ABSTRACT:

This study analyzes data of 29 joint-stock commercial banks in Vietnam over m w88 period from 2007 to 2019 to test m w88 impact of factors affecting m w88 profitability of commercial banks. Fixed effects (FE) and random effects (RE) regression methods were used to conduct this study. Then, a suitable research model was selected via m w88 Hausman test. m w88 results show that banking characteristics have significant impacts on m w88 profitability of commercial banks. Based on m w88 study’s findings, some solutions are proposed to improve m w88 performance efficiency ofcommercial banks.

Keywords: performance efficiency, commercial banking, panel data.

1.Introduction

m w88 banking system is critical to m w88 development of m w88 economy because it allows capital to be circulated from excess sources and in demand. As a result, m w88 commodity budget's stability is regarded as a critical aspect of m w88 economy's development. Currently, in economic terms, Vietnam is a member state of m w88 United Nations, m w88 World Trade Organization, m w88 International Monetary Fund, m w88 World Bank Group, m w88 Asian Development Bank, m w88 Asian Development Bank, m w88 International Monetary Fund, m w88 Asia-Pacific Economic Cooperation, and m w88 ASEAN. Vietnam participates in multilateral free trade agreements with ASEAN countries, Korea, Japan, and China. Vietnam has also signed a bilateral economic partnership agreement with Japan. For m w88 monetary and banking sector, m w88 integration process is associated with m w88 financial market liberalization process, bringing many opportunities, but also many challenges. From that reality, m w88 study analyzes factors affecting m w88performanceof Vietnamese commercial banks in m w88 current period. Based on m w88 study’s findings, some practical solutions are proposed to improve m w88 performance of Vietnamese commercial banks.

2. LiteratureReview

Commercial banks, according to Rose (2004), are also regarded as business groups that operate for m w88 purpose of maximizing profits while minimizing risk. Profitability, on m w88 other hand, is an aim that banks are interested in, since high income would assist banks to conserve capital, expand market share, and attract investment capital. m w88 impact of factors on operational efficiency has been shown through several domestic and foreign studies, such as Le Thi Huong (2002) with research on improving m w88 investment performance of Vietnamese commercial banks; Ariss's (2010) study used OLS and Tobit models to explore how market power affects m w88 efficiency and stability of m w88 system in m w88 context of developing economies.

According to William (2012), m w88 SFA, 2SLS, and Tobit models are used to analyze m w88 relationship between market power and bank efficiency in Latin America. Most of m w88 studies on m w88 efficiency of banking activities focus mainly on developed countries.

Athanasoglou et al (2008) examined m w88 internal, sectoral, and macro factors affecting m w88 ROA and ROE of m w88 Greek banks. m w88 results show that, except for m w88 size variable, m w88 variables reflecting bank characteristics such as capital adequacy, credit risk, production capacity, cost management, and scale all affect profitability.

Osuagwu (2014) studies m w88 profitability of commercial banks in developing countries, specifically Nigeria. m w88 findings show that bank-specific factors are important in determining bank profitability, while industry factors have a negligible influence and macro factors fail m w88 multi-collinearity test.

3. ResearchMethods and Data

3.1 Research methods

Theoretically, as well as with empirical evidence, there are many different measures and representations of performance. m w88 author's research point of view: Choose m w88 ROE ratio to measure m w88 performance of joint-stock commercial banks and it is m w88 dependent variable. Based on m w88 theory of several factors affecting bank performance and empirical studies at home and abroad related to m w88 impact of factors affecting performance. m w88 author proposes a research model:

ROEit = β0 + β1SIZEit + β2TCTRit + β3DLRit + β4ETAit + β5NPLit + uit

3.2 Research data

Research data was collected from m w88 annual financial statements of 20 joint-stock commercial banks operating as of m w88 end of m w88 2019 accounting year. m w88 results of Table 2 show that most of m w88 variables, such as: ROE, NPL, SIZE, TCTR, ETA all have relatively low dispersion. m w88 DLR variables, on m w88 other hand, produce m w88 opposite result.

 Table 1: Description of variables

description_m w88_variables

(Sources:Compiled by m w88 author)

4. Result

Table 2: Descriptive Statistics

descriptive_statistics

 (Source:  Work’s estimation from STATA 15)

Table 3: Regression results

regression_results

 (Source:  Work’s estimation from STATA 15)

m w88 standard errors of variables are put into parentheses.

*, **, *** stand for m w88 significance level at 10%, 5% and 1% respectively.

From m w88 FE and RE regression results, we see that m w88 variables TCTR, ETA, DLR, NPL, and size always have an impact on m w88 ROA. All regression models are statistically significant and have an R-square of 19%. m w88 Hausman test is used to choose between m w88 FE and RE models, and m w88 test results show that Prob Chi 2 = 0.039 = 0.05. Therefore, we accept hypothesis H0, m w88 FE model is more suitable than RE. m w88 Breusch - Pagan test for m w88 FE model gives m w88 result that Prob < Chi 2 = 0.000 < = 0.05, so m w88 model has a variable variance. At m w88 same time, m w88 Wooldridge autocorrelation test for Prob Chi 2 = 0.07 = 0.05, so m w88 model does not have any autocorrelation, multicollinearity test

Table 4: Variance Inflation Factor (VIF) results

variance_inflation_facm w88r_vif_results (Source:  Work’s estimation from STATA 15)

Their VIF values are less than 10, suggesting that there is no multicollinearity among them (Any VIF greater than 10 indicates a multicollinearity issue (Hair et al. 2010). m w88 magnitude of m w88 correlation coefficients indicates that multicollinearity in m w88 regression model is unlikely. m w88 FGLS (feasible generic least square) approach is then used to address m w88 phenomena of variable variance, and m w88 results are shown in Table 5.

Table 5: m w88 result FGLS

m w88_result_fgls (Source:  Work’s estimation from STATA 15)

m w88 standard errors of variables are put into parentheses.

*, **, *** stand for m w88 significance level at 10%, 5% and 1% respectively.

When testing m w88 model's fit, m w88 value of m w88 F test yields m w88 result Prob (F-statistic) = 0.000 = 0.05, so we reject hypothesis H0 and accept hypothesis H1 that m w88 research model is adequate. m w88 independent variables account for approximately 20% of m w88 variation in ROE. As a result, m w88 model is free of flaws, ensuring its dependability.

5. Conclusions

m w88 regression coefficient of m w88 scale variable (SIZE) is 0.003. It shows that m w88 bank size has a positive effect on m w88 performance and is significant at m w88 5% level. m w88 larger m w88 bank's scale, m w88 easier it is to equip it with more modern technology to diversify its services. m w88 research results of Ho Thi Hong Minh and Nguyen Thi Canh (2015) show that there is an evidence that income diversification positively affects profitability. Therefore, this study also predicts that m w88 bank size has a positive effect on m w88 dependent variable. m w88 regression coefficient of m w88 variable cost to revenue (TCTR) is -0.001. m w88 results of this study show that m w88 cost-to-revenue ratio harms operational efficiency and has statistical significance at 5%. This finding is consistent with m w88 author's expectations and it is supported by Rahman et al (2015). DLR is statistically significant at m w88 1% level. This shows that if banks make good use of mobilized capital, they can increase their operational efficiency.

m w88 regression coefficient of m w88 variable equity ratio (ETA) is 0.079. This result shows that m w88 ratio of equity to total assets has a positive effect on performance and has a statistical significance of 1%. When equity is high, they can lend more, which contributes to an increase in operational efficiency. This finding is consistent with m w88 research of Rahman et al (2015). NPL ratio (NPL) is statistically significant at m w88 5% level of significance. This variable reflects m w88 quality of m w88 bank's lending assets. This result is consistent with m w88 studies of Ayanda et al. (2013), Osuagwu (2014).

Furthermore, to optimize profitability, commercial banks must strike a balance between costs and revenue. Furthermore, it is critical to make good use of m w88 mobilized money because m w88 input capital has a high cost that affects m w88 bank's profit. Furthermore, rising equity must be considered because increasing equity is also a component of generating profit.

 

REFERENCES:

  1. Ayanda et al. (2013). Detarminants of banks' profitability in a developing economy: Evidence from Nigerian banking industry.Interdisciplinary journal of contemporary research in business, 4(9), 155-182.
  2. Athanasoglou, Brissimis and Delis. (2008). Bank-specific, industry-specific and macroeconomic determinants of bank profitability.Journal of International Financial Markets, Institutions & Money, 18, 121-136.
  3. Ho Thi Hong Minh, Nguyen Thi Canh. (2015). Income diversification and factors affecting m w88 profitability of Vietnamese commercial banks. Banking Technology Magazine, 106-107.
  4. Nouaili1. M, Abaoub. E, Ochi. A. (2015). m w88 Determinants of Banking Performance in Front of Financial Changes: Case of Trade Banks in Tunisia.International Journal of Economics and Financial Issues, 5(2), 410-417.
  5. Osuagwu. (2014). Determinants of Bank Profitability in Nigeria.International Journal of Economics and Finance, 6(12), 46- 64
  6. Rahman. M. M., Hamid. K & Khan. A. M (2015). Determinants of Bank Profitability: Empirical Evidence from Bangladesh.International Journal of Business and Management,10(8), 135-150.
  7. Sturm, J. and Williams, B. (2008). Characteristics determining m w88 efficiency of foreign banks in Australia.Journal of Banking and Finance, 32(11), 2346–2360;

 

CÁC NHÂN TỐ ẢNH HƯỞNG ĐẾN HIỆU QUẢ HOẠT ĐỘNG

CỦA NGÂN HÀNG THƯƠNG MẠI

ThS. LÊ HỒNG NGA

Khoa Kinh tế, Trường Đại học Bạc Liêu

TÓM TẮT:

Nghiên cứu này phân tích dữ liệu của 29 ngân hàng thương mại cổ phần (NHTMCP) tại Việt Nam từ năm 2007 đến năm 2019 nhằm kiểm định tác động của các nhân tố ảnh hưởng đến lợi nhuận của các ngân hàng thương mại. Phương pháp hồi quy hiệu ứng cố định (FE) và hiệu ứng ngẫu nhiên (RE) được sử dụng trong nghiên cứu này. Từ đó, một mô hình nghiên cứu phù hợp đã được lựa chọn thông qua bài kiểm tra Hausman. Kết quả cho thấy các đặc điểm của ngân hàng có tác động đáng kể đến lợi nhuận của các ngân hàng thương mại. Dựa trên kết quả nghiên cứu, một số giải pháp được đề xuất nhằm góp phần nâng cao hiệu quả hoạt động của ngân hàng thương mại.

Từ khóa: hiệu quả hoạt động, ngân hàng thương mại, dữ liệu bảng.

[Tạp chí Công Thương - Các kết quả nghiên cứu khoa học và ứng dụng công nghệ,

Số 13, tháng 6 năm 2021]