proportional relation to EF. The increased rate would raise the tech- nical efficiency and vice versa. It can be seen that VietinBank's increased investment in fixed assets would improve its efficiency. The machinery and equipment will improve the bank's infrastructure and facilitate the development of products and services to best serve the clients. * Testing factors affecting productive efficiency by regression model with ROAdependent variables - Statistical description of variables in regression model with ROAdependent variables 49 journal of Trade Science JOURNAL OF TRADE SCIENCE ’S JTS Table 4: Results of Tobit regression model *;**;*** significant at 1%, 5%, 10% (Source:Author's calculation byStata 13) Variables DLR LOTA FATA TCTA DLR -0.757*** (0.174) LOTA 1.307*** (0.315) FATA 60.68** (20.92) TCTA -6.710** (2.163) Constant 1.833*** -0.0826 0.252 1.453*** (0.225) (0.229) (0.221) (0.193) LLL 3.86 4.15 1.330 2.463 Table 5: Statistical description of variables in regression model with ROA dependent variables (Source:Author's calculation byStata 13) Variables Mean Deviation Min Max ROA 0.012136 0.005112 0.0039 0.0203 EQRE 0.062858 0.01626 0.041422 0.09382 LPNL 0.013816 0.008277 0.004758 0.031342 FATA 0.010684 0.002059 0.00731 0.013526 TRAD 7.615003 3.139801 4.176325 14.40462 SIZE 33.386 0.674638 32.38259 34.28965 The study described the variables in the model. Accordingly, ROAaveraged at 1.21% with max value of 2.03% and min of 0.39%. Other factors were also presented as mean, deviation, min and max in the table. - Correlation matrix The large correlation coefficient shows the strong relation between variables. From the results, ROAhas the strongest relation with SIZE - Bank size (0.79), and weakest relation with LPNL (- 0.4095).It is necessary to use regression analysis to evaluate the one-way impact of variables on ROA. - Results of regression model It is required to do some tests to check the significant results. a. Regression equation specification error test It showed that the equation model was suitable with P-value = 0.1494 greater than 0.05. With the result, hypothesis Howas accepted,so the linear equa- tion was rational. b. Heteroscedasticity test White's test led to P-value= 0.3575 greater than 0.05. Therefore, hypothesis Ho was accepted and there was no homoscedasticity in the model. 50 Journal of Trade Science JOURNAL OF TRADE SCIENCE ’S JTS Table 6: Correlation matrix of coefficient between variables (Source:Author's calculation byStata 13) Ramsey RESET test using powers of the fitted values of ROAA Ho: model has no omistted variables F (3,2) = 5.85 Prob > F = 0.1494 Variables ROA EQRE LPNL FATA TRAD SIZE ROA 1 EQRE 0.5703 1 LPNL -0.4095 -0.1468 1 FATA 0.3716 0.2669 -0.614 1 TRAD -0.3868 -0.349 0.4036 -0.475 1 SIZE 0.7986 0.7402 -0.5213 0.2151 -0.166 1 Table 7: Results of regression model with ROA dependent variables (Source: Author's calculation byStata 13) ROA dependent variables Coefficients Standard error T P>t Confidence interval 95% EQRE -0.29739 0.097742 -3.04 0.029 -0.54864 -0.04613 LPNL 0.582112 0.180001 3.23 0.023 0.119406 1.044818 FATA 1.407584 0.513214 2.74 0.041 0.088324 2.726843 TRAD -0.00087 0.000292 -2.97 0.031 -0.00162 -0.00012 SIZE 0.013486 0.002593 5.2 0.003 0.006819 0.020152 _cons -0.43588 0.085137 -5.12 0.004 -0.65473 -0.21703 Whites test for Ho: homoskedasticity against Ha: unrestricted heteroskedasticity chi2 (10) = 11.00 Prob > chi2 = 0.3575 c. Auto-correlation test The test results showed P-value = 0.2382 greater than 0.05, then we accepted hypothesis Ho and con- cluded that the model did not have auto-correlation. d. Multicollinearity VIF < 10 showed that there was no multicollinear- ity in the model, all variables could enter the model simultaneously. Analysis of regression model with ROA dependent variables EQRE coefficient - Equity/Total capitalhas oppo- site effect on ROA with P-value < 0.05 and negative beta coefficient. The negative effect of EQRE on pro- ductive efficiency showed that the bank increased its capital too rapidly without effective use of capital, which reduces its efficiency. LPNL - Loan loss provision/ Total loan has propor- tional effect on ROA. VietinBank fulfilled its duties to classify and provide for risks in order to form a strong financial source for its operation and improve the effi- ciency. Furthermore, the increased provision may result from increased non-performing loan, but it can be solved by other methods related to capital, technol- ogy and labour. This helps increase the bank's produc- tive efficiency. FATA - Fixed asset/Total asset has positive effect on ROA. The increased ratio of fixed assets on total asset leads to the increase in productive efficiency, and vice versa. It showed that VietinBank investment in fixed assets promoted its efficiency. Therefore, the facilities and equipment help the bank create good infrastructure for developing products and services and improving its profitability. TRAD - Interest income/Operating incomehas opposite effect on ROA with the significance less than 0.05. VietinBank focused on interest income, which led to a decrease in the productive efficiency. Therefore, VietinBank should pay attention to other products and services to increase its non-interest income. SIZE - Bank size (Logarithm of Total assets) has positive effect on ROA with the significance of less than 5%. It means that the increased bank size can result in higher productive efficiency. However, it had limited effect (0.013). Thus, VietinBankshould consid- er before building expansion strategies to improve its efficiency. 5. Conclusion The regression results of Tobit model and regres- sion model with ROA dependent variable showed that (1) FATA - Fixed assets/ Total assets has positive effect on technical efficiency (EF) and returns on assets (ROA). Over the past few years, the investment in fixed assets has increased VietinBank's efficiency and it has been a right decision. (2) The effect of some fac- tors on the efficiency of VietinBank showed that each model had different factors and different influencing levels. The testing results were supplemented and combined the system of factors affecting the produc- tive efficiency of VietinBank. (3) The results from two supplementing models presented highly valued con- clusions. Regarding ROA model, SIZE has positive effect, which means the increase in size leads to the increase in profitability, but the effect is still limited. In addition, under DEA model, the bank had lowering technical efficiency in returns to scale from 2010 to 2015. As the combined results from the two models, VietinBank should carefully plan the expansion strate- gy to increase its efficiency. 51 journal of Trade Science JOURNAL OF TRADE SCIENCE ’S JTS Breusch-Godfrey LM test for autocorrelationg H0: no serial correlation lags (p) chi2 df Prob>chi2 1 1.391 1 0.2382 Variable VIF SIZE 6.71 EQRE 5.54 LPNL 4.86 FATA 2.45 TRAD 1.85 Mean VIF 4.28 References: 1. Banker, R.D., Charnes, A. and Cooper, W.W. (1984), "Some models for estimating technical and scale inefficiencies in data envelopment analysis", Management Science, Vol. 30, No. 9 September 1984. 2. Berger, N.A. and Humphrey, B.D. (1997), "Efficiency of financial institutions: International sur- vey and directions for future research", European Journal of Operational Research 98 pp. 175-212. 3. Dawood, U. (2014), "Factors impacting prof- itability of commercial banks in Pakistan for the peri- od of (2009-2012)", MS Finance, University of Gujrat. Pakistan, International Journal of Scientific and Research Publications, Volume 4, Issue 3, March 2014. 4. Farrell, MJ (1957), "The measurement of pro- ductive efficiency", Journal of the royal statistical soci- ety (Series A), 120/3, pp. 253-281. 5. Tobin, J. (1958), "Estimation of relationships for limited dependent variables", Econometrica 26(1), pp. 24-36. 6. Syafri (2012), "Factors affecting bank prof- itability in Indonesia", The 2012 international confer- ence on Business and Management. Summary Vieäc ñaùnh giaù hieäu quaû kinh doanh (HQKD) vaø xem xeùt caùc yeáu toá taùc ñoäng ñeán HQKD cuûa ngaân haøng thöông maïi (NHTM) trong neàn kinh teá thò tröôøng laø noäi dung phöùc taïp vì hoaït ñoäng kinh doanh cuûa ngaân haøng coù tính ñaëc thuø, lieân quan ñeán nhieàu nhoùm chuû theå, phuï thuoäc nhieàu yeáu toá chuû quan vaø khaùch quan, caùc yeáu toá coù theå taùc ñoäng tröïc tieáp hoaëc giaùn tieáp. Taïi nghieân cöùu naøy, taùc giaû söû duïng moâ hình bao döõ lieäu (DEA-Data Envelopment Analysis) ñeå öôùc löôïng hieäu quaû kyõ thuaät, sau ñoù duøng moâ hình hoài qui Tobit ñeå ñaùnh giaù caùc yeáu toá taùc ñoäng ñeán hieäu quaû kyõ thuaät trong giai ñoaïn 2005-2011cuûa Ngaân haøng thöông maïi coå phaàn Coâng Thöông Vieät Nam (VietinBank). Ngoaøi ra, nghieân cöùu söû duïng moâ hình hoài qui vôùi bieán phuï thuoäc ROA ñeå ñaùnh giaù caùc yeáu toá taùc ñoäng ñeán hieäu quaû sinh lôøi cuûa VietinBank. Keát quaû töø caùc moâ hình ñöôïc toång hôïp ñaùnh giaù vaø haøm yù moät soá giaûi phaùp ñeå naâng cao HQKD cuûa VietinBank trong thôøi gian tôùi. 52 Journal of Trade Science JOURNAL OF TRADE SCIENCE ’S JTS DANG THI MINH NGUYET 1. Personal Profile - Name: Dang Thi Minh Nguyet - Date of birth: August 17th 1981 - Title: Master - Workplace: Thuongmai University - Position: lecturer 2. Major research directions: Productive efficiency in commercial bank, finance and bank- ing, securities. 3. Publications the author has published his works: - Economy and Forecast Review - Viet Nam Trade and Industry Review - Trade Science Review