Ownership structure and bank risk-taking in ASEAN countries: A quantile regression approach

Figures & data

Table 1. Definitions of variables

Variables	Measure
Panel A: Dependent variable (bank risk-taking)
Z-score	Z = [Return on assets ratio + (Equity/Total assets)]/Std(Return on assets ratio)
Altman’s Z-score (AZ-score)	AZ-score = 1.2x1 + 1.4x2 + 3.3x3 + 0.6x4 + 1.0x5 where x1 is the working capital/total assets, x2 the retained earnings/total assets, x3 the earnings before interest and taxes/total assets, x4 the market value of equity/total assets, and x5 is the sales/total assets.
Panel B: Ownership structure
Foreign ownership (FOW)	The proportion of foreign shares to total shares
State ownership (SO)	The proportion of state shares to total shares
Ownership concentration (OWC)	A dummy variable which equals 1 for banks having at least one shareholder which holds a 10% share or more and otherwise is equal to 0
Panel C: Other control variable
Diversification index (DIV)	We use a diversification index that is increasing in the degree of diversification. It is defined as: $1-\left|\frac{Netinterestincome-Otheroperatingincome}{Totaloperatingincome}\right|$
Bank size (SIZE)	The natural logarithm of total assets
Net interest margin (NIM)	The accounting value of bank’s net interest revenue as a share of its average interest-bearing (total earning) assets
Listed bank (IPO)	A dummy variable which equals 1 for listed banks, otherwise 0
Bank crisis (BCR)	A dummy variable which equals 1 if the country is going through a systemic crisis in that year, otherwise 0
Assets quality (ASQ)	The ratio of loan loss provisions to total assets
Bank concentration (CR3)	Concentration Ratio for three largest banks = $\sum _{n=1}^3\mathrm{b}\mathrm{r}\mathrm{a}\mathrm{n}\mathrm{c}\mathrm{h}\mathrm{n}/\sum _{k=1}^i\mathrm{b}\mathrm{r}\mathrm{a}\mathrm{n}\mathrm{c}\mathrm{h}\mathrm{k}$, n = 1; …; 3 are the three largest banks by number of bank branches
GDP per capita (GDP)	Natural logarithm of GDP per capita in a year

Table 2. Descriptive statistics

Variable	Obs	Mean	Std. Dev	Min	Q25	Q50	Q75	Max	Skewness	Kurtosis
Z-score	1,067	27.172	18.136	−2.619	13.449	23.518	37.942	95.516	0.825	3.205
AZ-score	1,067	8.603	6.955	−118.172	6.000	7.697	9.911	60.162	−3.541	117.349
SO	1,067	0.207	0.344	0.000	0.000	0.000	0.285	1.000	1.507	3.712
FOW	1,067	0.161	0.266	0.000	0.000	0.000	0.226	1.000	1.954	5.974
OWC	1,067	0.848	0.359	0.000	1.000	1.000	1.000	1.000	−1.940	4.765
DIV	1,067	0.371	1.397	−29.188	0.304	0.496	0.693	1.000	−16.471	319.562
SIZE	1,067	9.774	0.769	7.447	9.228	9.742	10.351	11.606	0.027	2.632
NIM	1,067	0.034	0.026	−0.029	0.021	0.031	0.039	0.278	3.643	25.897
IPO	1,067	0.343	0.475	0.000	0.000	0.000	1.000	1.000	0.661	1.437
BCR	1,067	0.837	0.370	0.000	1.000	1.000	1.000	1.000	−1.824	4.327
ASQ	1,067	0.007	0.037	−0.036	0.001	0.003	0.007	1.174	29.381	919.125
CR3	1,067	0.589	0.139	0.288	0.497	0.552	0.670	0.920	0.437	2.761
GDP	1,067	3.470	0.410	2.530	3.239	3.409	3.740	4.810	0.931	4.417

This table presents the distribution of variables by showing the number of observations (Obs.), mean, standard deviation (Std. Dev.), minimum (Min.), 25th quartile (Q25), 75th quartile (Q75), and maximum (Max). This table also shows Altman’s Z-score. We adopt the Z-score equation exactly as it was proposed by Altman (1968). See Table 1 for variable definitions.

Table 3. Correlation matrix of main regression variables

	Z-score	SO	FOW	CTR	DIV	SIZE	NIM	IPO	BCR	ASQ	CR3	GDP
Z-score	1.000
SO	−0.085	1.000
	(0.005)
FOW	0.104	−0.249	1.000
	(0.001)	(0.000)
CTR	0.180	0.218	0.132	1.000
	(0.000)	(0.000)	(0.000)
DIV	0.132	−0.040	0.033	0.016	1.000
	(0.000)	(0.197)	(0.282)	(0.601)
SIZE	0.232	0.051	0.178	0.121	0.037	1.000
	(0.000)	(0.093)	(0.000)	(0.000)	(0.228)
NIM	−0.031	−0.040	−0.006	−0.002	0.067	−0.332	1.000
	(0.312)	(0.188)	(0.840)	(0.955)	(0.029)	(0.000)
IPO	0.197	−0.164	0.107	−0.041	0.083	0.444	0.026	1.000
	(0.000)	(0.000)	(0.000)	(0.182)	(0.007)	(0.000)	(0.397)
BCR	0.082	−0.071	0.007	0.047	−0.014	0.144	−0.102	0.030	1.000
	(0.008)	(0.021)	(0.820)	(0.129)	(0.639)	(0.000)	(0.001)	(0.322)
ASQ	−0.075	0.016	−0.016	0.018	−0.015	−0.080	−0.031	−0.033	−0.015	1.000
	(0.015)	(0.605)	(0.592)	(0.551)	(0.619)	(0.009)	(0.320)	(0.287)	(0.624)
CR3	−0.024	0.074	0.028	0.123	0.027	−0.286	0.237	−0.188	−0.429	0.051	1.000
	(0.439)	(0.015)	(0.355)	(0.000)	(0.374)	(0.000)	(0.000)	(0.000)	(0.000)	(0.094)
GDP	0.448	−0.145	0.135	0.196	0.106	0.620	−0.187	0.446	0.229	−0.034	−0.170	1.000
	(0.000)	(0.000)	(0.000)	(0.000)	(0.001)	(0.000)	(0.000)	(0.000)	(0.000)	(0.269)	(0.000)

P-values are reported in parentheses below each correlation estimate. See Table 1 for variable definitions.

Table 4. Independent variables by bank risk-taking quartiles

Variable	First quartile	Second quartile	Third quartile	Fourth quartile	p-value of Wilcoxon Test (fourth quantile-first quantile)
SO	0.195	0.204	0.215	0.209	0.215
FOW	0.149	0.162	0.169	0.157	0.623
OWC	0.683	0.764	0.871	0.893	<0.01
DIV	0.313	0.296	0.395	0.381	<0.01
SIZE	8.715	9.942	10.402	9.272	<0.01
NIM	0.046	0.041	0.037	0.021	0.514
IPO	0.313	0.286	0.382	0.357	0.243
BCR	0.752	0.768	0.812	0.856	<0.01
ASQ	0.007	0.006	0.007	0.007	0.823
CR3	0.491	0.511	0.586	0.601	<0.01
GDP	3.405	3.513	3.306	3.569	0.243

The t-statistic is for a difference of means test from the first to the fourth quartile.

Table 5. The effect of ownership structure on bank risk-taking

Variables	OLS	S-GMM	Quantile Regressions
			10th	20th	30th	40th	50th	60th	70th	80th	90th
	(1)	(2)	(3)	(4)	(5)	(6)	(7)	(8)	(9)	(10)	(11)
SO	−1.326	−24.698**	−4.464***	−5.542**	−4.168*	−2.427	−1.077	0.380	3.571	5.191**	12.061***
FOW	2.009	−21.989	−5.265***	−7.482***	−5.244*	−1.985	−0.275	3.086*	3.353*	8.065***	11.472**
OWC	5.025***	24.887***	1.511	2.217	4.782**	6.537***	7.922***	7.138***	7.752***	4.645**	−2.062
DIV	1.028***	0.386*	1.128***	0.721	0.506	0.632	0.764**	0.884*	1.068*	1.218	1.445*
SIZE	−1.605*	−0.088	3.449***	2.626**	2.650*	1.033	0.507	−0.375	−4.392**	−6.866	−11.885***
NIM	11.915	196.816	62.060***	60.754**	58.405*	34.217	24.300	24.228	13.413	−12.708	−44.437
IPO	0.620	12.873	1.243	0.782	0.699	1.228	1.402	0.230	0.191	−0.037	1.058
BCR	−0.462	−0.143	2.700*	0.820	−1.116	−4.211**	−4.767***	−4.666**	−3.556	−2.31	0.340
ASQ	−31.490**	−7.522	−2.901	−8.439	−12.969	−17.874	−20.664	−22.464	−28.414	−34.561	−44.096
CR3	2.437	6.642	−0.789	2.669	9.334	9.893**	8.287*	−3.163	−11.910*	−17.131	−15.852
GDP	20.042***	9.748*	−1.447	5.285**	15.854***	19.432***	20.589***	21.541***	27.146***	29.17	35.435***
R2/Pseudo R2	0.260		0.054	0.046	0.078	0.125	0.160	0.185	0.198	0.220	0.197
Hansen J test (p-value)		0.173
AR(2) (p-value)		0.204
No. of instruments		30

Superscripts *, **, and *** indicate statistical significance at 10%, 5%, and 1% respectively. See Table 1 for definitions of variables.

Table 6. Inter-quantile comparison of the coefficient

Panel A: Inter comparison of the coefficient of SO variable
	Quantile regression
	20th	30th	40th	50th	60th	70th	80th	90th
10th	0.26	0.01	0.58	1.6	2.48	5.55**	10.18***	19.69***
20th		0.39	1.7	3.38*	4.55**	8.41***	13.18***	22.11***
30th			0.8	1.85	2.91*	6.11**	8.93***	17.97***
40th				0.83	1.72	4.94**	7.61***	16.94***
50th					0.83	4.11**	6.64***	15.72***
60th						3.21*	4.58**	12.53***
70th							0.6	6.71***
80th	0.26	0.01	0.58	1.6	2.48	5.55**	10.18***	19.69***
Panel B: Inter comparison of the coefficient of FOW variable
Quantile	Quantile regression
	20th	30th	40th	50th	60th	70th	80th	90th
10th	0.28	0	0.86	1.89	5.73**	3.34*	8.38***	9.21***
20th		0.37	1.64	2.43	4.83**	3.71*	7.69***	8.49***
30th			1.39	2.1	4.79**	3.50*	8.22***	8.59***
40th				0.68	3.56*	1.92	6.99***	7.26***
50th					2.27	1.08	5.57**	6.42**
60th						0.01	2.89*	3.78*
70th							2.6*	3.19*
80th								0.87
Panel C: Inter comparison of the coefficient of OWC variable
	Quantile regression
	20th	30th	40th	50th	60th	70th	80th	90th
10th	0.32	4.09**	9.05***	14.47***	8.27***	5.20**	1.48	1.06
20th		4.53**	9.92***	15.16***	7.65***	4.61**	0.94	1.57
30th			2.88*	5.56**	1.93	1.41	0.00	4.01**
40th				1.77	0.17	0.28	0.64	6.7***
50th					0.48	0.01	2.18	9.54***
60th						0.12	1.44	8.46***
70th							2.43	8.91***
80th								5.88**

This table reports the F-tests for the equality of quantile slope coefficients of SO, FOW, OWC (present on panels A, B, and C respectively) across the various pairs of quantiles. ***, **, and * indicate significance at the 1%, 5%, and 10% levels respectively. One thousand bootstrap replications are used in the quantile regressions.

Figure 1. Quantile and OLS estimates of SO on Z-score.

Table 7. The effect of ownership structure on bank risk-taking—Quantile regression with instrument variables

Variable	Quantile regressions
	10th	20th	30th	40th	50th	60th	70th	80th	90th
SO	−10.575***	−7.905**	−6.138**	−4.547*	−2.499	−0.423	1.375	3.864	7.665*
FOW	−14.357***	−11.066**	−8.888**	−6.926*	−4.402	−1.842	0.373	3.442	8.127*
CTR	0.757	1.681	2.292	2.843	3.552*	4.271**	4.893**	5.754**	7.070**
DIV	−1.513**	−0.964	−0.601	−0.274	0.147	0.573	0.942**	1.454***	2.235***
SIZE	11.450***	8.934***	7.270***	5.770***	3.840	1.884	0.191	−2.155	−5.736***
NIM	206.428***	173.212***	151.230***	131.431***	105.947	80.117***	57.754*	26.782	−20.507
IPO	−4.064	−3.708	−3.472	−3.260	−2.987	−2.710	−2.471	−2.139	−1.632
BCR	−5.641	−4.810	−4.259	−3.764	−3.126	−2.479	−1.919	−1.144	0.040
ASQ	115.438	277.653	385.005	481.696	606.153	732.294	841.510	992.766	1223.711
CR3	−6.727	−7.787	−8.489	−9.121	−9.935	−10.759	−11.473	−12.462	−13.972
GDP	1.830	5.709*	8.276***	10.588***	13.564***	16.580***	19.191***	22.808***	28.330***

This table presents the result in estimation of the structural quantile functions defined by Chernozhukov and Hansen (2008) using the method of Machado and Silva (2019). Superscripts *, **, and *** indicate statistical significance at 10%, 5%, and 1%, respectively. See Table 1 for variable definitions.

Table 8. The effect of ownership structure on bank risk-taking as measured by Altman’s Z-score

Variables	Quantile Regressions
	10th	20th	30th	40th	50th	60th	70th	80th	90th
SO	−1.064**	−0.811***	−0.657**	−0.311	0.192	0.383	1.119**	1.676***	1.222
FOW	−0.298	−0.023	0.055	0.307	0.125	0.020	0.734	0.455	1.101
OWC	0.245	0.698***	0.819	0.787**	−0.180	−0.451	−0.621	0.392*	−1.246
DIV	0.348***	0.379***	0.409***	0.437***	0.467***	0.389***	0.131	0.159	0.121
SIZE	−0.988***	−1.200***	−1.358***	−1.905***	−2.584***	−2.751***	−3.456***	−4.597***	−6.965***
NIM	59.441***	63.181***	62.451***	61.267***	68.053***	73.314***	69.583***	60.530***	48.775***
IPO	0.271	0.269	0.346	0.366	0.504*	0.247	−0.126	−0.281	0.583
BCR	1.018**	0.264	0.453	−0.214	−0.066	0.285	0.248	0.610	−0.133
ASQ	−103.661***	−104.123***	−104.925	−105.671***	−106.529***	−102.669***	−38.321***	−34.732***	−42.451***
CR3	−0.103	−1.124	−0.462	−1.269	−0.413	0.285	−1.178	−1.578	−2.405
GDP	2.269***	2.243***	1.952	2.420***	2.930***	3.119***	4.173***	5.856***	8.938***
Pseudo R2	0.307	0.254	0.219	0.196	0.186	0.191	0.201	0.244	0.292

Note: Superscripts *, **, and *** indicate statistical significance at 10%, 5%, and 1% respectively. See Table 1 for variable definitions.

Altman, E. I. (1968). Financial ratios, discriminant analysis and the prediction of corporate bankruptcy. The Journal of Finance, 23(4), 589–19. https://doi.org/10.1111/j.1540-6261.1968.tb00843.x

 Web of Science ®Google Scholar

Chernozhukov, V., & Hansen, C. (2008). Instrumental variable quantile regression: A robust inference approach. Journal of Econometrics, 142(1), 379–398. https://doi.org/10.1016/j.jeconom.2007.06.005

 Web of Science ®Google Scholar

Machado, J. A., & Silva, J. S. (2019). Quantiles via moments. Journal of Econometrics, 213(1), 145–173. https://doi.org/10.1016/j.jeconom.2019.04.009

 Web of Science ®Google Scholar