Determinants of bank performance in Vietnamese commercial banks: an application of the camels model

Figures & data

Table 1. Variables in model

	Variables	Index	Formula/ Source data	Related research
Dependent variables
$\mathrm{b}\mathrm{a}\mathrm{n}\mathrm{k}\mathrm{p}\mathrm{e}\mathrm{r}\mathrm{f}\mathrm{o}\mathrm{r}\mathrm{m}\mathrm{a}\mathrm{n}\mathrm{c}{\mathrm{e}}_{\mathrm{i}\mathrm{t}}$	tobin’s_q	$\mathrm{t}\mathrm{o}\mathrm{b}\mathrm{i}\mathrm{n}\mathrm{\_}{\mathrm{q}}_{\mathrm{i}\mathrm{t}}$		Rostami (2015b)
Independent variables
$\mathrm{c}\mathrm{a}\mathrm{m}\mathrm{e}\mathrm{l}\mathrm{s}\mathrm{\_}\mathrm{f}\mathrm{a}\mathrm{c}\mathrm{t}\mathrm{o}\mathrm{r}{\mathrm{s}}_{\mathrm{i}\mathrm{t}}$	Capital adequacy ratio	$\mathrm{c}\mathrm{a}{\mathrm{r}}_{\mathrm{i}\mathrm{t}}$	From Financial statements and annual reports	Kaur (2010), Sangmi and Nazir (2010), Soni (2012), Rozzani and Rahman (2013), Rahman et al. (2015).
	Asset quality	$\mathrm{n}\mathrm{p}\mathrm{l}{\mathrm{s}}_{\mathrm{i}\mathrm{t}}$	non-performing loans/total loans (From Financial statements and annual reports)	Olweny and Shipho (2011), Dang (2011), Rozzani and Rahman (2013), Balango and Rao (2017), Kingu et al. (2018), Patwary and Tasneem (2019).
	Management	$\mathrm{c}\mathrm{i}{\mathrm{r}}_{\mathrm{i}\mathrm{t}}$	Total cost/Total income	Olweny and Shipho (2011), Roman and Sargu (2013), Liu and Pariyaprasert (2014).
	Earnings	$ro{e}_{\mathrm{i}\mathrm{t}}$	From Financial statements and annual reports	Jha and Hui (2012), Rozzani and Rahman (2013), Liu and Pariyaprasert (2014).
	Liquidity	$\mathrm{l}\mathrm{d}{\mathrm{r}}_{\mathrm{i}\mathrm{t}}$	Total loans/Total deposits	Golin (2001), Elyor (2009), Jha and Hui (2012), Liu and Pariyaprasert (2014).
	Sensitivity	$\mathrm{s}\mathrm{e}{\mathrm{n}}_{\mathrm{i}\mathrm{t}}$	Bank asset/Total asset banking sector	Sarker (2006), Avkiran and Cai (2012), Roman and Sargu (2013), Kumari (2017).
$\mathrm{M}\mathrm{a}\mathrm{c}\mathrm{r}\mathrm{o}\mathrm{e}\mathrm{c}\mathrm{o}\mathrm{n}\mathrm{o}\mathrm{m}\mathrm{i}\mathrm{c}{\mathrm{s}}_{\mathrm{i}\mathrm{t}}$	Inflation rate	$\mathrm{i}\mathrm{n}{\mathrm{f}}_{\mathrm{i}\mathrm{t}}$	World Bank	J. Boyd and Smith (1998), Guru et al. (2002), Jiang et al. (2003), John H. Boyd and Champ (2006), Fadzlan (2009), Miguel Á. et al. (2018), Gilbert and Jaya (2019), Cetin (2019), Mbabazize et al. (2020), Almansour et al. (2021).
	GDP growth rate	$\mathrm{g}\mathrm{d}{\mathrm{p}}_{\mathrm{i}\mathrm{t}}$	World Bank	Sufian and Habibullah (2010), Liu and Pariyaprasert (2014), Emase (2017), Tahsin and Gülşah (2018), Matar et al. (2018).
$\mathrm{O}\mathrm{t}\mathrm{h}\mathrm{e}\mathrm{r}\mathrm{f}\mathrm{a}\mathrm{c}\mathrm{t}\mathrm{o}\mathrm{r}\mathrm{s}$	Leverage	$\mathrm{l}\mathrm{e}{\mathrm{v}}_{\mathrm{i}\mathrm{t}}$	Total liabilities/Total assets	Booth et al. (2001), Onaolapo and Kajola (2010), Salim and Yadav (2012), Iavorskyi (2013).
	Ownership	$\mathrm{o}\mathrm{w}{\mathrm{n}}_{\mathrm{i}\mathrm{t}}$	own = 0 if bank is state-owned commercial bank; own = 1 otherwise The explanatory variables are dummies for ownership type, with domestic private. The robustness of the ownership results is established in the discussion section.	La Porta et al. (2002), Barth et al. (2001), Cornett et al. (2009), Su and He (2012), Robin et al. (2018).
$\mathrm{I}\mathrm{n}\mathrm{s}\mathrm{t}\mathrm{r}\mathrm{u}\mathrm{m}\mathrm{e}\mathrm{n}\mathrm{t}\mathrm{v}\mathrm{a}\mathrm{r}\mathrm{i}\mathrm{a}\mathrm{b}\mathrm{l}{\mathrm{e}}_{\mathrm{i}\mathrm{t}}$	ltobin_q	$\mathrm{t}\mathrm{o}\mathrm{b}\mathrm{i}\mathrm{n}\mathrm{\_}{\mathrm{q}}_{\mathrm{i}\mathrm{t}-1}$
	lroe	$ro{e}_{\mathrm{i}\mathrm{t}-1}$

Table 2. Descriptive statistics

Variable	Obs	Mean	Std. Dev.	Min	Max
tobin_q	420	4.34	5.16	0.10	26.28
car	420	0.13	0.04	0.05	0.23
npl	420	0.05	0.06	0.01	0.82
cir	420	−0.52	0.19	−1.12	1.83
roe	420	0.12	0.36	−0.56	7.36
ldr	420	0.85	0.22	0.37	1.81
sen	420	0.06	0.10	0.01	1.31
lev	420	11.54	4.52	2.01	23.95
size	420	32.17	1.24	28.83	34.96
own	420	0.89	0.32	0.00	1.00
gdp	420	0.06	0.02	0.01	0.09
inf	420	0.06	0.04	2.01	0.19

Table 3. Test of the multi-collinear phenomenon

Variable	VIF	1/VIF
roe	2.54	0.39
cir	2.01	0.50
npl	1.93	0.52
lev	1.86	0.54
size	1.84	0.54
own	1.32	0.76
ldr	1.21	0.83
inf	1.16	0.86
car	1.07	0.93
sen	1.03	0.97
gdp	1.02	0.98
Mean VIF	1.55

Table 4. Correlation matrix

	tobin_q	car	npl	cir	roe	ldr	lev	sen	size	own	inf	gdp
tobin_q	1.00
car	0.59	1.00
npl	−0.48	−0.39	1.00
cir	−0.09	0.04	0.12	1.00
roe	−0.65	−0.52	0.63	−0.02	1.00
ldr	−0.26	−0.32	0.32	−0.03	0.19	1.00
lev	−0.17	−0.22	0.16	−0.03	0.19	0.11	1.00
sen	0.53	0.70	−0.46	0.02	−0.38	−0.39	−0.15	1.00
size	−0.62	−0.18	0.56	0.04	0.65	0.37	0.28	−0.38	1.00
own	−0.02	−0.02	0.02	0.02	−0.02	0.27	−0.04	−0.02	0.01	1.00
inf	−0.18	−0.23	0.49	−0.01	0.23	0.08	0.05	−0.17	0.17	0.05	1.00
gdp	−0.11	0.00	0.05	0.01	0.00	0.03	0.02	0.18	0.00	0.00	0.01	1.00

Table 5. Test of autocorrelation and heteroskedasticity

No.	Test	F-statistic	p-values	H0
1	Wooldridge test for autocorrelation in panel data	11.946	0.0015	Reject
2	Breusch-Pagan/Cook-Weisberg test for heteroskedasticity	3.67	0.0554	Accept

Table 6. SGMM results

Group variable: BANK				Number of obs =		376
Time variable: year				Number of groups =		35
Number of instruments = 31				Obs per group: min =		10
Wald chi2(12) = 53,599.91				avg =		10.74
Prob > chi2 = 0.000				max =		12
tobin_q	Coef.	Corrected Std. Err.	z	P > z	[95% Conf.	Interval]
ltobin_q	1.430	0.695	2.060	0.040	0.068	2.793
car	0.533	0.059	9.040	0.000	0.417	0.648
npl	−7.899	0.685	11.540	0.000	−9.241	−6.557
cir	0.968	0.074	13.030	0.000	0.822	1.113
roe	2.006	0.553	3.630	0.000	0.923	3.090
ldr	3.553	1.088	3.260	0.001	1.420	5.686
lev	−0.010	0.056	−0.170	0.865	−0.120	0.101
sen	−1.107	0.037	29.730	0.000	−1.180	−1.034
own	−3.278	1.657	−1.980	0.048	−6.525	−0.031
lroe	0.502	0.512	0.980	0.327	−0.501	1.505
inf	17.010	1.906	8.920	0.000	13.274	20.746
gdp	0.350	0.034	10.430	0.000	0.284	0.415
_cons	−0.980	0.629	−1.560	0.119	−2.213	0.253
Arellano-Bond test for AR(1) in first differences: z = −1.17 Pr > z = 0.241
Arellano-Bond test for AR(2) in first differences: z = −1.06 Pr > z = 0.287
Sargan test of overid. restrictions: chi2(18) = 15.25 Prob > chi2 = 0.644
(Not robust but not weakened by many instruments.)
Hansen test of overid. restrictions: chi2(18) = 5.73 Prob > chi2 = 0.997
(Robust but weakened by many instruments.)
Difference-in-Hansen tests of exogeneity of instrument subsets:
GMM instruments for levels
Hansen test excluding group: chi2(9) = 3.38 Prob > chi2 = 0.947
Difference (null H = exogenous): chi2(9) = 2.35 Prob > chi2 = 0.985
iv(tobin_q)
Hansen test excluding group: chi2(17) = 5.69 Prob > chi2 = 0.995
Difference (null H = exogenous): chi2(1) = 0.04 Prob > chi2 = 0.843
iv(npl)
Hansen test excluding group: chi2(17) = 4.66 Prob > chi2 = 0.999
Difference (null H = exogenous): chi2(1) = 1.07 Prob > chi2 = 0.300
iv(lroe)
Hansen test excluding group: chi2(17) = 5.69 Prob > chi2 = 0.995
Difference (null H = exogenous): chi2(1) = 0.04 Prob > chi2 = 0.840
iv(ldr)
Hansen test excluding group: chi2(17) = 3.32 Prob > chi2 = 1.000
Difference (null H = exogenous): chi2(1) = 2.41 Prob > chi2 = 0.121
iv(size)
Hansen test excluding group: chi2(17) = 5.62 Prob > chi2 = 0.995
Difference (null H = exogenous): chi2(1) = 0.12 Prob > chi2 = 0.734

Table

No.	Code	Name of bank
1	ABB	An Binh Bank
2	ACB	Asia Commercial Bank
3	BAB	Bac A Bank
4	BID	Bank for Investment and Development of Vietnam
5	BVB	Bao Viet Bank
6	CTG	Vietnam Joint Stock Commercial Bank for Industry and Trade
7	EAB	Dong A Commercial Joint Stock Bank
8	EIB	Vietnam Export Import Commercial Joint Stock Bank
9	GDB	Viet Capital Bank
10	HDB	Housing Development Commercial Joint Stock Bank
11	KLB	Kien Long Commercial Joint Stock Bank
12	LPB	Lien Viet Post Joint Stock Commercial Bank
13	MBB	Military Commercial Joint Stock Bank
14	MSB	Vietnam Maritime Commercial Joint Stock Bank
15	NAB	Nam A comercial Join Stock Bank
16	NVB	National Citizen Bank
17	PGB	Petrolimex Group Commercial Joint Stock Bank
18	PVF	Vietnam Public Joint Stock Commercial Bank
19	SCB	Sai Gon Joint Stock Commercial Bank
20	SEAB	SouthEast Asia Commercial Joint Stock Bank
21	SGB	Saigon bank for industry and trade
22	SHB	Saigon—Ha Noi Commercial Joint Stock Bank
23	STB	Sai Gon Thuong Tin Commercial Joint Stock Bank
24	TCB	Vietnam Technical Commercial Bank
25	TPB	Tienphong commercial Joint Stock Bank
26	VAB	Vietnam Asia Commercial Joint Stock Bank
27	VCB	Joint Stock Commercial Bank for Foreign Trade of Vietnam
28	VIB	Vietnam International Commercial Joint Stock Bank
29	VPB	Vietnam Prosperity Joint Stock Commercial Bank
30	OCB	Orient Commercial Joint Stock Bank
31	VBB	Vietnam Thuong Tin Commercial Joint Stock Bank
32	Agribank	Vietnam Bank for Agriculture and Rural Development
33	GP Bank	Global Petro Commercial Joint Stock Bank
34	Ocean	Ocean Commercial One Member Limited Library Bank
35	Construction	Vietnam Construction Bank

Rostami, M. (2015b). The effect of ownership structure on Tobin’s Q Ratio. Journal of Research in Business, Economics and Management, 3 (2), 161–171. Retrieved from http://scitecresearch.com/journals/index.php/jrbem/article/view/247

 Google Scholar

Kaur, H. V. (2010). Analysis of banks in India - A CAMEL approach. Global Business Review, 11(2), 257–280. https://doi.org/https://doi.org/10.1177/097215091001100209

 Google Scholar

Sangmi, M., & Nazir, T. (2010). Analyzing financial performance of commercial banks in India: Application of CAMEL model. Pakistan Journal Commercial Social Sciences, 1(2010), 1–10. https://www.econstor.eu/handle/10419/187999

 Google Scholar

Soni, R. (2012). Applicability of CAMELS rating for supervisory regulation of the Indian banking system. Vishwakarma Business Review, 2(2), 14–20.

 Google Scholar

Rozzani, N., & Rahman, R. A. (2013). Camels and performance evaluation of banks in Malaysia: Conventional versus Islamic. Journal of Islamic Finance and Business Research, 2(1), 36–45.

 Google Scholar

Rahman, M. M., Hamid, M. K., & Khan, M. A. M. (2015). Determinants of bank profitability: Empirical evidence from Bangladesh. International Journal of Business and Management, 10(8), 135–149. https://doi.org/https://doi.org/10.5539/ijbm.v10n8p135

 Google Scholar

Olweny, T., & Shipho, T. M. (2011). Effects of banking sectoral factors on the profitability of commercial banks in Kenya. Economics and Finance Review, 1(5), 1–30. http://wwww.businessjournalz.org/efr

 Google Scholar

Dang, U. (2011). The CAMEL rating system in banking supervision: A case study of Arcada. University of Applied Sciences, International Business.

 Google Scholar

Balango, T. K., & Rao, K. (2017). The effect of NPL on profitability of banks with reference to commercial bank of Ethiopia. Business and Management Research Journal, 7(5), 45–50.

 Google Scholar

Kingu, P. S., Macha, D. S., & Gwahula, D. R. (2018). Impact of non-performing loans on bank’s profitability: Empirical evidence from commercial banks in Tanzania. International Journal of Scientific Research and Management, 6(1), 71–79. https://doi.org/https://doi.org/10.18535/ijsrm/v6i1.em11

 Google Scholar

Patwary and Tasneem. (2019). Impact of non-performing loan on profitability of banks in Bangladesh: A study from 1997 to 2017. Global Journal of Management and Business Research: C Finance, 19(1), 13–27.

 Google Scholar

Roman, A., & Sargu, A. C. (2013). Analysing the financial soundness of the commercial banks in Romania: An approach based on the camels framework. Procedia Economics and Finance, 6(2013), 703–712. https://doi.org/https://doi.org/10.1016/S2212-5671(13)00192-5

 Google Scholar

Liu, J., & Pariyaprasert, W. (2014). Determinants of bank performance: The application of the CAMEL model to banks listed in China’s stock exchanges from 2008 to 2011. AU-GSB e-JOURNAL, 7(2), 80–95. http://www.assumptionjournal.au.edu/index.php/AU-GSB/article/view/1067

 Google Scholar

Jha, S., & Hui, X. (2012). A comparison of financial performance of commercial banks: A case study of Nepal. African Journal of Business Management, 6(25), 7601–7611. https://doi.org/https://doi.org/10.5897/AJBM11.3073

 Google Scholar

Golin, J. (2001). The bank credit analysis handbook: A guide for analysts, bankers and investors. John Wiley & Sons Pre Ltd.

 Google Scholar

Elyor, S. (2009). Factors affecting the performance of foreign banks in Malaysia. Universiti Utara Malaysia.

 Google Scholar

Sarker, A. (2006). CAMELS rating system in the context of Islamic banking: A proposed ‘S’ for Shariah framework. Journal of Islamic Economics, Banking and Finance, 2(2), 1–26. https://ibtra.com/pdf/journal/v2_n2_article4.pdf

 Google Scholar

Avkiran, N. K., & Cai, L. (2012). Predicting bank financial distress prior to crises. The University of Queensland, Australia.

 Google Scholar

Kumari, I. G. (2017). A study of the financial performance on foreign commercial banks in Sri Lanka: An application of CAMEL Rating System. Economics, Commerce and Trade Management: An International Journal, 1 (1), 59–70. https://airccse.com/ectij/papers/1117ectij05.pdf

 Google Scholar

Boyd, J., & Smith, B. (1998). Capital market imperfections in a monetary growth model. Economic Theory, 11(2), 241–273. https://doi.org/https://doi.org/10.1007/s001990050187

 Google Scholar

Guru, B., Staunton, J., & Balashanmugam, B. (2002). Determinant of commercial bank profitability in Malaysia. Sydney: 12th Annual Australian Finance and Banking Conference.

 Google Scholar

Jiang, G., Tang, N., Law, E., & Sze, A. (2003). Determinants of Bank Profitability in Hong Kong.

 Google Scholar

Boyd, J. H., & Champ, B. (2006). Inflation, Banking, and Economic Growth. Federal Reserve Bank of Cleveland.

 Google Scholar

Fadzlan, S. (2009). Determinants of bank profitability in a developing economy: Empirical evidence from the China banking sector. Journal of Asia-Pacific Business, 10(4), 201–307. https://doi.org/https://doi.org/10.1080/10599230903340205

 Google Scholar

Miguel Á., T.-Z., Martínez, F. V., & Preciado, V. H. T. (2018). Effects of inflation on financial sector performance: New evidence from panel quantile regressions. Investigación Económica, LXXVII, (303), 94–129. https://doi.org/https://doi.org/10.22201/fe.01851667p.2018.303.64156

 Google Scholar

Gilbert, B., & Jaya, S. (2019). Inflation and Profitability of Commercial Banks in Rwanda: A Case Study of Bank of Kigali. International Journal of Business and Management, 14(10), 35–43. https://doi.org/https://doi.org/10.5539/ijbm.v14n10p35

 Google Scholar

Cetin, H. (2019). Inflation and bank profitability: G20 countries banks panel data analysis. In Phuket, Thailand: 2019 international conference on management science and industrial engineering (pp. 168–172). Association for Computing Machinery.

 Google Scholar

Mbabazize, R. N., Turyareeba, D., Ainomugisha, P., & Rumanzi, P. (2020). Monetary policy and profitability of commercial banks in Uganda. Open Journal of Applied Sciences, 10(10), 625–653. https://doi.org/https://doi.org/10.4236/ojapps.2020.1010044

 Google Scholar

Almansour, A. Y., Alzoubi, H. M., Almansour, B. Y., & Almansour, Y. M. (2021). The effect of inflation on performance: an empirical investigation on the banking sector in Jordan. Journal of Asian Finance, Economics and Business, 8(6), 0097–35. https://doi.org/https://doi.org/10.13106/jafeb.2021.vol8.no6.0097

 Google Scholar

Sufian, F., & Habibullah, M. S. (2010). Assessing the impact of financial crisis on bank performance, empirical evidence from Indonesia. ASEAN Economic Bulletin, 27(3), 245–262. https://doi.org/https://doi.org/10.1355/ae27-3a

 Google Scholar

Emase, M. A. (2017). Effect of macroeconomic factors on the profitability of commercial banks listed at the Nairobi securities exchange in Kenya. The School of Business And Public Management, KCA University. http://41.89.49.13:8080/xmlui/handle/123456789/1325

 Google Scholar

Tahsin, K., & Gülşah, Ş. (2018). Analysis of macroeconomic factors which affect performance of global finance centers. Asian Economic and Financial Review, 8(1), 63–70. https://doi.org/https://doi.org/10.18488/journal.aefr.2018.81.63.70

 Google Scholar

Matar, A., Al-Rdaydeh, M., & Odeh, M. (2018). Factors affecting the corporate performance: Panel data analysis for listed firms in Jordan. Academy of Accounting and Financial Studies Journal, 22(6), 1–10. https://www.abacademies.org/articles/Factors-Affecting-the-Corporate-Performance-Panel-Data-Analysis-for-Listed-Firms-in-Jordan-1528-2635-22-6-315.pdf

 Google Scholar

Booth, L., Aivazian, V., Demirguc-Kunt, A., & Maksimovic, V. (2001). Capital structures in developing countries. The Journal of Finance, 56(1), 87–130. https://doi.org/http://dx.doi.org/10.1111/0022-1082.00320

 Google Scholar

Onaolapo, A. A., & Kajola, S. O. (2010). Capital structure and firm performance: Evidence from Nigeria. European Journal of Economics, Finance and Administrative Sciences, 25, 70–82.

 Google Scholar

Salim, M., & Yadav, R. (2012). Capital structure and firm performance: Evidence from Malaysian listed companies. Procedia - Social and Behavioral Sciences, 65(2012), 156–166. https://doi.org/https://doi.org/10.1016/j.sbspro.2012.11.105

 Google Scholar

Iavorskyi, M. (2013). The impact of capital structure on firm performance: Evidence from Ukraine. Thesis. Kyiv School of Economics.

 Google Scholar

La Porta, R., Lopez‐de‐Silanes, F., & Shleifer, A. (2002). Government ownership of banks. The Journal of Finance, 57(1), 265–301. https://doi.org/https://doi.org/10.1111/1540-6261.00422

 Google Scholar

Barth, J. R., Caprio, G., Jr., & Levine, R. (2001). Banking Systems Around the Globe: Do Regulation and Ownership Affect Performance and Stability? Prudential Supervision: What Works and What Doesn’t. University of Chicago Press.

 Google Scholar

Cornett, M. M., McNutt, J. J., & Tehranian, H. (2009). Corporate governance and earnings management at large US bank holding companies. Journal of Corporate Finance, 15(4), 412–430. https://doi.org/https://doi.org/10.1016/j.jcorpfin.2009.04.003

 Google Scholar

Su, D., & He, X. (2012). Ownership structure, corporate governance and productive efficiency in China. Journal of Productivity Analysis, 38(3), 303–318. https://doi.org/https://doi.org/10.1007/s11123-011-0257-8

 Google Scholar

Robin, I., Salim, R., & Bloch, H. (2018). Financial performance of commercial banks in the post-reform era: Further evidence from Bangladesh. Economic Analysis and Policy, 58(C), 43–54. https://doi.org/https://doi.org/10.1016/j.eap.2018.01.001

 Google Scholar