The effect of financial inclusion on bank stability: Evidence from ASEAN

Figures & data

Figure 1. Graphical explanation of a 3-dimensional IFI.Source: Sarma (2012)

Table 1. Other variables’ description and measuring

Variables	Description and Measuring
Bank size(lnTA)	The logarithm of total assets is used to account for the potential size effect on bank stability, as the too-big-to-fail can destabilize the efficient financial intermediation of the entire banking system.
Loan loss provision(LossProv)	We use the ratio of loan loss provision to total loans in order to account for individual bank’s loan portfolio risk.
Income diversification(NonIncome)	The ambiguous effect of off-balance-sheet activities of individual banks on stability necessitates considering the ratio of non-interest income to total operating income.
Capitalization(EQA)	Because well-capitalized banks are assumed to take less risk, we use the equity ratio to total assets to control capital risk.
Management quality(EAtoTA)	The ratio of total earning assets to total assets is used as better management quality that can mitigate excessive risk-taking.
Lerner index(Lerner)	We use the Lerner index—the only measure of market power calculated at the bank-level (Ahamed & Mallick, 2019; Berger et al., 2009) as:$\mathrm{L}\mathrm{e}\mathrm{r}\mathrm{n}\mathrm{e}{\mathrm{r}}_{\mathrm{i}\mathrm{t}}=\frac{{\mathrm{P}}_{\mathrm{i}\mathrm{t}}-\mathrm{M}{\mathrm{C}}_{\mathrm{i}\mathrm{t}}}{{\mathrm{P}}_{\mathrm{i}\mathrm{t}}}(5)$ Where: Pit is the price of total assets, the ratio of total revenue (interest and non-interest income) to total assets for bank i at time t.MC is the marginal cost of producing it in an additional unit of output, which is derived from the translog cost function (Berger et al., 2009; Fernández de Guevara et al., 2005) and in this paper, estimated by using a fixed-effects model.This index is interpreted as the inverse of competition; the higher the index is, the greater the pricing power is, which implies less competitive market conditions.
GDP growth rate	We use GDP growth rate to control for economic growth.

Source: Authors gathered

Table 2. Summary statistics

Variable	Mean	Std. Dev	Min	Max	Obs.
ln(sdGrDep)	−2.3315	0.9933	−6.1964	5.2725	1224
NPLTA	0.0146	0.0364	0	0.1967	1068
lnZscore	1.4318	0.3233	−0.8642	2.0394	1224
IFI	0.4386	0.1856	0.1664	0.7938	1224
IFIp	0.4403	0.2365	0.1001	0 .9963	1224
IFIa	0.2254	0.0988	0.0716	0.4011	1224
IFIu	0.4164	0.2445	0.1843	0.9672	1224
lnTA	15.6841	2.1226	6.6373	19.8801	1224
LossProv	0.0109	0.0281	−0.0332	0.4048	1224
NonIncome	1.0661	16.7629	−1.0880	99.5271	1224
EQA	0.1020	0.2682	−3.9607	0.9134	1224
EAtoTA	0.8557	0.0795	0.1387	0.9854	1105
Lerner	0.2203	0.1594	−1.0273	0.5455	1148
GDPrate	0.0529	0.0172	−0.0151	0.1453	1224

Source: Authors’ estimates using STATA 16 Software.

Table 3. Estimated results of financial inclusion and the stability of bank deposit funding

Variable	ln(sdGrDep)
	IFI	IFIp	IFIa	IFIu
l.ln(sdGrDep)	0.3023***	0.2910***	0.3267***	0.3145***
Financial inclusion	−0.8211***	−0.6269***	−0.6626***	−0.5061**
lnTA	−0.1663***	−0.1700***	−0.2032***	−0.1908***
LossProv	2.5630**	2.3873*	1.7711	3.2551**
NonIncome	0.0000	0.0003	0.0008	−0.0002
EQA	−4.4926***	−4.6729***	−5.7944***	−6.5123***
EAtoTA	4.2236***	4.0664***	3.6495***	3.6191***
Lerner	0.7917***	0.7667***	0.5204**	0.8732***
GDPrate	−0.3826	−0.2878	0.1113	−0.5434
Constant	−1.8397***	−1.6953***	−0.7434*	−0.8216*
AR2	0.2	0.237	0.19	0.151
Hansen	0.369	0.361	0.251	0.322
Observations	880	880	880	880

***, **, and * indicate statistical significance at the 1%, 5% and 10% levels respectively.

Source: Authors’ estimates using STATA 16 Software.

Table 4. Estimated results of financial inclusion and nonperforming loans

Variable	NPLTA
	IFI	IFIp	IFIa	IFIu
l.NPLTA	0.3346***	0.3291***	0.3461***	0.3408***
Financial inclusion	−0.0076***	−0.0074***	−0.0014***	−0.0034***
lnTA	−0.0003***	−0.0002***	−0.0009***	−0.0007***
LossProv	0.7426***	0.7370***	0.7419***	0.7489***
NonIncome	0.0001***	0.0001***	0.0001***	0.0001***
EQA	−0.1338***	−0.1258***	−0.1574***	−0.1572***
EAtoTA	−0.0339***	−0.0333***	−0.0399***	−0.0394***
Lerner	0.0141***	0.0140***	0.0137***	0.0148***
GDPrate	−0.0587***	−0.0581***	−0.0533***	−0.0548***
Constant	0.0574***	0.0545***	0.0707***	0.0685***
AR2	0.333	0.332	0.343	0.336
Hansen	0.676	0.721	0.567	0.666
Observations	910	910	910	910

***, **, and * indicate statistical significance at the 1%, 5% and 10% levels respectively.

Source: Authors’ estimates using STATA 16 Software.

Table 5. Estimated results of financial inclusion and bank stability

Variable	ln(Zscore)
	IFI	IFIp	IFIa	IFIu
l.ln(Zscore)	0.1923***	0.1932***	0.1960***	0.1785***
IFIk	0.0933***	0.0574***	−0.0434	0.2486***
lnTA	0.0476***	0.0490***	0.0501***	0.0385***
LossProv	−2.5901***	−2.5496***	−3.478***	−3.1601***
NonIncome	−0.0012***	−0.0012***	−0.0009***	−0.0008**
EQA	2.0283***	2.1078***	2.3586***	1.9812***
EAtoTA	0.2221**	0.2617***	0.4328***	0.1047
Lerner	0.067	0.0664	0.1974**	0.0282
GDPrate	0.3484**	0.3204**	0.3168*	0.5677***
Constant	−0.074	−0.1277	−0.3278***	0.1449
AR2	0.183	0.193	0.166	0.118
Hansen	0.572	0.59	0.377	0.417
Observations	769	769	769	769

***, **, and * indicate statistical significance at the 1%, 5% and 10% levels respectively.

Source: Authors’ estimates using STATA 16 Software.

Sarma, M. (2012). Index of financial inclusion. Berlin Working Papers on Money, Finance, Trade and Development No. 07/2012. Competence Center “Money, Finance, Trade and Development “.

 Google Scholar

Ahamed, M. M., & Mallick, S. K. (2019). Is financial inclusion good for bank stability? International evidence. Journal of Economic Behavior and Organization, 157, 403–427. https://doi.org/10.1016/j.jebo.2017.07.027

 Web of Science ®Google Scholar

Berger, A. N., Klapper, L. F., & Turk-Ariss, R. (2009). Bank competition and financial stability. Journal of Financial Services Research, 35(2), 99–118. https://doi.org/10.1007/s10693-008-0050-7

 Web of Science ®Google Scholar

Fernández de Guevara, J., Maudos, J., & Perez, F. (2005). Market power in European banking sectors. Journal of Financial Services Research, 27(2), 109–137. https://doi.org/10.1007/s10693-005-6665-z

 Google Scholar