Performance Of Market Discipline
In Financial Crisis: The Case of Islamic And State-Owned Banks In Indonesia1
Erie Febrian2
Department of Management & Business, Universitas Padjadjaran, Indonesia
Abstract
During a recession, state-owned banks in Indonesia tend to place their fund in the central
bank’s certificate, as real sector becomes less attractive. On the other side, Islamic bank’s
strong dependence on the accomplishment of its Profit-Loss Sharing (PLS) partners may pose
significant liquidity threat in a slump economy, since the bank also directly bears its
partners’ failure risk. Those environments may provide much less incentive to public to
deposit their fund in state-owned and Islamic banks. However, such inconveniences may not
be substantial to the public if the government either partially or fully guarantees any bank
deposit at certain level. In other words, public can be indifferent to risk of any banks in the
existence of deposit insurance.
This study conducts empirical study on whether depositors in Indonesia are unresponsive to
the risk of Islamic banks and state-owned banks before the US crisis hit the economy (2005.9
– 2008.8) and during the crisis (2008.9 – 2011.12), using panel data analysis. The findings
show that depositors are not sensitive to risk of the observed Islamic and state-owned banks
when their money are protected, to the extent that risk is calculated using fundamental factors
of a bank, regardless the upper limit levels and the economy standing. This implies that
Indonesian banking regulator should focus more on the enforcement of pillar 1 and 2 of Basel
II to maintain sound practices of Islamic and state-owned banks.
Keywords: Bank Risk, Deposit Insurance, Market Discipline, Islamic Bank, State-owned
bank
Small part of this article has been modified from the author’s previous study published in the
Journal of International Finance and Economics, Vol. 11, no. 1, 2011.
1
2
ERIE FEBRIAN is an assistant Professor in Islamic Banking and Finance at the Faculty of
Economics
&
Business,
Universitas
Padjadjaran,
Bandung,
Indonesia.
Email:
[email protected]; [email protected]; Office fax # +62 22 2509055
1
1 Introduction
Practitioners, and academicians in Banking sector have been interested in assessing the
effectiveness of the third pillar of Basel II, i.e., Market Discipline, in promoting sound
banking, particularly when deposits are insured. Some studies have proven that deposit
insurance play significant role in weakening public motive to discipline risky banks, and that
the insurance may induce more bank risk taking, e.g., Merton (1977), Thies & Gerlowski
(1989), Grossman (1992), Wheelock (1992), Demirguc-Kunt & Detragiache (2002), and
Febrian & Meera (2011). Demirguc-Kunt (1998a, 1998b, and 2000a) suggests that depositors
are uninterested in the association of bank’s fundamentals and risk with their deposits, since
they are confident with the government pledges to their money. Other studies have proven
that high insurance ceiling has made depositors indifferent to bank risk, e.g., England (1991).
Advocates for this conclusion seem to significantly dominate the studies. In Russia,
Peresetsky, Karminsky, and Golovan (2007) reveal that Russian depositors demand higher
deposit interest rates from banks with risky financial policies, and that the risks taken by
banks increase after the introduction of deposit insurance scheme in 2005. As well, in Japan,
Murata and Hori (2006), and Hosono (2005) prove that depositor sensitivity to bank risks has
fluctuated over time, with respect to the deposit insurance scheme and the economic
circumstance. When relating market discipline to the magnitude of deposit insurance, Ikuko
and Masaru (2007) in Japan, and Ioannidou and Dreu (2006) find that deposit insurance
significantly reduces market discipline, and that the effect of deposit insurance varies across
coverage rates.
Contrarily, the fact is that many economies have adopted deposit insurance schemes to
prevent bank runs from occurring (Laeven, 2002), while there have been many studies
proving significantly that market can control bank risk-taking behavior, such as Romera &
2
Tabak, (2010), Hosono (2005, 2006), LLlewellyn (2005), Santos (2004), Levy-Yeyati, Peria,
and Schmukler (2003, 2004), Benink & Wihlborg (2002), Nier and Baumann (2002),
Diamond & Dybvig (1983), Khorassani (2000), and Niinimaki (2003). Peria, and Schmukler
(1999, 2001), employing data across countries and across deposit insurance schemes, find
that deposit insurance does not appear to lessen the extent of market discipline, and further
suggest that market discipline exists even among small, insured depositors. This conclusion is
backed up by Khorassani (2000), who proves that in 1980s and early 1990s, US depositors
remain sensitive to bank risk, despite the high deposit insurance ceiling.
The above discussion shows that the degree of deposit insurance intervention on the market
discipline varies across coverage rates, insurance schemes, regions, and economic
circumstances. Nevertheless, there have been insufficient studies conducted on this issue
using data of Islamic banks, which do not offer fixed return, and data of state-owned
banks that are fully supported by government, in an economic downturn. To be more
specific, whether depositors are sensitive to risk of Islamic Banks and to risk of governmentowned banks, when deposits are insured in a slump economy, still needs to be answered.
Empirical investigation on the effectiveness of market discpline in Islamic banks during a
financial crisis is crucial, since Islamic bank may face significant liquidity threat, given that
the bank is exposed to its partners’ failure risk. It is also interesting to see how depositors
respond to risk taking in state-owned bank during a slump economy, since such a bank
receives full support from the government, in addition to the protection from deposit
insurance.
This study attempts to fill the above literature gap by particularly explaining the role of market
discipline in controlling Islamic and State-owned bank risk taking in the existence of deposit
insurance in the banking system. In this study, the author examines whether depositors in
3
Indonesia are insensitive to the risk of Islamic banks and government-owned banks before the
US crisis (2005.9 to 2008.8) and during the US crisis (2008.10 to 2010.12).
The author organizes the rest of the paper as follows. In session 2, some relevant studies in
deposit insurance and market discipline are elaborated, and the variables included in the first
and second equation are briefly summarized. In session 3, the data and methodology are
expalined. In session 4, the empirical results and findings are discussed. The author describes
the sensitivity of depositors to risk of Islamic banks, and government-owned banks during the
observed period. At the end, the study is concluded with a brief discussion.
2 Literature Review
2.1 Deposit Insurance
In many economies, either explicit or implicit deposit insurance are applied to avert bank
runs and to ensure liquidity to banks experiencing bank runs. Most of economies
implementing explicit deposit insurance scheme guarantee deposits up to a certain limit.
Meanwhile, some economies, like Turkey, provide complete deposit insurance, which can
eradicate the threat of bank runs as long as guarantees credibility is effective. However, this
full deposit insurance may ruin potentially advantageous information disclosure and
monitoring by depositors (Laeven, 2001). The stipulation of deposit insurance also engenders
stimulations for bank managers to be more risk taker. The banking literatures provide
comprehensive theoretical and empirical descriptions of the moral hazard consequences of
deposit insurance. Among others, Merton (1977, 1978) and Kareken and Wallace (1978)
theoretically revealed that banks choose a less risky portfolio of assets when deposits were
not insured. A study done by Murata and Hori (2006) shows that incentives for banks to
assume relatively high risk are reduced if the insurance coverage of bank creditors drops from
full to partial coverage. Moreover, Eberle (1990) empirically prove that when deposit
insurance is provided at no cost to banks, a risk neutral bank will invest its entire portfolio in
4
the risky asset, while it will diversify its portfolio between safe and risky assets in the
absence of deposit insurance. Theis and Gerlowski (1989), Cebula and Hung (1992),
Grossman (1992), Wheelock (1992), Brewer and Mondschean (1994), Wheelock and
Kubhakar (1994), and Shiers (1994) also conducted empirical studies to prove that generally
deposit insurance has some impact on bank risk and/or bank default. Merton (1977, 1978)
then further model value of the associated deposit insurance opportunity cost. Laeven (2002)
employs the estimate of the opportunity-cost value of deposit insurance services as a proxy
for bank risk and reveals that this proxy has predictive power in forecasting bank misfortune.
Bhattacharya and Thakor (1993) also develop a model of the enticements by which deposit
insurance tempts insured banks to invest in excessively risky portfolio and remain lower level
of liquidity in terms of the social optimum.
How well the deposit insurance works as expected has been proven to be dependence on
specific circumstances of an economy. Hall, King, Meyer, and Vaughan (2004) examine the
sensitivity of jumbo-CD yields and run-offs to risk before and after The US Federal Deposit
Insurance Corporation Improvement Act of 1991 as well as the implied impact of any risk
penalties on bank profitability, and find that raising the deposit-insurance ceiling would not
exacerbate moral hazard, at least in the particular institutional and economic environment.
Meanwhile, an empirical study conducted by Demirgüç-Kunt and Huizinga (1999, 2004)
proves that explicit deposit insurance reveals a trade-off between the benefits of enhanced
depositor safety and the costs of lessened creditor discipline. Demirguc-Kunt and Kane
(2001) also provide evidence that challenges the wisdom of encouraging economies to
introduce explicit deposit insurance without having appropriate assessment and remedy on
shortcomings in their informational and supervisory environments. Moreover, using crosseconomy data, Demirgüç-Kunt and Detragiache (1999) reveal that economies with
insufficient institutional circumstance would more likely experience banking crises when
5
providing explicit deposit insurance. This finding is in line with that of Laeven (2000), who
proves that the existing governmental deposit insurance schemes create moral hazard and
other incentive problems in the insured banks that operate in environment with weak
institutions and are characterized by concentrated private ownership. Cull, Senbet, and Sorge
(2000) argue that to daunt instability and promote financial development, the introduction of
an explicit deposit insurance scheme should be backed up by an adequate regulatory
framework. Kane (2000) argues that country-specific factors, like differences in
informational environments and the enforceability of private contracts, should be precisely
considered in a country’s financial safety net scheme. Demirgüç-Kunt and Kane (2001)
summarize that economies with a weak institutional environment should not introduce
explicit deposit insurance.
2.2 Market Discipline
In January 2001, to overcome shortcomings in the 1988 Capital Accord on credit risk, the
Basel Committee on Banking Supervision, which is part of Bank for International
Settlements, issued a proposal for a New Basel Capital Accord that is to be implemented by
participating banks all over the world in 2006. In part, the 2001 Basel Capital Accord is based
on market discipline. The interest in the introduction of market discipline to regulate the
banking industry has surged accordingly.
There are many studies carried out to explain the nature of market discipline and the
associated mechanisms. Further studies on the issue also reveal the market discipline impacts
on bank risk-taking behavior before, during and after financial crisis, particularly in
developing economies. The results of the studies vary over observed periods, economies, and
particular circumstances.
6
Some study results show that market discipline may not be as effective as expected in
preventing banks from being more risk taker. By reviewing the key features of the Basel II
pillars and discussing and evaluating associated conceptual issues concerning theoretical
predictions and empirical findings in the academic literature, Vanhoose (2007) concludes that
the market-discipline pillar does not go far enough in the direction suggested by academic
research, and the supervisory-process pillar actually goes in the wrong direction. This is in
line with finding of a research conducted by Hall, King, Meyer, and Vaughan (2004) that
suggests that operationalizing debt-market discipline as pillar of bank supervision could
prove more difficult than previously thought. Moreover, based on an empirical study using
the experience of Indonesian retail depositors and interbank interlock, Valensi (2003)
suggests that the reliance of Basel II on market discipline in its third pillar could be less
effective in the context of developing countries and, therefore, regulators might pay more
attention on the first pillar and the second pillar.
On the other hand, there have been many studies result in convincing supports for the
effectiveness of market discipline in discouraging excessive bank risk taking. Murata & Hori
(2006) show that riskier institutions attract smaller amounts of deposits and are required to
pay higher interest rates reflecting that depositors run effective market discipline. Also,
contrary to Valensi (2003), Caprio and Honohan (2004) suggest that enhancing market
discipline (third pillar) is much more likely to be helpful in most developing economies than
addressing the refinements of the risk-weighting system of Basel II's first pillar.
The existence of market discipline also confirms in financial crisis circumstances. Santos
(2004) shows that depositors require higher risk premiums, more from riskier banks than
safer ones, during financial recessions. In Russia, using a database from post-communist, predeposit-insurance, Karas, Pyle, and Schoors (2006) prove that both firm and household
depositors provide quantity-based sanction to weaker banks, particularly after the financial
7
crisis of 1998. Additionally, assessing the experience of 4 countries hit by the Asian crisis
(i.e., Indonesia, Malaysia, Thailand, and the Republic of Korea), Hosono (2005) reveal
empirical proofs that the deposit interest rate was negatively associated with bank equity
capital, reflecting that depositors could understand bank risk and identify a problem bank.
Similarly, a study on the impact of banking crises on market discipline in Argentina, Chile,
and Mexico during the 1980s and 1990s shows that depositors discipline banks by liquidating
deposits and by demanding higher interest rates, and that depositors’ responsiveness to bank
risk taking increases in the consequence of crises (Peria and Schmukler, 2001). Furthermore,
Romera and Tabak, (2010) suggest that depositors are able do discriminate between well and
poorly managed banks, and explain that depositors discipline banks by withdrawing deposits
during crisis periods and charging higher interest rates during tranquil periods.
In the market discipline mechanism, depositors usually employ fundamental information of
the observed bank. Barajas and Steiner (2000), using panel data estimations for 1985-1999 in
Columbia, prove that depositors prefer banks with stronger fundamentals, banks with
stronger fundamentals benefit from lower interest costs and higher lending rates, and,
consequently, banks tend to improve their fundamentals after being punished by depositors.
Rose, Pinfold, and Wilson, (2004), testing the relationship between bank risk premiums and
the risk indicators contained in disclosure statements in New Zealand, conclude that bank
disclosure statements do provide depositors with valuable information and this information is
reflected in the interest rates charged by individual banks. This finding is consistent with that
of study conducted by Peria and Schmukler (1999) that employ GMM estimations to confirm
that fundamentals are at least as imperative as other factors influencing deposits.
However, the proposed third pillar to enhance market discipline of banks' risk-taking is too
weak to achieve its objective. The accomplishment of market discipline is not inevitable, as
some conditions may apply based on specific circumstances of an economy. Llewellyn
8
(2005) finds that there is much that regulators are able to and are required to do to improve
the effectiveness of market discipline and to ensure that market discipline is not hindered.
Levy-Yeyati, Peria, and Schmukler (2003) conclude that market discipline would be certainly
quite strong when systemic risks are factored in, while admitting that certain institutional
characteristics of developing economies (such as inadequate capital markets, invasive
government ownership of banks, greater deposit insurance, insufficient disclosure and
transparency) may impinge on market responses to bank risk. Levy-Yeyati, Peria, and
Schmukler (2004) further explain that as systemic risk increases, the informational substance
of historic fundamentals declines, and that few systemic shocks can trigger a bank run
irrespective of ex-ante fundamentals. Moreover, Ioannidou and Dreu (2006) emphasize the
need for binding exposure limits per depositor, high level of co-insurance, and tailor made
deposit insurance systems that preserve the incentives of a critical mass of depositors that are
willing and able to perform market discipline. Benink and Wihlborg (2002) suggest that
regulators can strengthen market discipline by asking banks to issue subordinated debt as part
of the capital requirement. Similarly, Hosono (2006) shows that effective market discipline
needs various institutional structures, such as disclosure and transparency, credible and
modest safety net schemes, development of security markets, liberalization of bank activities,
privatization of banks, and stable macroeconomic policy.
Another specific issue in market discipline studies is the ability of market discipline to
resolve the moral hazard problem that arises when depositors are not well informed whether
bankers are monitoring or not the projects they finance.
2.3 Market Discipline Measurement in the Previous Studies
Studies on the impact of deposit insurance on market discipline generally examine either nonguaranteed deposit changes only or both non-guaranteed and guaranteed deposit changes. The
9
former basically conducts regression on the spread of deposit’s interest rate against various
banks’ financial ratios (fundamental factors) to see whether bank risk explains the spread.
This group may include studies done by Hannan and Hanweck (1988), Flannery and Sorescu
(1996) and Dennis, Sharpe and Sim (1998), among others. Meanwhile, the latter group
usually carries out a two-stage analysis consisting of two or three equations. This group may
include studies conducted by Park and Peristiani (1998), Park (1995), Goldberg and Hudgins
(1996) Khorassani (2000) and Ioannidou and Dreu (2006). In the first stage, a logit regression
of bank failure against various banks’ financial ratios is conducted to predict value of bank
failure variable. In the second stage, the value of bank failure is then used as an independent
variable in the second stage analysis of estimating the interest rate and/or the deposit change.
Estimation equations of interest rate and the deposit growth are equations of demand and
supply, respectively. The interest rate required by the depositors is represented by the demand
equation, while the bank deposit growth is represented by the supply equation.
To examine whether depositors respond to increases in bank risk by reducing their supply of
deposits, ideally one should estimate a simultaneous equations model specifying demand and
supply equations, which suggest that sign of bank failure probability variable should be
positive in interest rate equation and be negative in deposit quantity equation. However, the
associated studies, like Mondschean & Opiela (1999), Barajas & Steiner (2000), Calomiris &
Powell (2001), Luzio-Antezana (2001), and Peria & Schmukler (2001), hardly prove the
opposite sign of the same financial ratio on both equations. In practice, it is hard to find
exogenous variables that strongly affect either the supply or the demand equation, like in the
studies of Khorassani (2000) and Goldberg & Hudgins (1996). Consequently, the empirical
literature has tried to infer whether market discipline is present using reduced-form equations
introduced by Park (1995) for the equilibrium interest rates and/or deposits. Particularly,
market discipline implies that higher bank-risk leads to less supply of deposits.
10
Another way to overcome the above variable sign problem is the inclusion on some bank
specific variables such as ownership, number of branch offices and return to deposit variables
(interest rate) in addition to banks’ fundamentals (financial ratios). Khorassani (2000) adds
variables like average predicted risk of the industry, ratio of personal income to number of
commercial banks, interest rate on deposit, average deposit interest rate in the industry,
number of branches, and age of the bank, in the second stage equation.
3 Data And Methodology of The Study
This study utilizes financial data of all Islamic and state-owned banks operating in Indonesia
in the period of deposit insurance regime, i.e., 2005.9 – 2011.12. This period is divided into
two sub periods, i.e., the period of lower ceiling (2005.9 – 2008.8) and the period of higher
ceiling (2008.9 – 2011.12). The dissection is to reveal the impact of two different ceilings of
the pledge and influence of the downturn on the market discipline, as maximum limit of the
amount guaranteed was increased from IDR 100 millions to IDR 2,000 millions in 2009.9 to
prevent the economy from the worse crisis impact.
The author only includes banks whose data is consistently available during the observation
period. There were three Islamic banks in 2005, i.e., Bank Muamalat Indonesia (BMI), Bank
Syariah Mandiri (BSM), and Bank Mega Syariah (BMS). These banks still operated in 2011.
Meanwhile, there were five state-owned banks in 2005,i.e., Bank Mandiri, Bank Negara
Indonesia (BNI), Bank Rakyat Indonesia (BRI), Bank Tabungan Negara (BTN), and Bank
Ekspor Impor (BEI). In 2011, BEI was not in the industry anymore. Thus, in this study, three
Islamic banks and four state-owned banks are selected as the observed banks.
In this study, a bank is said unsafely risky if it receives one of the three Indonesian central
bank’s financial assistance schemes, i.e., Intraday Liquidity Fund (locally known as FPI),
Short-term Fund (FPJP) and Emergency Fund (FPD), and/or receives financial assistance
11
from any external party(ies), and/or bears Non Performing Loan (NPL) or Non Performing
Financing (NPF) more than 5%.
The first equation is as follows:
Risk it   i   i1Capast   i 2 Aggast   i 3Tradast   i 4 Manast   i 6 Consast   i 6 Secast   i 7 Plcbi
 i8 Plcob  i 9 Invrev  i10 Logast  i11 Age  i12Off  i13Perinc  i14Unem  i15Bank
  i16 Depast   i17 Incast   i18 Licast .........(equation 1)
In the above first equation, the author runs a regression of eighteen independent variables on
the dependent variable, i.e., the binary figure (0 or 1), which indicates whether the bank is
unsafely risky or not. The observed independent variables are:

ratio of capital to total asset (Capast);

ratios of loan (or Profit-Loss Sharing/PLS investment) in agriculture (Aggast),
trading (Tradast), manufacture (Manast), and construction to total asset (Consast);

ratio of security to total asset (Secast);

placement in the central bank, Bank Indonesia (Plcbi);

placement in other domestic banks (Plcob);

the ratio of total loan/PLS Investment revenue of each bank to its total revenue
(Invrev);

natural log of total asset (Logast);

age of bank (Age);

number of bank office (Off);

income per capita (Perinc);

unemployment rate (Unem);

the ratio of the number of banks to total population in an area (Bank);

ratio of deposit to total asset (Depast);
12

ratio of net income to total asset (Incast); and

ratio of liquid asset to total asset (Liqast).
The values of Risk (predicted risk) obtained from the first equation regression are then
employed in the second equation regression.
Ldpit   i  i1Lincprbk  i 2 Rdp  i 3 Lnum  i 4 Lage  i 5 Risk ......... (equation 2)
In the second stage, the author regresses five independent variables on the natural log of
total bank deposit (Ldp) to examine the depositor sensitivity. The independent variables
include:

natural log of the ratio of national income per capita to the number of banks
nationwide (Lincprbk);

return rate on bank deposits (Rdp);

natural log of number of bank offices (Lnum);

natural log of age of the bank (Lage);

predicted risk (Risk).
The above process utilizes data of Islamic banks, and government-owned banks before and
during the crisis to reveal the difference between depositor sensitivity to risk of Islamic
banks, government-owned banks, and conventional-national banks. The author conducts
rolling regression to the data in both observation periods, for the first equation. There are 54
rolling periods for the pre-crisis analysis and 54 rolling periods for the during-crisis analysis.
4 Empirical Results And Findings
4.1 Islamic Banks Before Crisis (Lower Ceiling-Deposit Insurance)
The estimated coefficients of the probit model for the periods of 2005.9 through 2008.8 are
shown on Table 1. Generally, the probit equations show good result across the rolling
13
periods, which are revealed by the average Pseudo R-square of 0.452. Moreover, majority of
the coefficient signs are consistent with the theory. Fifteen out of eighteen independent
variables have substantial contribution to the probability of banks being categorized as
unsafely risky banks in minimum 20% of the observed rolling periods.
The variables of trast, plcbi, and depast do not contribute considerably to the bank risk.
Placement of Islamic banks in the central bank’s security (plcbi) does not lessen their risk.
This empirical result supports the philosophy that Islamic bank avoids passive investments.
Moreover, PLS investment in trading (trast) and deposit do not substantially positively or
negatively influence the bank risk, inferring that in this observed period partnership in trading
is not gainful enough to diminish risk nor so poor to boost the risk. Likewise, the growth of
PLS-based deposit fails to reduce bank risk. The variable of aggast and consast contribute to
the bank risk, while manast negatively influences the risk. This implies that the PLS
investment in agriculture and construction businesses seems to be less cost-effective, while
manufacture PLS investment provides positive results. It is worth noting that placement in the
Islamic securities contributes substantially to risk of the Islamic bank in this period,
reminding Islamic banks to stay focus more on real sector financing than on passive
investment.
Furthermore, as favorable economy prior the crisis leads to higher personal real income
(perinc) and more incentives for individuals to deposit their money in a bank, the variable
preinc reduces the Islamic bank risk in the before-crisis period. Meanwhile, in line with the
theory, change in unemployment rate has shown positive correlation with the probability of
the bank failure.
14
Table 1
Description of Probit Model Estimates Using 54 Rolling Periods
for Islamic Banks, Periods of 2005.9 – 2008.8 (Lower Ceiling-Deposit Insurance)
Independent
Variable
Number
of
Rolling
Periods
In
Which
The
Variable
Is
Included
Number of Rolling
Periods With
Negative But
Insignificant
Coefficient (Prob
>0.05)
No
Prop
Number of Rolling
Periods With
Negative And
Significant
Coefficient (Prob
<0.05)
No
Number of Rolling
Periods With
Positive But
Insignificant
Coefficient (Prob
>0.05)
Prop
No
Prop
Number of Rolling
Periods With
Positive And
Significant
Coefficient (Prob
<0.05)
No
Prop
C
54
9
0,167
8
0,148
26
0,481
11
0,204
CAPAST
54
8
0,148
39
0,722
3
0,056
4
0,074
AGGAST
54
14
0,259
3
0,056
26
0,481
11
0,204
TRAST
54
29
0,537
0
0,000
17
0,315
8
0,148
MANAST
54
28
0,519
11
0,204
13
0,241
2
0,037
CONSAST
54
13
0,241
0
0,000
26
0,481
15
0,278
SECAST
54
11
0,204
0
0,000
31
0,574
12
0,222
PLCBI
54
25
0,463
4
0,074
22
0,407
3
0,056
PLCOB
54
26
0,481
14
0,259
5
0,093
9
0,167
INVREV
54
24
0,444
12
0,222
14
0,259
4
0,074
LOGAST
54
26
0,481
18
0,333
10
0,185
0
0,000
OFF
54
13
0,241
20
0,370
21
0,389
0
0,000
BANK
54
31
0,574
13
0,241
6
0,111
4
0,074
PERINC
54
31
0,574
20
0,370
3
0,056
0
0,000
UNEM
54
3
0,056
0
0,000
33
0,611
18
0,333
AGE
54
17
0,315
12
0,222
25
0,463
0
0,000
INCAST
54
26
0,481
14
0,259
13
0,241
1
0,019
LIQAST
54
11
0,204
22
0,407
21
0,389
0
0,000
DEPAST
54
34
0,630
7
0,130
7
0,130
6
0,111
Pseudo R-square (Average)
0.452
Pseudo R-square (Range)
0.369 - 0.562
15
Table 2
Equation 2 Model for Islamic Banks
Periods of 2005.9 – 2008.8 (Lower Ceiling-Deposit Insurance)
Dependent Variable: LDP
Method: Least Squares
Date: 23/04/13 Time: 21:10
Sample: 1 54
Included observations: 54
Variable
C
RDP
MEANRDP
RISK
MEANRISK
LINCPRBK
LNUM
R-squared
Adjusted R-squared
S.E. of regression
Sum squared resid
Log likelihood
Durbin-Watson stat
Coefficient
5.100218
-1.020281
0.000178
-0.003228
0.043438
-0.049087
0.64718
0.630059
0.55888
0.083756
0.276829
48.89647
2.149893
Std. Error
t-Statistic
0.220889
0.760448
0.000127
0.005208
0.007897
0.059022
0.207868
Mean dependent var
S.D. dependent var
Akaike info criterion
Schwarz criterion
F-statistic
Prob(F-statistic)
18.00906
-1.35338
1.098266
-0.609927
5.419044
-0.841726
3.071964
Prob.
0
0.1902
0.2794
0.5267
0
0.4022
0.0033
6.226301
0.130375
-1.907875
-1.635028
10.09996
0.000011
Table 2 indicates the results of Equation 2 Regression for Islamic Banks during the pre-crisis
period (2005.9 – 2008.8). This model has passed the Normality, Autocorrelation,
Heterocedasticity, and Multicolinearity tests. Variables of meanrisk and lnum are significant
substantially positively influence the deposit amount in Islamic banks, inferring that
depositors are less sensitive to risk of Islamic banks when deposit was guaranteed by the
government at any coverage rate. Rather, risk of competing banks around the observed
Islamic banks and the number of bank office help upsurge deposits in Islamic banks. The
higher the risks of other banks in particular area, the more desirable are the Islamic banks.
Similarly, the more accessible the Islamic banks’ service, the more their ability to boost PLS
deposit.
16
4.2 Islamic Banks During Crisis (Higher Ceiling-Deposit Insurance)
Details of the estimated coefficients of the Islamic bank probit model for the periods of
2008.9 through 2011.12 are provided on Table 3. Overall the probit equations indicate
effective result across the rolling periods, which are supported by the average Pseudo Rsquare ranging from 0.361 to 0.556. Most of the coefficient signs are consistent with the
theory. Uniquely, several factors contributing to bank risk before the crisis are no longer
significant factors in the period of crisis, i.e., plcob, off, bank. Meanwhile, plcbi and depast
become significant factors to the bank risk during the crisis, implying that in the slump
economy, Islamic bank tends to get linked with the central bank by placing particular amount
of its fund in the central bank’s security, rather than placing its fund in other banks, which
encounter the same hazard. It seems that Islamic banks chooses to reduce its risk by putting
its fund into central bank’s security, rather than channeling it to the real sector. This action is
reflected by the negative correlation between deposit amount and bank risk, and may not
display the real nature of Islamic banks which are real sector oriented. Variables off (Islamic
bank’s accessibility) and bank (banking competition in particular area) do not contribute
significantly to bank risk. This is true as all banks in the economy encounter the same
danger.
17
Table 3
Decription of Probit Model Estimates Using 54 Rolling Periods
for Islamic Banks, Periods of 2008.9 – 2011.12 (Higher ceiling - Deposit Insurance)
Independent
Variable
Number
of
Rolling
Periods
In
Which
The
Variable
Is
Included
Number of Rolling
Periods With
Negative But
Insignificant
Coefficient (Prob
>0.05)
No
Prop
Number of Rolling
Periods With
Negative And
Significant
Coefficient (Prob
<0.05)
No
Number of Rolling
Periods With
Positive But
Insignificant
Coefficient (Prob
>0.05)
Prop
No
Prop
Number of Rolling
Periods With
Positive And
Significant
Coefficient (Prob
<0.05)
No
Prop
C
54
8
0.148
7
0.130
29
0.537
10
0.185
CAPAST
54
2
0.037
49
0.907
2
0.037
1
0.019
AGGAST
54
9
0.167
5
0.093
26
0.481
14
0.259
TRAST
54
28
0.519
1
0.019
18
0.333
7
0.130
MANAST
54
27
0.500
16
0.296
10
0.185
1
0.019
CONSAST
54
11
0.204
1
0.019
26
0.481
16
0.296
SECAST
54
12
0.222
1
0.019
26
0.481
15
0.278
PLCBI
54
28
0.519
13
0.241
10
0.185
3
0.056
PLCOB
54
32
0.593
5
0.093
10
0.185
7
0.130
INVREV
54
27
0.500
13
0.241
13
0.241
1
0.019
LOGAST
54
29
0.537
17
0.315
8
0.148
0
0.000
OFF
54
20
0.370
9
0.167
22
0.407
3
0.056
BANK
54
31
0.574
9
0.167
9
0.167
5
0.093
PERINC
54
30
0.556
13
0.241
9
0.167
2
0.037
UNEM
54
5
0.093
3
0.056
30
0.556
16
0.296
AGE
54
13
0.241
14
0.259
26
0.481
1
0.019
INCAST
54
26
0.481
12
0.222
14
0.259
2
0.037
LIQAST
54
14
0.259
24
0.444
16
0.296
0
0.000
DEPAST
54
28
0.519
13
0.241
11
0.204
2
0.037
Pseudo R-square (Average)
Pseudo R-square (Range)
0.438
0.361 - 0.556
18
Table 4 shows the Equation 2 Regression model for Islamic Banks during the crisis or the
application of higher-limit Deposit Insurance. The model has passed the Normality,
Autocorrelation, Heterocedasticity, and Multicolinearity tests.
Table 4
Equation 2 Model for Islamic Banks,
Periods of 2008.9 – 2011.12 (Higher ceiling - Deposit Insurance)
Dependent Variable: LDP
Method: Least Squares
Date: 28/04/13 Time: 10:18
Sample: 1 54
Included observations: 53 after adjustments
Variable
Coefficient
Std. Error
t-Statistic
C
RDP
MEANRDP
DRISK
MEANRISK
LNUM
LAGE
-0.10268
0.07099
4.10E-06
-0.02188
1.00165
0.06158
1.023026
0.29009
0.211432
1.05E-05
0.01411
0.002278
0.03213
0.062006
-0.583083
0.201308
0.109058
-0.918802
3.51003
1.83819
19.7701
R-squared
Adjusted R-squared
S.E. of regression
Sum squared resid
Log likelihood
Durbin-Watson stat
0.95779
0.91677
0.030088
0.02651
101.988
2.23577
Mean dependent var
S.D. dependent var
Akaike info criterion
Schwarz criterion
F-statistic
Prob(F-statistic)
Prob.
0.5609
0.87088
0.8006
0.3023
0.0032
0.09961
0
6.51228
0.121005
-3.85627
-3.51102
121.0002
0
Significant contribution from variables of meanrisk, and lage to the deposit decision implies
that depositors count risk of other banks in their area and experience of the observed Islamic
bank in their decision, when deposit insurance ceiling is increased from IDR 100 million to
IDR 2,000 million. The empirical results also reveal that depositors’ deposit making does not
really consider the level of return provided by the Islamic bank, or interest rates offered by
the competitors in particular area. Depositors consider risk of other banks in the oberved area
in their deposit decision. Remarkably, depositors’ decision is not well correlated with the risk
19
of Islamic bank, suggesting that the market is still confident with the nature of Islamic banks,
i.e., avoiding speculative investments and predetermined interest rate securities. Such
character helps Islamic banks survive the crisis.
4.3 Government-owned Banks Before Crisis (Lower Ceiling-Deposit Insurance)
The estimated coefficients of the Government-owned bank probit model for the periods of
2005.9 through 2008.8 are summarized on Table 5. The average Pseudo R-square of 0.472
indicates good result across the observed period. It is worth noting that unemployment
variation in particular provincial or metropolitan city has relatively significant influence on
the government-owned bank risk. This may indicate that community of particular provincial
area or metropolitan city is still important market for government-owned banks. Significant
contribution of plcbi to the bank risk shows that government-owned banks tend to pursue
passive investment by placing their funds in the central banks’ certificate, and pay less
attention on real sector financing. The favorable economic circumstance in the period allows
higher personal real income (perinc) and provides more incentives for individuals to deposit
their money. In this case, the variable perinc reduces the government-owned bank risk before
crisis. Meanwhile, in line with the theory, change in unemployment rate has shown positive
correlation with the probability of the bank failure.
Other observed variables show support to the theory. Variables of capast, logast, incast,
liqast and depast tend to be negatively correlated with risk of state-owned banks. In other
words, the growth in capital, total asset, income, liquidity and deposit help reduce risk of the
state-owned bank during the conducive economy.
20
Table 5
Description of Probit Model Estimates for Government-owned banks
Periods of 2005.9 – 2008.8 (Lower ceiling - Deposit Insurance)
Independent
Variable
Number
of
Periods
In
Which
The
Variable
Is
Included
Number of Periods
With Negative But
Insignificant
Coefficient (Prob
>0.05)
No
Prop
Number of Periods
With Negative And
Significant
Coefficient (Prob
<0.05)
No
Prop
Number of Periods
With Positive But
Insignificant
Coefficient (Prob
>0.05)
No
Prop
Number of Periods
With Positive And
Significant
Coefficient (Prob
<0.05)
No
Prop
C
54
14
0.259
8
0.148
23
0.426
9
0.167
CAPAST
AGGAST
54
54
17
23
0.315
0.426
22
7
0.407
0.130
10
18
0.185
0.333
5
6
0.093
0.111
TRAST
54
20
0.370
6
0.111
22
0.407
6
0.111
MANAST
54
19
0.352
7
0.130
24
0.444
4
0.074
CONSAST
54
17
0.315
5
0.093
25
0.463
7
0.130
SECAST
54
20
0.370
7
0.130
21
0.389
6
0.111
PLCBI
54
21
0.389
21
0.389
9
0.167
3
0.056
PLCOB
54
15
0.278
6
0.111
26
0.481
7
0.130
INVREV
54
22
0.407
4
0.074
24
0.444
4
0.074
LOGAST
54
11
0.204
19
0.352
20
0.370
4
0.074
OFF
54
18
0.333
6
0.111
28
0.519
2
0.037
BANK
54
10
0.185
7
0.130
32
0.593
5
0.093
PERINC
54
21
0.389
22
0.407
8
0.148
3
0.056
UNEM
54
12
0.222
3
0.056
17
0.315
22
0.407
AGE
54
25
0.463
6
0.111
20
0.370
3
0.056
INCAST
54
9
0.167
24
0.444
19
0.352
2
0.037
LIQAST
54
20
0.370
19
0.352
15
0.278
0
0.000
DEPAST
54
22
0.407
21
0.389
9
0.167
2
0.037
Pseudo R-square (Average)
Pseudo R-square (Range)
0.472
440 - 522
Meanwhile, Table 6 shows the Equation 2 Regression model for state-owned Banks during
the crisis or the application of higher-limit Deposit Insurance. In this observed period
depositors tend to assess the accessibility (lnum) and experience (lage) of the intended banks
before placing their money. They do not explicitly consider risk of the bank or average risk of
21
the alternative banks in their deposit decision. In other words, the depositors are indifferent to
the calculated risk of state-owned bank, since they preceive that government will always
protect its interest in the bank and may bail out the bank if necessary.
Table 6
Equation 2 Model for Government-owned Banks,
Periods of 2005.9 – 2008.8 (Lower Ceiling-Deposit Insurance)
Dependent Variable: LDP
Method: Least Squares
Date: 28/04/13 Time: 13:22
Sample: 1 54
Included observations: 54
Variable
C
RDP
MEANRDP
DRISK
MEANRISK
LNUM
LAGE
R-squared
Adjusted R-squared
S.E. of regression
Sum squared resid
Log likelihood
Durbin-Watson stat
Coefficient
0.03302
0.02309
0.00078
0.00003
0.02967
1.51295
1.100023
0.95209
0.90701
0.03201
0.02557
99.902
2.0051
Std. Error
0.29028
0.210421
0.0003
0.01183
0.00117
0.01207
0.05201
t-Statistic
-0.513015
0.20081
0.19251
-0.91008
3.5156
1.80038
19.0877
Mean dependent var
S.D. dependent var
Akaike info criterion
Schwarz criterion
F-statistic
Prob(F-statistic)
Prob.
0.0056
0.87108
0.7016
0.1323
0.2176
0.0025
0
6.5002
0.1413
-3.032
-3.2101
119.2443
0
4.4 Government-owned Banks During Crisis (Higher Ceiling-Deposit Insurance)
Table 7 reveals the estimated coefficients of the local bank probit model for the periods of
2008.9 through 2010.12. The values of Pseudo R-square ranging from 0.442 - 0.539 indicate
good result across the periods. Like Islamic Banks in some degree, state-owned banks tend to
place their fund in the central bank’s certificate during the crisis to minimize the tension, as
indicated by tendency of plcbi signs. In this observed period, other variables like capast,
logast, perinc, unem, incast, liqast, and depast consistently contribute to the local bank risk.
22
Table 7
Description of Probit Model Estimates for Government-owned banks
Periods of 2008.9 – 2011.12 (Higher ceiling - Deposit Insurance)
Independent
Variable
Number
of
Periods
In
Which
The
Variable
Is
Included
Number of Periods
With Negative But
Insignificant
Coefficient (Prob
>0.05)
No
Prop
Number of Periods
With Negative And
Significant
Coefficient (Prob
<0.05)
No
Prop
Number of Periods
With Positive But
Insignificant
Coefficient (Prob
>0.05)
No
Prop
Number of Periods
With Positive And
Significant
Coefficient (Prob
<0.05)
No
Prop
C
54
16
0.296
8
0.148
22
0.407
8
0.148
CAPAST
54
18
0.333
24
0.444
9
0.167
3
0.056
AGGAST
54
22
0.407
5
0.093
20
0.370
7
0.130
TRAST
54
24
0.444
3
0.056
22
0.407
5
0.093
MANAST
54
21
0.389
8
0.148
21
0.389
4
0.074
CONSAST
54
18
0.333
4
0.074
27
0.500
5
0.093
SECAST
54
20
0.370
6
0.111
22
0.407
6
0.111
PLCBI
54
21
0.389
25
0.463
8
0.148
0
0.000
PLCOB
54
15
0.278
5
0.093
27
0.500
7
0.130
INVREV
54
20
0.370
4
0.074
26
0.481
4
0.074
LOGAST
54
13
0.241
21
0.389
18
0.333
2
0.037
OFF
54
18
0.333
6
0.111
28
0.519
2
0.037
BANK
54
11
0.204
7
0.130
32
0.593
4
0.074
PERINC
54
23
0.426
22
0.407
8
0.148
1
0.019
UNEM
54
13
0.241
3
0.056
15
0.278
23
0.426
AGE
54
15
0.278
18
0.333
18
0.333
3
0.056
INCAST
54
8
0.148
24
0.444
18
0.333
4
0.074
LIQAST
54
21
0.389
19
0.352
14
0.259
0
0.000
DEPAST
54
20
0.370
22
0.407
8
0.148
4
0.074
Pseudo R-square (Average)
Pseudo R-square (Range)
0.477
442 - 539
Nevertheless, investment variables like aggast, trast, and manast are not factors to bank risk
in the period, which imply that state-owned banks may handle their credit allocation very
carefully during the crisis and tend to avoid more risk by putting their funds in the central
bank. This empirical results also reveal that in the downturn period, accessibility of
23
government-owned banks (reflected by off), which is supported by large office networks, fails
to help reduce bank risk. Meanwhile, management experience (indicated by age) effectively
reduce the threat to government-owned banks, as it negatively influences the local bank risk.
Table 8
Equation 2 Model for Government-owned banks,
Periods of 2008.9 – 2011.12 (Higher ceiling - Deposit Insurance)
Dependent Variable: LDP
Method: Least Squares
Date: 28/04/13 Time: 14:45
Sample: 1 54
Included observations: 54
Variable
Coefficient
C
RDP
MEANRDP
DRISK
MEANRISK
LNUM
LAGE
0.13102
0.07119
0.00431
-0.02187
0.91602
0.06151
1.02310
R-squared
Adjusted R-squared
S.E. of regression
Sum squared resid
Log likelihood
Durbin-Watson stat
0.95017
0.9201
0.03112
0.0226
100.098
2.42571
Std. Error
0.29029
0.21412
0.00011
0.01241
0.00127
0.03423
0.06302
t-Statistic
-0.5838
0.20118
0.10229
-0.91802
3.5111
1.13801
18.0771
Mean dependent var
S.D. dependent var
Akaike info criterion
Schwarz criterion
F-statistic
Prob(F-statistic)
Prob.
0.5688
0.8201
0.8099
0.3202
0.0015
0.0929
0
6.5233
0.121098
-3.8516
-3.15412
121.045
0
Table 8 exhibits the Equation 2 Regression model for state-owned banks during the crisis.
The
model
has
passed
the
Normality,
Autocorrelation,
Heterocedasticity,
and
Multicolinearity tests. The empirical results are similar to those of Islamic banks,in which
only meanrisk, and lage are significant factors to the deposit decision. Meaningful influence
from meanrisk, and lage to the deposit decision infers that depositors anticipate risk of other
banks in their area and experience of the observed state-owned banks in their decision. Other
important finding is that depositors are indifferent to the level of interest offered by the
24
Government-owned bank, or offered by the competitors in particular area. Another message
from the empirical results is that bank risk is not a factor to depositors’ decision, which infers
that in some degree deposit insurance effectively weakens market discipline in the stateowned banking sector.
5 CONCLUSION
This study is aimed at revealing the effectiveness of market discipline in Islamic and
government-owned banks in Indonesia before and during the economy being affected by the
US crisis. The study utilizes data of Islamic and government-owned banks, as well as
pertinent macroeconomic variables during the application of deposit insurance with
maximum coverage of IDR 100 million (2005.9 – 2008.8, before crisis) and of IDR 2,000
million (2008.9 – 2011.12, during the crisis).
This study finds that depositors are insensitive to risk of Islamic banks in both periods of
observation. Instead, average risk of alternative banks in particular city or province and bank
experience are factors to the depositors’ deposit decision, in both periods. Meanwhile, similar
examination employing data of state-owned bank in both periods shows slightly different
results. In the pre-crisis period, depositors’ investment decision is influenced by the bank
accessibility and experience, while during the crisis, depositors tend to anticipate average risk
of alternative banks in particular area and management experience in their decision.
Empirical investigation using data of both types of bank and two different economic
circumstances has shown that in the presence of deposit insurance, market discipline is
somewhat ineffective. To sum up, depositors are insensitive to risk of Islamic and governmentowned banks when their money are insured, irrespective with the coverage rate and the
economy states. On the other hand, depositors may evaluate aggregate risk of banking sector in
particular area to define exposure of the bank they observe.
25
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