The conundrum of bank capital structure: Empirical evidence from Pakistan

Figures & data

Table 1. Capital Adequacy Ratio of Commercial Banks

		2013	2014	2015	2016	2017
Minimum Require ments set by SBP	Total Capital plus CCB (%)	10	10	10.25	11.25	11.875
Sample Scheduled Commercial Banks (2006–2017)	Minimum CAR (%)	8	9	7	11	10
	Maximum CAR (%)	65	36	41	54	54
	Average CAR (%)	19	17	16	18	18
	Banks meeting the minimum requirements	22	23	23	22	22
	Banks not meeting the minimum requirements	2	1	1	2	2

Note: Author’s Calculation.

Table 2. Descriptive Statistics

Variables	Mean	S.D.	Min	Max
CAR	.188	.131	.006	.857
BM	.032	.013	−.008	.075
ROE	.081	1.705	−14.74	24.018
NPL	.129	.146	0	.784
CR	.432	.107	.013	.709
Z	15.943	11.356	−2.574	85.295
PEER	.186	.015	.154	.222
HHI	.318	.279	.083	.701

Note: No. of Banks = 24, Years = 12, No. of firm-year Observations: 288.

Table 3. Correlations

Variables	(1)	(2)	(3)	(4)	(5)	(6)	(7)	(8)	VIF
(1) CAR	1.000
(2) BM	0.173*	1.000							1.09
(3) PEER	−0.236*	0.003	1.000						1.87
(4) ROE	0.171*	0.055	−0.110	1.000					1.04
(5) NPL	0.488*	−0.098	−0.204*	0.086	1.000				1.33
(6) CR	−0.372*	0.069	0.324*	−0.084	−0.142*	1.000			1.24
(7) Z	−0.022	0.223*	0.127*	0.050	−0.415*	−0.113	1.000		1.39
(8) HHI	0.078	0.135*	0.648*	−0.106	−0.075	0.324*	0.167*	1.000	1.90

*shows the significance at the .05 level.

Table 4. Estimation Results

Independent Variables	Pooled OLS (2)	FE (3)	GMM (4)
	β/(t)	β/(t)	β/(z)
CARt-1	-	-	0.676*** (3.42)
Bank-specific variables
BM	1.865*** (4.18)	0.926 (0.77)	0.241 (0.48)
ROE	0.007** (2.10)	0.003* (1.92)	0.016*** (2.98)
Bank risk-based variables
NPL	0.395*** (9.03)	0.178* (1.77)	0.247** (2.18)
LTAR	−0.384*** (−6.52)	−0.221*** (−3.04)	−0.165*** (−3.38)
Z	0.001 (0.89)	0.005*** (5.48)	0.002 (1.21)
Industry-specific variables
PEER	−2.979*** (−5.46)	−1.618** (−2.45)	−0.65** (−2.45)
HHI	0.240*** (6.78)	0.108** (2.43)	0.113* (1.91)
Financial crisis dummy
DUMMY	−0.049*** (−2.76)	−0.019*** (−2.92)	−0.036** (2.25)
Constant	0.725*** (7.38)	0.424*** (5.04)	0.158** (2.40)
Number of observations	288	288	240
R-square	0.497
R-square within		0.319
Hausman test (FE vs. RE)		27.81***
Wald Chi-square			390.46***
AR 1 (p-value)			[0.010]
AR 2 (p-value)			[0.326]
Number of Instruments			64

Note: CAR is the dependent variable; $CA{R}_{it-1}$ is the lagged dependent variable; Arellano–Bond suggests the second lags of the dependent variable and all the feasible lags thereafter, the study employed data for 12 time periods, which yield 64 instruments (55 GMM-type instruments for the dependent variable, 9 standard instruments are given by the first difference of the predictors and the constant); Arellano-Bond order 1 (2) test for first (second) order serial correlation (H₀: no autocorrelation);*** p < 0.01, ** p < 0.05, * p < 0.1; t-statistics of pooled OLS and FE estimators while Z-statistics of GMM model are reported in parentheses.

Table 5. Summary of Hypotheses Tested

Hypotheses Formulated	H0	H0 (Decision)
H1: Management quality is significantly associated with a bank’s CAR.	β1 = 0	Not Rejected
H2: The alternative cost of capital is significantly related to banks’ CAR.	β2 = 0	Rejected
H3: Default risk is positively related to banks’ CAR.	β3 ≤ 0	Rejected
H4: Credit risk has a negative relationship with banks’ CAR.	β4 ≥ 0	Rejected
H5: Bank’s risk index has a negative relationship with a bank’s CAR.	β5 ≥ 0	Rejected
H6: The average CAR of the sector is positively associated with the bank’s CAR.	β6 ≤ 0	Rejected
H7: There is a significant association of the Herfindahl-Hirschman Index with Banks’ CAR.	β7 = 0	Rejected
H8: The financial crisis has a negative relationship with banks’ CAR.	β8 ≥ 0	Rejected