Potential risks of liquidity and credit affecting the efficiency of Islamic banks in Bangladesh

Figures & data

Figure 1. Share of the Islamic banking industry in the overall banking industry.

Source: Quarterly report on Developments of Islamic Banking in Bangladesh.

Table 1. Summary of the literature showing the relation of the liquidity and credit risk with bank performance

Relationship of liquidity and credit risk with bank performance	Studies	Mostly used measurement for liquidity risk	Mostly used measurement for credit risk	Most used measurement for bank performance or profitability.
Positive relation	(Ajibike & Aremu, 2015; Alshatti, 2015; Ghenimi et al., 2017; Rahman & Banna, 2015).	* Deposit, * Cash reserve, * Liquidity gap, * Liquidity coverage ratio, * Net stable fund ratio, * Quick ratio, * Capital to total assets, * Net credit Facilities to total assets, * Acid liquid assets to total assets, * Berger–Bouwman (BB), * Cash to Total Assets, *Liquid Assets to current liabilities, * Loan (investment) to deposit ratio, * Logarithm of (Assets-Liabilities).	* Non-performing loan (investment) to total loans (investments) and advances, * Net Charge Off to Total Loans (investments) and Advances, * Pre-Provision Profit to Net Total Loans (investments) and Advances, * Loan (investment) loss provision, * Loan (investment) Loss Reserves to gross Loans (investments), * cost per loan (investment), * Loan (investment) Provision to Non-Performing Loans (investments), * Loan (investment) Provision to Total Assets, * Provision for non-performing loans (investments) to total loans (investments).	Return on Equity, Return of Asset, Net interest Margin.
Negative relation	(Djan et al., 2016; Ekinci & Poyraz, 2019; Hakimi & Zaghdoudi, 2017; Hassan et al., 2019; Kodithuwakku, 2015; Noman et al., 2015).

Table 2. Efficiency and its determinants around the world

Country/Area	Model used	Bank-specific determinants which have a significant impact (relationship)	Studies
Ethiopia	DEA, Tobit regression	Deposit and liquidity (+)	(Tesfay, 2016)
Cambodia	DEA, panel regression (M1: Value-added approach and M2: Operating approach)	Ln total assets (+), Z-score (-), Foreign dummy (-), Specialized banks dummy (+), MFIs dummy (M1 -, M2 +), Diversification (+).	(Okuda & Aiba, 2016)
Ghana	DEA, binary logistic regression	Profitability (+), bank size, and bank funding quality (-)	(Adusei et al., 2016)
Turkey	DEA, Tobit regression	NPL ratio and personal expenses (- for CBs & + for IBs), Total loans (investments) divided by a total asset (+), where GDP and Inflation (-).	(Batir et al., 2017)
Indonesia	DEA, Tobit regression	Financing intensity, profitability, non-financing expense, and capitalization (+) and trade freedom, GDP, and exchange rate (-).	(Bayuny & Haron, 2017)
Bahrain	DEA and regression	Market share (+ IBs), Income Diversity (+ IBs), Total Assets (-), Equity/Total Assets (− IBs), Net Loans (investments)/Total Assets (+ IBs), Government Variables (− CBs).	(Daly & Frikha, 2017)
Malaysia	DEA, Wilson’s double bootstrap regression	Bank nature, foreign ownership, GDP, ROA (+), where market share, bank size, liquidity (-)	(Azad et al., 2017)
Ten frontier African countries	DEA, truncated bootstrapping approach	Degree of risk (+) and Bank size (-)	(Banya & Biekpe, 2018)
China	DEA, three-stage least square estimator (3-SLS), seemingly unrelated regression (SUR).	Credit risk and Insolvency risk (+) where liquidity risk and capital risk (-).	(Tan & Floros, 2018)
Ghana	DEA, Prais–Winsten (PW) regression, Pooled OLS, Random effect	Board gender diversity (+), Board size (+), Board characteristics, Size(+), Loan (investment) to deposit ratio(+), Age(-)	(Adeabah et al., 2018)
Vietnam	DEA, Tobit regression, GMM	Bank size (+), Liquid asset to total asset (+), Herfindahl–Hirschman Index in terms of total assets (+).	(T. D. Le et al., 2022)
Indonesia	DEA, Tobit regression	Revenue sharing(+), Non performing loan (investment) (-), ROA(+),Capital adequacy ratio (-), Cost to income ratio (+)	(Endri et al., 2022)

Table 3. Inputs and outputs considered in this paper

Classification	Name	Symbol	Definition	Estimation Method
Inputs	Employee expense	PE	Total expenses for all the employees of the organization over the year.	Sum of all the employees’ expenses.
	Deposits	TD	Total deposit amount at the end of the year.	Remaining balance at the end of the year.
	Fixed assets	FA	Total fixed assets at the end of the year.	Year-end balance
Outputs	Total loans (investments)	TL	Total loan (investment) amount disbursed at the end of the year.	Year-end balance
	Other earning assets	OEA	Total earning assets other than loans (investments) at the end of the year.	Year-end balance

Table 4. Description of independent variables

	Indicator	Variable name	Estimation Method	Expected sign
Liquidity risk	LTD	a) Loan (investment)-to-deposit ratio	Total loan (investment)/Total deposit	Negative
	F_gap	b) Financing gap.	Total Risk-weighted asset- Total Liabilities as deposit	Negative
Credit risk	LNNPL	a) Amount of non-performing loan (investment)	ln (year-end balance of the non-performing loan (investment)).	Negative
	NPL ratio	b) The ratio of NPL amount to total loan (investment).	Amount of non-performing loan (investment)/Amount of total loan (investment).	Negative
	LNLLP	c) Amount of loan (investment) loss provision against the non-performing loan (investment).	ln (total amount of loan (investment) loss provision)	Negative
Insolvency Risk	Z score	Measures the financial stability of the bank.	(ROA+ROE)/STDEV of ROA	Positive
External risk	Crisis	Crisis period	The financial crisis period from 2007 through 2009 has been considered a dummy variable.	Negative
Instruments	Age	Age of the Bank	Difference between the current year and the year of establishment of the bank.	Positive
	Branch	Number of branches	The number of branches in each year.	Positive
	ROA	Return on Asset	Net Income/Total Asset	N/A
	ROE	Return on Equity	Net Income/Total Equity	N/A

Figure 2. Overall TE, PTE, and SE Bangladeshi Islamic banks, 2007–2018.

Note: Source: Author’s calculation

Table 5. Bangladeshi Islamic banks’ RTS for 2007 = 2018 (percentage share)

		IRS	CRS	DRS	Total
2007	No. of banks	2	4	1	7
	% share	29%	57%	14%	100%
2008	No. of banks	1	6	0	7
	% share	14%	86%	0%	100%
2009	No. of banks	2	4	1	7
	% share	29%	57%	14%	100%
2010	No. of banks	0	5	2	7
	% share	0%	71%	29%	100%
2011	No. of banks	0	6	1	7
	% share	0%	86%	14%	100%
2012	No. of banks	0	5	2	7
	% share	0%	71%	29%	100%
2013	No. of banks	2	4	1	7
	% share	29%	57%	14%	100%
2014	No. of banks	2	4	1	7
	% share	29%	57%	14%	100%
2015	No. of banks	2	4	1	7
	% share	29%	57%	14%	100%
2016	No. of banks	1	5	1	7
	% share	14%	71%	14%	100%
2017	No. of banks	0	6	1	7
	% share	0%	86%	14%	100%
2018	No. of banks	0	4	3	7
	% share	0%	57%	43%	100%
Average Share		14%	68%	18%	100%

Note: Source: Author’s own calculation

Table 6. Breusch-Pagan/Cook–Weisberg test for heteroscedasticity

Ho: Constant variance
Model	chi2	Prob > chi2
Model 1	11.76	0.0006
Model 2	47.23	0.0000
Model 3	15.11	0.0001

Note: Source: Author’s calculation.”

Table 7. Model 1 shows the Multivariate regression analysis models considering TE as the dependent variable

		Model 1 (a)	Model 1 (b)	Model 1 (c)	Model 1 (d)	Two-stage
VARIABLES	Expected sign	TE	TE	TE	TE	Heckman Model
Zscore	+Ve	0.00253	0.00253	0.00413**	0.00253
		(0.00245)	(0.00219)	(0.00202)	(0.00245)
LTD	-Ve	0.136**	0.136**	0.0697	0.136**	9.833***
		(0.0533)	(0.0589)	(0.0430)	(0.0533)	(1.804)
F_gap	-Ve	2.32e-07***	2.32e-07***	9.54e-08	2.32e-07***	−4.33e-05***
		(6.67e-08)	(5.25e-08)	(6.50e-08)	(6.67e-08)	(7.64e-06)
LNNPL	-Ve	−0.0139**	−0.0139***	−0.00894*	−0.0139**	0.466
		(0.00683)	(0.00406)	(0.00505)	(0.00683)	(0.394)
NPLratio	-Ve	0.0310	0.0310	−0.0535	0.0310	5.021***
		(0.0242)	(0.0190)	(0.0849)	(0.0242)	(1.494)
LNLLP	-Ve	0.0126**	0.0126**	0.0137***	0.0126**	−0.906**
		(0.00588)	(0.00503)	(0.00446)	(0.00588)	(0.382)
Inverse Mill’s ratio (lambda)		-	-	-	-	0.00218 (0.00932)
Constant		0.881***	0.881***	0.898***	0.881***	−6.494***
		(0.0556)	(0.0736)	(0.0443)	(0.0556)	(1.766)
Observations		84	84	84	84	180
R-squared		0.307	0.307	0.151
Number of DMU				7	7

Note: Standard errors in parentheses, *** p<0.01, ** p<0.05, * p<0.1; Source: Author’s calculation.”

Note: The sample consists of 7 IBs operating in Bangladesh from 2007 to 2018. In column 1, the expected signs of the variables are shown. In columns a,b,c,d we employ OLS, White’s Robust-standard error, fixed effect, and random effect, respectively. In column 6, we utilize a two-stage Heckman selection model procedure.

Table 8. Model 2 shows the Multivariate regression analysis models considering PTE as the dependent variable

		Model 2 (a)	Model 2 (b)	Model 2 (c)	Model 2 (d)	Two-stage
VARIABLES	Expected sign	PTE	PTE	PTE	PTE	Heckman Model
Zscore	+	−0.000301	−0.000301	−0.000792	−0.000301
		(0.00108)	(0.000374)	(0.00111)	(0.00108)
LTD	-	0.0159	0.0159	−0.00938	0.0159	9.833***
		(0.0235)	(0.0147)	(0.0237)	(0.0235)	(1.804)
F_gap	-	−5.44e-08*	−5.44e-08**	−2.49e-08	−5.44e-08*	−4.33e-05***
		(2.94e-08)	(2.54e-08)	(3.57e-08)	(2.94e-08)	(7.64e-06)
LNNPL	-	−0.00561*	−0.00561*	−0.00360	−0.00561*	0.466
		(0.00301)	(0.00292)	(0.00278)	(0.00301)	(0.394)
NPLratio	-	0.0124	0.0124**	0.0164	0.0124	5.021***
		(0.0107)	(0.00574)	(0.0467)	(0.0107)	(1.494)
LNLLP	-	0.00156	0.00156	−0.000655	0.00156	−0.906**
		(0.00259)	(0.00200)	(0.00245)	(0.00259)	(0.382)
Inverse Mill’s ratio (lambda)		-	-	-	-	0.00563 (0.00409)
Constant		1.013***	1.013***	1.036***	1.013***	−6.494***
		(0.0245)	(0.0151)	(0.0244)	(0.0245)	(1.766)
Observations		84	84	84	84	180
R-squared		0.094	0.094	0.089
Number of DMU				7	7

Note: Standard errors in parentheses, *** p<0.01, ** p<0.05, * p<0.1; Source: Author’s calculation.”

Table 9. Model 3 shows the Multivariate regression analysis models considering SE as the dependent variable

		Model 3 (a)	Model 3 (b)	Model 3 (c)	Model 3 (d)	Two-stage
VARIABLES	Expected sign	SE	SE	SE	SE	Heckman Model
Zscore	+	0.00282	0.00282	0.00490**	0.00282
		(0.00234)	(0.00219)	(0.00201)	(0.00234)
LTD	-	0.120**	0.120**	0.0789*	0.120**	9.833***
		(0.0510)	(0.0578)	(0.0426)	(0.0510)	(1.804)
F_gap	-	2.86e-07***	2.86e-07***	1.20e-07*	2.86e-07***	−4.33e-05***
		(6.38e-08)	(5.05e-08)	(6.44e-08)	(6.38e-08)	(7.64e-06)
LNNPL	-	−0.00828	−0.00828**	−0.00535	−0.00828	0.466
		(0.00654)	(0.00341)	(0.00501)	(0.00654)	(0.394)
NPLratio	-	0.0187	0.0187	−0.0693	0.0187	5.021***
		(0.0232)	(0.0182)	(0.0842)	(0.0232)	(1.494)
LNLLP	-	0.0110*	0.0110**	0.0143***	0.0110**	−0.906**
		(0.00563)	(0.00481)	(0.00442)	(0.00563)	(0.382)
Inverse Mill’s ratio (lambda)		-	-	-	-	−0.00344 (0.00892)
Constant		0.868***	0.868***	0.862***	0.868***	−6.494*** (1.766)
		(0.0532)	(0.0740)	(0.0439)	(0.0532)
Observations		84	84	84	84	180
R-squared		0.328	0.328	0.207
Number of DMU				7	7

Note: Standard errors in parentheses, *** p<0.01, ** p<0.05, * p<0.1; Source: Author’s calculation.”

Table 10. Impact of liquidity risk and credit risk on TE (checking robustness and removing endogeneity)

	(OLS)	(FE)	(RE)	(IV_2SLS)	(PCSE)
VARIABLES	TE	TE	TE	TE	TE
Zscore	0.00387*	0.00564**	0.00387*	0.00460	0.00387**
	(0.00219)	(0.00281)	(0.00219)	(0.00465)	(0.00168)
LTD	0.134***	0.0492	0.134***	0.323*	0.134***
	(0.0483)	(0.0471)	(0.0483)	(0.191)	(0.0455)
F_gap	2.53e-08	1.89e-07*	2.53e-08	1.66e-07*	2.53e-08
	(9.39e-08)	(9.85e-08)	(9.39e-08)	(8.76e-08)	(9.53e-08)
LNNPL	−0.0151	−0.0190	−0.0151	−0.0978***	−0.0151
	(0.0105)	(0.0140)	(0.0105)	(0.0317)	(0.00932)
NPLratio	0.102**	−0.0209	0.102**	0.0411	0.102***
	(0.0443)	(0.114)	(0.0443)	(0.0436)	(0.0375)
LNLLP	0.0192**	0.0228**	0.0192**	0.0771***	0.0192**
	(0.00926)	(0.0109)	(0.00926)	(0.0268)	(0.00780)
AgeofBank	−0.00453***	−0.00410	−0.00453***		−0.00453***
	(0.00153)	(0.00272)	(0.00153)		(0.00123)
NoofBranches	3.29e-05	0.000520*	3.29e-05		3.29e-05
	(0.000168)	(0.000297)	(0.000168)		(0.000192)
Crisisdummy	−0.0248***	0.00487	−0.0248***	−0.0421***	−0.0248***
	(0.00919)	(0.0118)	(0.00919)	(0.0135)	(0.00654)
Constant	0.914***	0.949***	0.914***	0.943***	0.914***
	(0.0557)	(0.0561)	(0.0557)	(0.184)	(0.0421)
Observations	83	83	83	83	83
R-squared	0.509	0.157		0.035	0.509
Number of DMU		7	7		7

Note: Standard errors in parentheses, *** p<0.01, ** p<0.05, * p<0.1; Source: Author’s calculation.”

Note: Second, third, fourth, fifth, and sixth columns are showing the results of OLS, FE, RE, 2SLS, and PCSE respectively.

Table 11. Impact of liquidity risk and credit risk on PTE (checking robustness and removing endogeneity)

	(OLS)	(FE)	(RE)	(IV 2SLS)	(PCSE)
VARIABLES	PTE	PTE	PTE	PTE	PTE
Zscore	−0.000212	−0.00107	−0.000212	0.00301	−0.000212
	(0.00109)	(0.00157)	(0.00109)	(0.00223)	(0.000646)
LTD	0.0138	−0.00229	0.0138	0.187**	0.0138
	(0.0241)	(0.0263)	(0.0241)	(0.0916)	(0.0239)
F_gap	1.45e-08	−5.08e-08	1.45e-08	−7.96e-08*	1.45e-08
	(4.68e-08)	(5.50e-08)	(4.68e-08)	(4.21e-08)	(2.15e-08)
LNNPL	−0.0135**	−0.00626	−0.0135**	−0.0126	−0.0135***
	(0.00525)	(0.00783)	(0.00525)	(0.0152)	(0.00491)
NPLratio	0.0476**	0.0447	0.0476**	0.0369*	0.0476**
	(0.0221)	(0.0637)	(0.0221)	(0.0209)	(0.0201)
LNLLP	0.00832*	0.00264	0.00832*	0.00871	0.00832*
	(0.00461)	(0.00609)	(0.00461)	(0.0129)	(0.00439)
AgeofBank	−0.00146*	−0.000417	−0.00146*		−0.00146**
	(0.000763)	(0.00152)	(0.000763)		(0.000643)
NoofBranches	0.000183**	−5.77e-05	0.000183**		0.000183**
	(8.37e-05)	(0.000166)	(8.37e-05)		(7.26e-05)
Crisisdummy	−0.000200	−0.00499	−0.000200	−0.000399	−0.000200
	(0.00458)	(0.00658)	(0.00458)	(0.00649)	(0.00250)
Constant	1.036***	1.039***	1.036***	0.858***	1.036***
	(0.0277)	(0.0313)	(0.0277)	(0.0884)	(0.0229)
Observations	83	83	83	83	83
R-squared	0.186	0.107			0.186
Number of DMU		7	7		7

Note: Standard errors in parentheses, *** p<0.01, ** p<0.05, * p<0.1; Source: Author’s calculation.”

Table 12. Impact of liquidity risk and credit risk on SE (checking robustness and removing endogeneity)

	(1)	(2)	(3)	(4)	(5)
VARIABLES	SE	SE	SE	SE	SE
Zscore	0.00408*	0.00668**	0.00408**	0.00159	0.00496***
	(0.00208)	(0.00277)	(0.00208)	(0.00462)	(0.00149)
LTD	0.120**	0.0513	0.120***	0.137	0.108***
	(0.0457)	(0.0465)	(0.0457)	(0.190)	(0.0349)
F_gap	1.07e-08	2.39e-07**	1.07e-08	2.46e-07***	2.94e-08
	(8.89e-08)	(9.72e-08)	(8.89e-08)	(8.71e-08)	(8.56e-08)
LNNPL	−0.00161	−0.0128	−0.00161	−0.0851***	0.00528
	(0.00998)	(0.0139)	(0.00998)	(0.0315)	(0.00835)
NPLratio	0.0540	−0.0651	0.0540	0.00427	0.0478
	(0.0420)	(0.113)	(0.0420)	(0.0433)	(0.0419)
LNLLP	0.0109	0.0201*	0.0109	0.0684**	0.0115*
	(0.00877)	(0.0108)	(0.00877)	(0.0267)	(0.00692)
AgeofBank	−0.00308**	−0.00366	−0.00308**		−0.00301**
	(0.00145)	(0.00268)	(0.00145)		(0.00126)
NoofBranches	−0.000150	0.000576*	−0.000150		−0.000177
	(0.000159)	(0.000294)	(0.000159)		(0.000194)
Crisisdummy	−0.0245***	0.00991	−0.0245***	−0.0416***
	(0.00871)	(0.0116)	(0.00871)	(0.0134)
Constant	0.877***	0.910***	0.877***	1.085***	0.825***
	(0.0527)	(0.0554)	(0.0527)	(0.183)	(0.0287)
Observations	83	83	83	83	83
R-squared	0.532	0.221			0.482
Number of DMU		7	7		7

Note: Standard errors in parentheses *** p<0.01, ** p<0.05, * p<0.1. Source: Author’s calculation.”

Table 13. Hausman (1978) specification test

	Model 1 (c) and Model (d) Coef.	Model 2 (c) and Model (d) Coef	Model 3 (c) and Model 3 (d). Coef
Chi-square test value	−8.963	−2.522	−8.34
P-value	1	1	1

Source: Authors calculation.”

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