ArticlePDF Available

Abstract

The recent series of banking crises in the United States and in the Eurozone has resulted in numerous bank failures. In this paper, an agent-based model is employed to test for factors that determine bank viability in times of distress, focusing mainly on the endogenous risk of financial institutions. The authors test for the effects of both management and financial factors on the institutions’ ability to weather the storm during times when the banking system experiences distress. The agent-based simulation process is split into a setup period, when the simulation builds the structural characteristics of each bank, and a testing period, where these characteristics are tested against the final result, which is the bank’s viability. A risk estimation model is built and it is found that the proposed model is successful in predicting whether a particular bank can endure a stress testing situation. The empirical results confirm the relevant literature and put further emphasis on the policy implications regarding banking supervision and regulation, particularly in context of the Eurozone banking union.
“Good management or good finances? An agent-based study on the
causes of bank failure”
AUTHORS
Stathis Polyzos https://orcid.org/0000-0002-4317-1809
Khadija Abdulrahman
Apostolos Christopoulos
ARTICLE INFO
Stathis Polyzos, Khadija Abdulrahman and Apostolos Christopoulos
(2018). Good management or good finances? An agent-based study on
the causes of bank failure.
Banks and Bank Systems
,
13
(3), 95-105.
doi:10.21511/bbs.13(3).2018.09
DOI http://dx.doi.org/10.21511/bbs.13(3).2018.09
RELEASED ON Tuesday, 11 September 2018
RECEIVED ON Friday, 25 May 2018
ACCEPTED ON Wednesday, 15 August 2018
LICENSE
This work is licensed under a Creative Commons Attribution-
NonCommercial 4.0 International License
JOURNAL "Banks and Bank Systems"
ISSN PRINT 1816-7403
ISSN ONLINE 1991-7074
PUBLISHER LLC “Consulting Publishing Company “Business Perspectives”
FOUNDER LLC “Consulting Publishing Company “Business Perspectives”
NUMBER OF REFERENCES
44
NUMBER OF FIGURES
4
NUMBER OF TABLES
3
© The author(s) 2018. This publication is an open access article.
businessperspectives.org
95
Banks and Bank Systems, Volume 13, Issue 3, 2018
Abstraсt
e recent series of banking crises in the United States and in the Eurozone has result-
ed in numerous bank failures. In this paper, an agent-based model is employed to test
for factors that determine bank viability in times of distress, focusing mainly on the en-
dogenous risk of nancial institutions. e authors test for the eects of both manage-
ment and nancial factors on the institutions’ ability to weather the storm during times
when the banking system experiences distress. e agent-based simulation process is
split into a setup period, when the simulation builds the structural characteristics of
each bank, and a testing period, where these characteristics are tested against the nal
result, which is the bank’s viability. A risk estimation model is built and it is found that
the proposed model is successful in predicting whether a particular bank can endure
a stress testing situation. e empirical results conrm the relevant literature and put
further emphasis on the policy implications regarding banking supervision and regula-
tion, particularly in context of the Eurozone banking union.
Stathis Polyzos (Greece), Khadija Abdulrahman (United Arab Emirates),
Apostolos Christopoulos (Greece)
BUSINESS PERSPECTIVES
LLC “P “Business Perspectives
Hryhorii Skovoroda lane, 10, Sumy,
40022, Ukraine
www.businessperspectives.org
Good management
or good finances?
An agent-based study on
the causes of bank failure
Received on: 25 of May, 2018
Accepted on: 15 of August, 2018
INTRODUCTION
e world banking system has vivid memories from the nancial tur-
moil of 2008, where several nancial institutions were faced with ex-
tremely strenuous conditions. e 2008 crisis extended beyond the
nancial sector, hurting total output and thus damaging societal pros-
perity. Researchers still attempt to locate the distinguishing charac-
teristics of banks, which allowed some to recover from the crisis and
drove others to default. Most argue that there must exist a set of traits,
ranging from sound management to solid nances, that would permit
a forecast of the ability of a bank to weather the storm during distress.
In this paper, an agent-based model is employed in order to examine
the causes of bank distress. It is proposed that banks fail due to both -
nancial and corporate governance factors and introduce these features
in the authors modelling platform. e authors of the current article
attempt a link between these characteristics of the nancial institu-
tion and its nal state at the end of the simulation and employ this link
to develop a simple forecasting model, verifying its robustness.
e current paper contributes to three aspects of the existing litera-
ture. Firstly, to the best of the authors’ knowledge, it is the rst eort to
utilize an agent-based modelling platform as the medium with which
to carry out simulations in the elds of management and corporate
governance. Secondly, the validity of the results of existing literature
© Stathis Polyzos, Khadija
Abdulrahman, Apostolos
Christopoulos, 2018
Stathis Polyzos, Ph.D., Department
of Business Administration, Business
School, University of the Aegean,
Greece.
Khadija Abdulrahman, Assistant
Professor, College of Business, Zayed
University, United Arab Emirates.
Apostolos Christopoulos, Lecturer
of Banking and Finance, Faculty of
Economics, University of Athens,
Greece.
is is an Open Access article,
distributed under the terms of the
Creative Commons Attribution-Non-
Commercial 4.0 International license,
which permits re-use, distribution,
and reproduction, provided the
materials aren’t used for commercial
purposes and the original work is
properly cited.
corporate governance, agent-based nance, endogenous
risk, bank management
Keywords
JEL Classification G01, G32, G21, G28, H3
96
Banks and Bank Systems, Volume 13, Issue 3, 2018
on the causes of bank failure is tested. irdly, possible policy implications are examined with respect
to banking supervision, especially in the context of protecting societal prosperity.
e paper is structured as follows: Section 1 presents the relevant literature. In Section 2, the agent-
based model is discussed and its main points are briey presented. Section 3 includes the methodologi-
cal issues of the research work and the variables used. In Section 4, the outcome of the simulations is
presented and the last Section includes the concluding remarks.
1 e SIR Model is a compartmental model in Epidemiology which classies the population into three health states: Susceptible, Infected,
Recovered (thus SIR). In mathematical epidemiology, compartmental models help understand the dynamics of the spread of an epidemic.
1. LITERATURE REVIEW
ere exists a new trend in academic research that
has turned the focus on modelling bank surviv-
ability as opposed to protability, which was the
favored topic before the nancial crisis of 2008.
Existing studies mainly examine risk and risk
management and have linked these to the nan-
cial characteristics of banks. Philippas et al. (2015)
implement the SIR1 epidemiological model in an
eort to predict the nal state of a bank during a
banking crisis. Haq and Heaney (2012) nd a sig-
nicant negative relationship between total bank-
ing risk and the dividend payout ratio, which they
attribute to the eort of banking rms to increase
income for their shareholders. Broll et al. (2015)
also attempt to model the relationship between
risk and return in banking institutions.
Note that some researchers make the case that
greater risk-taking can be in the best interest of
shareholders in the presence of deposit insurance
(Beltratti & Stulz, 2009). Caluzzo and Dong (2015)
suggest that risk in the nancial sector has shied
away from individual risk towards systemic risk,
adding that banking systems are now more sus-
ceptible to systemic contagion (as opposed to con-
tagion in the banking system). Simper et al. (2015)
also show that risk management practices play an
important part in bank performance.
Contrary to existing research on bank perfor-
mance and viability, this paper expands to the
eld of management and additionally includes
corporate governance features. Macey and O’Hara
(2003) provide a thorough review of corporate gov-
ernance in the banking sector and its implications
on the nancial institutions and on the econom-
ic system as a whole. O’Connor and Byrne (2015)
show that “sound” corporate governance is linked
with rm maturity. Barr et al. (1993) also demon-
strate that management quality is closely linked
with bank survivability. Sullivan and Spong (2007)
show that insider wealth limits risk-taking behav-
ior, whereas stock ownership by hired managers
may increase risk. Additionally, wealth concentra-
tion, which is the proportion of one’s wealth at risk
in a given nancial institution, was also showed to
have a positive eect on risk management (lower
total risk), provided that the individual is in a po-
sition to inuence relevant managerial decisions
(Iannotta et al., 2007). Konishi and Yasuda (2004)
examine the Japanese banking sector and reach
similar conclusions, establishing a nonlinear em-
pirical relationship of stable ownership and bank-
ing risk. García-Marco and Robles-Fernández
(2008) corroborate these ndings for the Spanish
market.
Kangis and Kareklis (2001) demonstrate that the
mix between public and private ownership can
have an eect on bank performance. Barry et al.
(2011), and Haque and Shahid (2016) also conrm
the results showing the important role of own-
ership structure, especially for privately owned
banks, where institutional investors tend to imple-
ment riskier strategies when owning higher stakes
in banks. Wu and Li (2015) examine Chinese
rms and comment positively on the eects of
board independence on rm performance, while
Kaur Virk (2017) shows that board independence
is linked with a smaller number of regulatory vio-
lations. Laeven and Levine (2009) and Mullineux
(2006) also stress the importance of regulation.
Williams and Nguyen (2005) implement the
technical ineciency eects model of Battese
and Coelli (1995) using bank governance varia-
bles, similar to ours. is methodology was em-
ployed in the current article in order to implement
97
Banks and Bank Systems, Volume 13, Issue 3, 2018
a risk-governance index in the authors model,
which describes bank features that tend to show
“sound” management strategies. Additionally,
Gupta et al. (2013) employ an additive index to
quantify forty two bank governance factors. ey
nd that corporate governance “failed” during
the nancial crisis, since the factors that existing
literature considered as positive did little to help
large corporations. A similar index is constructed
by Koerniadi et al. (2014), who nd that good gov-
ernance practices are associated with lower levels
of risk. Agoraki et al. (2010) link board size and
composition to bank eciency, suggesting that a
small board size may signify better risk manage-
ment. Similar results are demonstrated in Conyon
and Peck (1998), who nd that a smaller board size
results in better corporate performance.
ElKelish (2017) performs a multi-country analy-
sis of corporate governance risks, linking them to
agency costs. Similarly, Aebi et al. (2012) propose
a series of measures of corporate governance that
are better suited to the banking sector. ey use
empirical data from banks in Europe and in the
US and nd that independent risk management is
crucial to the bank’s performance during a nan-
cial crisis. On the other hand, standard govern-
ance indicators seem to contribute little, if at all,
to the amelioration of these results. However, they
note the negative eects of risk governance on per-
formance during “normal” times, using common
performance indicators for the banking sector.
Reddy and Locke (2014) reach similar conclusions
from data regarding rms in New Zealand.
2. GENERAL MODEL
DESCRIPTION
e agent-based nancial model employed was
developed by Samitas and Polyzos (2015) and ex-
tended by Polyzos and Samitas (2015). e mod-
el was designed to simulate the behavior of eco-
nomic agents and is loosely based on the work of
Tsomocos (2003a, 2003b). However, the Tsomocos
model was extended to include agent-based char-
acteristics, which are a new trend oen seen in
simulation research (see for example Bookstaber
et al., 2018, and Riccetti et al., 2015). e specif-
ic agent-based model has also been used to sim-
ulate the post-Brexit economic system (Samitas et
al., 2018) and has also been applied to the Greek
banking system (Samitas & Polyzos, 2015).
e model incorporates three main types of eco-
nomic agents, namely Banks, Households and
Firms. ese agents operate under a given super-
visory framework, which is set forth by a market
regulator. In this setup, there is a constant, but
not unconditional, ow of funds between these
agents, which can take place in various ways,
ranging from the exchange of nancial goods be-
tween banks and their customers to the payment
of wages from rms to households. Firms operate
and improve their productive capacity using -
nancing from the banking system, which draws
liquidity from the funds of depositors. e mod-
el also employs the idea that agents can go bank-
rupt. Bankruptcy occurs when agents are unable
to meet their nancial obligations. e insolven-
cy conditions are stricter for banks than they are
for other agents and, naturally, the consequences
are dierent as well. e model supports various
methods of handling banks in distress, including
the bail-in solution, which was implemented to re-
solve the 2013 Cyprus nancial crisis.
3. METHODS
A thorough description of the latest version of the
model, including a formal model denition, can
be found in Samitas et al. (2018). In the current
paper, this work is extended, in order to mod-
el the risk of nancial institutions according to
both their nancial and their corporate govern-
ance characteristics. Each of the governance fea-
tures inuences the bank’s behaviour in a dier-
ent manner; this is something that the agent-based
nature of the authors model allows to implement.
e nancial features are calculated at a snapshot
of the nancial institution aer some time peri-
ods have elapsed. It must be noted that the pro-
posed methodology does not examine bank per-
formance, eciency or protability. At the current
stage, these are not handled by the extension of
the model, since the goal was to examine the caus-
es of failure, rather than the causes of success.
Extending the Samitas et al. (2018) model, specif-
ic characteristics have been introduced for each
bank. ese variables are monitored in order to
98
Banks and Bank Systems, Volume 13, Issue 3, 2018
link them with the end state of each nancial in-
stitution and to try to deduce an underlying rela-
tionship. In terms of governance features, the rst
monitored variable in the simulation is the pres-
ence of a Credit Risk Ocer (CRO) in the execu-
tive board. Aebi et al. (2012) suggest that when the
CRO has an active say in the executive board, this
generally results in better risk management. In the
current implementation, the bank is more capable
of discerning the probability of rms to default
on their loans. Additionally, banks with a CRO in
the board of directors have the capacity to oer -
nancing at customized interest rates, according to
the credit status of the borrower2.
Another variable implemented is the board size.
Aebi et al. (2012) and Beltratti and Stulz (2009)
show that a smaller board size can work in the
benet of exibility allowing the bank to respond
faster to changing market conditions. Both stud-
ies propose the use of further measures regarding
the Board of Directors, such as the attendance of
members to board meetings, but these were not
included in the authors simulations. However, if
the board size is too small, it is possible that the
lack of polyphony will hinder eective risk man-
agement. In the proposed model, a large board
size has a negative eect on the ability of the bank
to oer the appropriate interest rate for each rm
and to set its base deposit rate, which eects both
its cost of capital and its earnings3.
e board independence, which is the percent-
age of board members without further relation
to the bank, is also an implemented variable.
Additionally, a variable measuring the director
experience has been included, which is calculated
as the number of directors in the board with -
nancial background. Aebi et al. (2012) have imple-
mented this variable as the percentage of directors
with experience as an executive ocer in a bank or
insurance company. Both these variables tend to
improve risk management as they increase.
In terms of ownership, three variables have been
included, namely the percentage of total equity
2 See step 1.12 of the basic model, where the active rms seek nancing from banks from their proposed investment projects.
3 is is handled at step 1.11 of the basic model.
4 CEO: Chief Executive Ocer.
5 Note that this ratio will dier greatly from the expected values of a real-world bank, since the authors are only simulating part of a nancial
institution’s balance sheet.
owned by the CEO4, the percentage owned by the
public sector and the percentage owned by insti-
tutional investors. It has been shown (Barry et al.,
2011) that institutional investors tend to enforce
riskier strategies when their ownership percent
permits them to exert managerial control. On the
other hand, Barry et al. also show that public sec-
tor ownership is associated with lower risk, while
other research (Iannotta et al., 2007) suggests low-
er loan quality and higher insolvency. Ownership
concentration is associated with better risk man-
agement (Iannotta et al., 2007), while a high CEO
ownership seems to reduce overall risk (Sullivan &
Spong, 2007).
e monitored nancial variables include the
bank’s ratio of assets to liabilities5 and the ratio of
loans to deposits as shown below:
, 10
, 10
, 10
, 10
,
bt
bt
at
aA
b
lt
lL
Amt
Assets to Liabilities Amt
=
=
=
=
=
(1)
, , 10
, , 10
, 10
, 10
l
bt bt
bt bt
b
at
aA
lt
lL
Loans to Deposits
Amt
Amt where is of type Deposit
=
=
=
=
=
= .
(2)
In terms of the bank’s position in the marketplace,
the ratio of the average interest rate of deposits
and the ratio of the average interest rate of loans
over the market average were computed.
( )
, 10
, 10
, 10 , 10
, 10
.
bt
bt
b
at at
aA
at
aA
Average Interest Rate Loans
ir Amt
Amt
Market Average
=
=
= =
=
=
×
=
(3)
( )
, 10
, 10
, 10 , 10
, 10
,
bt
bt
b
at bat
lL
ba t
lL
Average Interest Rate Deposits
ir Amt
Amt
Market Average
=
=
= =
=
=
×
=
(4)
where l is of type Deposit.
99
Banks and Bank Systems, Volume 13, Issue 3, 2018
Also, the model uses the average spread (denoted
by the average interest rate of loans minus that of
deposits) and the prot margin, which is the aver-
age interest rate of loans less the WACC6. e latter
is the weighted average of the interest rates of the
bank’s liabilities.
, 10
, 10
, 10
, 10
, 10 , 10
, 10
, 10 , 10
, 10
Spread
,
bt
bt
bt
bt
at at
aA
b
at
aA
at bat
lL
ba t
lL
Average Amt
ir Amt
Amt
=
=
=
=
= =
=
= =
=
×
=
×
(5)
where l is of type Deposit.
, 10
, 10
, 10
, 10
, 10 , 10
, 10
, 10 , 10
, 10
.
bt
bt
bt
bt
at at
aA
b
at
aA
at bat
lL
ba t
lL
ir Amt
Profit Margin Amt
ir Amt
Amt
=
=
=
=
= =
=
= =
=
×
=
×
(6)
Note that equations 5 and 6 dier in the fact the
latter takes into account all liabilities of the bank
(i.e. includes interbank loans), while the former
only considers deposits.
With respect to the particulars of the banking sec-
tor, the authors monitor the amount of cash over
the weighted assets7, the percentage of non-per-
forming loans on total loans and the interbank ex-
posure of the bank, which is the percentage of in-
terbank loans over on loans. Increased interbank
exposure has been shown to deteriorate a bank’s
expected viability due to increased contagion
risks (Drehmann & Tarashev, 2013).
, 10
, 10
,
bt
b
bt
CB
CashtoWeighted Assets wa
=
=
=
(7)
, 10
, 10
', 10
'
, 10
,
bt
bt
b
at
aA
at
aA
NPLs
Amt wherea has missed payments
Amt
=
=
=
=
=
=
(8)
, 10
, 10
', 10 , 10
'
, 10
.
bt
bt
b
at bt
aA
at
aA
Interbank Exposure
Amt suchthat a L b B
Amt
=
=
= =
=
′′
=
∈∈
=
(9)
6 Weighted Average Cost of Capital.
7 is could be considered an approximation to the Tier-1 capital.
Aer the implementation of these variables in the
proposed agent-based model, a virtual economy is
designed, consisting of 1,000 households, 10 banks
and 40 rms. Basel III was enforced as a regulato-
ry framework for the banking system and a bail-in
was the solution of choice for the Regulator to save
a bank in distress. e time span for each simula-
tion was 30 periods and 10,000 simulations were
executed.
e governance features were assigned to each
bank at the start of the simulation. eir values
are random and the probability distribution has
been manipulated to follow the ndings of Aebi
et al. (2012), who recorded these variables over a
large sample of international banks. Each bank is
logged in the system with these variables at the
start of each simulation. e nancial variables
were recorded at period 10, when the banks had
enough time to interact with rms and house-
holds, in order to build their asset and liability list.
e nal state of the bank was then recorded, giv-
en four alternatives, as follows:
Bankrupt: In this state, the bank has gone
bankrupt. Note that in this case, the Regulator
was unable to rescue the bank, using the de-
posits the bank carries.
Needs nancing: In this state, the bank is still
working but is unable to meet the require-
ments of the regulatory framework and will
need a cash injection.
Balanced: is is the initial state of the bank.
is state will be assigned to banks in all cas-
es where they cannot be included in any other
state.
Prosperous: is is the ideal state of the bank.
In this case, the bank’s total assets including
its available cash exceed its liabilities. is
state is an indication that the bank is well
equipped to deal with nancial distress.
e nal state of the bank is the dependent var-
iable on the regression analysis proposed by the
authors. It was examined which of the above var-
100
Banks and Bank Systems, Volume 13, Issue 3, 2018
iables are signicant in the prediction of the nal
state and a forecasting model was built to predict
the outcome of the simulations. is methodology
is similar to Aebi et al. (2012), the dierence being
that the data is generated from the simulations of
the model. Following this process, the model was
executed again to verify its predictive eciency.
e results are presented in the following section.
4. EMPIRICAL RESULTS
Table 1 shows a summary of the monitored varia-
bles for each of the four nal states. e sample is
100,000 banks (10,000 simulations with 10 banks
each) with random governance features, as de-
scribed earlier. is table shows the distribution
patterns for each of the variables over the entire
sample of 100,000 observations, according to the
nal states. e table is indicative of the rm link
between the bank’s nal state and both its govern-
ance and nancial features.
Firstly, it is clear that CRO presence improves the
bank’s nal state, since the worse-o states show
lower average CRO presence in the board of di-
rectors (Figure 1). e board size does not seem
important in determining the nal state, but it
seems that an increased number of independent
members is benecial (Figure 2).
In terms of the ownership structure, it is evident
that a larger value in CEO ownership as well as in
institutional ownership will tend to improve the
Table 1. Summaries of monitored variables for each nal state
Bankrupt, % Needs financing, % Balanced, % Prosperous, %
No CRO in board 66.0 61.0 53.0 53.0
CRO in board 34.0 39.0 4 7. 0 4 7. 0
Board size (independent/dependent members) 12 (8/4) 13 ( 8 /5) 13 (9/ 4) 13 ( 9/4)
CEO ownership 20.5 23.7 25.2 25.2
Public ownership 28.6 28 .1 37. 2 30.5
Institutional ownership 20.9 23.2 22.6 24.3
Assets to liabilities 1,2 21 1, 0 98 73 691
Loans to deposits 3,702 2,165 156 1, 49 4
Deposit rate to market average 101.8 97.4 93.7 93.9
Loan rate to market average 102. 3 9 7. 2 94.2 95.3
Spread 6.41 5.95 5.88 5.91
Profit margin 5.28 5.42 5.58 5.42
Non-performing loans 9.88 15 .38 1. 59 9.16
Interbank exposure 28.7 54.4 1.4 39.3
Cash to weighted assets 25.6 24.6 36.1 31.8
Note: is table includes the summaries of monitored variable of the simulation set, for each of the nal states of banks. e
summary for the CRO variables is the percentage of the banks where the particular feature was true, except for the board size,
which shows the average number of members. e summaries for the nancial variables, as well as of ownership variables (CEO
ownership, public ownership and institutional ownership) represent the average values recorded at the snapshot period (period
10), linked with the end state of the bank aer the end of the simulation.
Figure 1. CRO presence for each of the four nal states
0%
20%
40%
60%
80%
100%
Bankrupt Needs financing Balanced Prosperous
No CRO in board CRO in board
101
Banks and Bank Systems, Volume 13, Issue 3, 2018
bank’s future. On the other hand, greater public
ownership seems to lead the bank to the balanced
state more oen, which is an expected result, since
publicly owned banks tend to exhibit lower risk
and lower protability. e latter variable (public
ownership) does not seem to exhibit a linear rela-
tionship with the dependent variable (nal state).
Moving on to nancial information, it is impor-
tant to note the existence of “extreme” values for
all states except the balanced state. It must also
be noted that the amount of loans that bankrupt
banks carry in their asset list is substantially high-
er than the other states. However, the existence of
extreme values in the prosperous state leads us to
deduce that banks cannot prosper if risks are not
assumed. Nevertheless, it must be made clear to
investors and depositors that these risks may re-
sult in bank failure. Risks must also be assumed
by the nancing department, where interestingly
Figure 2. Dependent and independent board members for each of the four states
0
2
4
6
8
10
12
14
Bankrupt Needs financing Balanced Prosperous
Independent members Dependent members
Figure 3. Average ownership percentages for each of the nal states
0%
5%
10%
15%
20%
25%
30%
35%
40%
Bankrupt Needs financing Balanced Prosperous
CEO ownership Public ownership Institutional ownership
Figure 4. Interest rates over the respecve market average
88%
90%
92%
94%
96%
98%
100%
102%
104%
Bankrupt Needs financing Balanced Prosperous
Deposit rate to market average Loan rate to market average
102
Banks and Bank Systems, Volume 13, Issue 3, 2018
enough data for the NPLs8 and the interbank ex-
posure at the snapshot period (period 10, as men-
tioned earlier) are similar for banks which ended
up in the bankrupt and prosperous states, albeit
interbank exposure is somewhat higher for the
prosperous state.
With respect to the market position, it must be
noted that the simulations appear to suggest an
interest rate strategy for banks. e ndings show
that oering lower interest rates, vis-à-vis the mar-
ket average, both for deposits and for loans, will
improve the bank’s future, the particulars of the
prisoner’s dilemma notwithstanding. A lower in-
terest rate spread is also advisable, as is the use of
a lower prot margin, even though the results are
not clear on the latter.
A simple linear regression on the results shows
that the important variables are the presence of
the CRO in the board, the ownership variables
and the interest rate strategy variables. ese were
included in the nal prediction model.
It is not surprising that the public ownership var-
iable does not exhibit high correlation, since, as
was shown earlier, its relationship with the nal
state is not a linear one and consequently a linear
regression of these variables will fail to describe
the dependent variable’s values. Admittedly, the
use of a linear regression is simplistic and is one of
the shortcomings of the current work. However, as
one will see below, the linear regression is success-
ful in describing the model and the resulting fore-
casting system can predict the bank’s nal state
with a fair amount of certainty.
8 Non-Performing Loans.
Table 2 shows the coecients for the variables in
the proposed prediction model, which are signi-
cant at the 95% condence level. is regression
model has a satisfactory R–2 value and was imple-
mented in the model in an eort to predict the
nal state of the nancial institution. Once the
prediction model was implemented, the simula-
tions were executed 1,000 more times to verify ro-
bustness and the outcome (displayed in Table 3)
was encouraging. On the snapshot period, the -
nancial variables were calculated and used in con-
junction with the governance variables in order
to compute a prediction for the bank’s nal state.
e authors let the simulation complete and com-
pared the predicted state to the actual nal state.
Table 3. Robustness check of the predicon
model over 1,000 simulaons
Percentage,
%
Successful prediction 64.25
Unsuccessful prediction 35.75
Better state than predicted 57. 9 8
Worse state than predicted 42.02
In most cases, the prediction model was successful
in forecasting the bank’s nal state, since in only
35% of the simulations the prediction was false. In
these latter cases, only 42% would be damaging to
the investors, since the nal state of the bank was
worse than the predicted one. Consequently, even
though one can argue that a prediction of a worse
state than the nal one can also prove damaging,
only a mere 15% of predictions could make an in-
vestor or depositor worse o if they followed it.
Table 2. Linear regression model for the predicon of the nal state of the bank
BStandard error
(Constant) –1.82 0.018
CRO in board 0.65 0.006
Loans to deposits –0.02 0.000
Public ownership –0.28 0 .012
Institutional ownership 0.32 0 . 013
CEO ownership 0.19 0 .013
Deposit rate to average 0.15 0.014
Loan rate to average –0.36 0.029
Note: e model’s R2 value is 0.62, which means that an important proportion of the variance in the dependent variable (Final
State) can be predicted from the given set of independent variables. e specic value (0.62) shows that the model is a good t
for the given data set.
103
Banks and Bank Systems, Volume 13, Issue 3, 2018
CONCLUSION
Concluding this paper, the authors have shown that both governance and nancial variables need to be
taken into account when discussing bank viability and when predicting whether the bank has enough
potential to handle a nancial crisis. e ndings agree with the relevant literature, which places em-
phasis on the presence of a CRO in the board of directors, on board independence and on the ownership
structure of the nancial institutions, when discussing bank performance and hence viability.
Additionally, the introduction of a low interest rate strategy is proposed, which needs further verica-
tion though, since it appears to be a case of prisoner’s dilemma. If all banks follow this strategy, then it
will simply be ineective. Consequently, a bank will need to be careful when using this strategy as a tool
for better results.
e ndings have also led to a simple, linear prediction model for the bank’s end state, but it must be
noted that the eectiveness is limited to the economic system of the agent-based model in its current
version. e model seems to fail to predict a worse-o nal state in only 15% of cases.
e empirical results have some important policy implications. Banking supervision pays little impor-
tance to the corporate governance features of the nancial institutions. Additionally, authorities seem to
focus more on capital requirements, which have been shown to hinder banking activity, with negative ef-
fects on the real economy and society. e results of the simulations suggest that regulators should take
into account management characteristics of each bank as well. Policy makers can use this information
to improve their stress testing systems in order to yield better results. e lack of statistical signicance
for commonly quoted gures, such as the NPLs and the interbank exposure, implies that banking au-
thorities need to evolve their models and include more characteristics which might not have been taken
previously into account. In today’s corporate environment, where the role of banks is not limited to -
nancial services but extends to many aspects of the modern society, bank failure can have severe adverse
eects in community prosperity.
REFERENCES
1. Aebi, V., Sabato, G., & Schmid,
M. (2012). Risk management,
corporate governance, and bank
performance in the nancial
crisis. Journal of Banking &
Finance, 36(12), 3213-3226.
https://doi.org/10.1016/j.jbank-
n.2011.10.020
2. Agoraki, M. E. K., Delis, M. D., &
Staikouras, P. K. (2010). e eect
of board size and composition
on bank eciency.International
Journal of Banking, Accounting and
Finance,2(4), 357-386. https://doi.
org/10.1504/IJBAAF.2010.037155
3. Barr, R. S., Seiford, L. M., & Siems,
T. F. (1993). An envelopment-
analysis approach to measuring
the managerial eciency of
banks. Annals of Operations
Research, 45(1), 1-19. https://doi.
org/10.1007/BF02282039
4. Barry, T. A., Lepetit, L., & Tarazi,
A. (2011). Ownership structure
and risk in publicly held and
privately owned banks.Journal of
Banking & Finance,35(5), 1327-
1340. https://doi.org/10.1016/j.
jbankn.2010.10.004
5. Battese, G. E., & Coelli, T. J. (1995).
A model for technical ineciency
eects in a stochastic frontier
production function for panel
data. Empirical Eeconomics, 20(2),
325-332. https://doi.org/10.1007/
BF01205442
6. Beltratti, A., & Stulz, R. M. (2009).
Why Did Some Banks Perform
Better during the Credit Crisis? A
Cross-Country Study of the Impact
of Governance and Regulation
(Fisher College of Business
Working Paper No. 2009-03-012).
https://doi.org/10.3386/w15180
7. Bookstaber, R., Paddrik, M., &
Tivnan, B. (2018). An agent-
based model for nancial
vulnerability.Journal of
Economic Interaction and
Coordination,13(2), 433-466.
Retrieved from https://link.
springer.com/article/10.1007/
s11403-017-0188-1#citeas
8. Broll, U., Guo, X., Welzel, P.,
& Wong, W. K. (2015). e
banking rm and risk taking in
a two-moment decision model.
Economic Modelling, 50, 275-280.
https://doi.org/10.1016/j.econ-
mod.2015.06.016
9. Calluzzo, P., & Dong, G. N.
(2015). Has the nancial system
become safer aer the crisis?
e changing nature of nancial
institution risk.Journal of
Banking & Finance,53, 233-248.
104
Banks and Bank Systems, Volume 13, Issue 3, 2018
https://doi.org/10.1016/j.jbank-
n.2014.10.009
10. Conyon, M. J., & Peck, S. I.
(1998). Board size and corporate
performance: evidence from
European countries. e European
Journal of Finance, 4(3), 291-304.
11. Drehmann, M., & Tarashev, N.
(2013). Measuring the systemic
importance of interconnected
banks. Journal of Financial
Intermediation, 22(4), 586-
607. https://doi.org/10.1016/j.
j.2013.08.001
12. Drehmann, M., Sorensen, S., &
Stringa M. (2010). e integrated
impact of credit and interest
rate risk on banks: A dynamic
framework and stress testing
application. Journal of Banking &
Finance, 34(4), 713-729.
13. ElKelish, W. W. (2017). Corporate
governance risk and the agency
problem.Corporate Governance:
e International Journal of
Business in Society, 18(2), 254-269.
https://doi.org/10.1108/CG-08-
2017-0195
14. García-Marco, T., &
Robles-Fernández, M. D. (2008).
Risk-taking Behaviour and
Ownership in the Banking
Industry: e Spanish
evidence.Journal of Economics
and Business,60(4), 332-354.
https://doi.org/10.1016/j.jecon-
bus.2007.04.008
15. García-Palacios, J. H., Hasman,
A., & Samartín, M. (2014).
Banking crises and government
intervention. Journal of Financial
Stability, 15, 32-42. https://doi.
org/10.1016/j.jfs.2014.08.007
16. Gupta, K., Krishnamurti, C.,
& Tourani-Rad, A. (2013). Is
corporate governance relevant
during the nancial crisis? Journal
of International Financial Markets,
Institutions and Money, 23, 85-110.
https://doi.org/10.1016/j.in-
tn.2012.10.002
17. Haq, M., & Heaney, R. (2012).
Factors determining European
bank risk. Journal of International
Financial Markets, Institutions and
Money, 22(4), 696-718.
18. Haque, F., & Shahid, R. (2016).
Ownership, risk-taking and
performance of banks in
emerging economies: Evidence
from India.Journal of Financial
Economic Policy,8(3), 282-297.
https://doi.org/10.1108/JFEP-09-
2015-0054
19. Huang, X., Zhou, H., & Zhu, H.
(2009). A framework for assessing
the systemic risk of major
nancial institutions. Journal of
Banking & Finance, 33(11), 2036-
2049.
20. Iannotta, G., Nocera, G., &
Sironi, A. (2007). Ownership
structure, risk and performance
in the European banking industry.
Journal of Banking & Finance,
31(7), 2127-2149.
21. Kangis, P., & Kareklis, P. (2001).
Governance and organisational
controls in public and private
banks.Corporate Governance: e
International Journal of Business in
Society,1(1), 31-38.
22. Karas, A., Pyle, W., & Schoors,
K. (2013). Deposit insurance,
banking crises, and market
discipline: Evidence from a
natural experiment on deposit
ows and rates. Journal of Money,
Credit and Banking, 45(1), 179-
200. https://doi.org/10.1111/
j.1538-4616.2012.00566.x
23. Kaur Virk, G. (2017). e
inuence of board characteristics
on corporate illegality. Journal
of Financial Regulation and
Compliance, 25(2), 133-148.
https://doi.org/10.1108/JFRC-05-
2016-0045
24. Koerniadi, H., Krishnamur-
ti, C., & Tourani-Rad, A.
(2014). Corporate governance
and the variability of stock
returns. International Journal of
Managerial Finance, 10(4), 494-
510. https://doi.org/10.1108/IJMF-
08-2012-0090
25. Konishi, M., & Yasuda, Y. (2004).
Factors aecting bank risk taking:
Evidence from Japan.Journal of
Banking & Finance,28(1), 215-232.
26. Laeven, L., & Levine, R. (2009).
Bank Governance, Regulation and
Risk Taking. Journal of Financial
Economics,93(2), 259-275.
27. Macey, J. R., & O’Hara, M. (2003).
e corporate Governance
of Banks. Economic Policy
Review,9(1).
28. Mullineux, A. (2006). e
corporate governance of banks.
Journal of Financial Regulation
and Compliance, 14(4), 375-382.
29. O’Connor, T., & Byrne, J. (2015).
Governance and the corporate
life-cycle. International Journal of
Managerial Finance, 11(1), 23-43.
https://doi.org/10.1108/IJMF-03-
2013-0033
30. Philippas, D., Koutelidakis, Y., &
Leontitsis, A. (2015). Insights
into European interbank network
contagion. Managerial Finance,
41(8), 754-772. https://doi.
org/10.1108/MF-03-2014-0095
31. Polyzos, S., & Samitas, A. (2015).
Banking Crises & Contagion:
Why Worry About Taxation,
Output and the Cost of Capital?
Investment Management and
Financial Innovations, 12(2).
Retrieved from https://business-
perspectives.org/component/zoo/
banking-crises-and-contagion-
why-worry-about-taxation-out-
put-and-the-cost-of-capital
32. Reddy, K., & Locke, S. (2014). e
relationship between ownership
structure, capital structure
and corporate governance
practices: A case study of co-
operatives and mutuals in New
Zealand. International Journal of
Managerial Finance, 10(4), 511-
536. https://doi.org/10.1108/IJMF-
12-2012-0130
33. Riccetti, L., Russo, A., & Gallegati,
M. (2016). Financialisation
and crisis in an agent based
macroeconomic model.Economic
Modelling,52, 162-172. https://
doi.org/10.1016/j.econ-
mod.2014.11.028
34. Samitas, A., & Polyzos, S. (2016).
Freeing Greece from capital
controls: Were the restrictions
enforced in time? Research
in International Business and
Finance,37, 196-213. https://doi.
org/10.1016/j.ribaf.2015.11.005
35. Samitas, A., & Polyzos, S. (2015).
To Basel or not to Basel? Banking
crises and contagion. Journal
of Financial Regulation and
Compliance, 23(3), 298-318.
https://doi.org/10.1108/JFRC-11-
2014-0045
105
Banks and Bank Systems, Volume 13, Issue 3, 2018
36. Samitas, A., Polyzos, S., &
Siriopoulos, C. (2018). Brexit and
nancial stability: An agent-
based simulation.Economic
Modelling,69, 181-192. https://
doi.org/10.1016/j.econ-
mod.2017.09.019
37. Simper, R., Hall, M. J., Liu, W.,
Zelenyuk, V., & Zhou, Z. (2015).
How relevant is the choice of risk
management control variable
to non-parametric bank prot
eciency analysis? e case of
South Korean banks. Annals
of Operations Research, 250(1),
105-127. https://doi.org/10.1007/
s10479-015-1946-x
38. Sullivan, R. J., & Spong, K.
R. (2007). Manager Wealth
Concentration, Ownership
Structure and Risk in Commercial
Banks.Journal of Financial
Intermediation,16(2), 229-248.
39. Tsomocos, D. P. (2003a).
Equilibrium analysis, banking
and nancial instability. Journal
of Mathematical Economics, 39(5),
619-655.
40. Tsomocos, D. P. (2003b).
Equilibrium analysis, banking,
contagion and nancial fragility
(Bank of England Working Paper
No. 175).
41. Williams, J., & Nguyen, N. (2005).
Financial liberalisation, crisis,
and restructuring: A comparative
study of bank performance and
bank governance in South East
Asia. Journal of Banking & Finance,
29(8), 2119-2154.
42. Wong, J., Wong, T. C., & Leung, P.
(2007). A Leading Indicator Model
of Banking Distress – Developing
an Early Warning System for
Hong Hong and Other EMEAP
Economies December 18, 2007
(Hong Kong Monetary Authority
Working Paper No. 22/2007).
43. Wong, J., Wong, T. C., & Leung,
P. (2010). Predicting banking
distress in the EMEAP economies.
Journal of Financial Stability, 6(3),
169-179. https://doi.org/10.1016/j.
jfs.2010.01.001
44. Wu, X., & Li, H. (2015). Board
independence and the quality of
board monitoring: evidence from
China. International Journal of
Managerial Finance, 11(3), 308-
328. https://doi.org/10.1108/IJMF-
07-2014-0101
... In order to model the effects of banking crises on societal welfare, we extend the agent-based financial model of Polyzos et al. (2018) in order to include SWB and unemployment. The model is designed to simulate the behavior of economic agents and is loosely based on the work of Gourio et al. (2018) and Goodhart et al. (2004). ...
... In this section, we will describe the model in brief. Readers can refer to Polyzos et al. (2018) and Samitas et al. (2018) for the formal model definition and for detailed algorithmic steps. ...
Article
Purpose The purpose of this paper is to examine the link between banking crises and the subjective well-being of individuals. In addition, the authors examine the transmission of crises from the banking sector to well-being and show that negative financial shocks have significant adverse effects. Design/methodology/approach The authors employ agent-based modeling to test for the direct and indirect welfare effects of banking crises. The model includes a support vector machine (SVM) optimized subjective well-being function. The existing literature suggests that this is influenced by both the negative psychological effects of recessions and the adverse economic effects of income loss and increased unemployment. Findings The authors show that the different choices of policy response to a banking crisis carry different opportunity costs in terms of welfare and that societal preferences should be taken into account. The authors demonstrate that these effects influence different population classes in an asymmetric manner. Finally, the results demonstrate that the welfare loss of a bank failure is much higher than the cost of a bailout. Practical implications The authors are able to propose to the authorities the best policy mix in order to handle banking crises in the most adequate manner, according to society's preferences between financial stability and public goods. Social implications The findings extend the existing literature on subjective well-being, by quantifying the welfare cost of banking crises and showing that authorities should reconsider bank bailouts as a policy solution to bank distress. Originality/value The originality of this article lies in the use of an agent-based model to model the relationship between societal well-being and financial stability. Also, the authors extend existing agent-based methodologies to include machine learning optimization techniques.
... The lists factors associated with the non-completion of postgraduate studies, namely poor planning and management and methodological difficulties related to inadequate research knowledge. Over the years, the Eurozone banking industry observed financial distress, and there is a question about institution's ability for its regulation, supervision significantly policy implications (Polyzos et al., 2018). ...
Article
Full-text available
This paper is a speculative and exploratory essay on the emerging field of social accounting practices in Bangladesh. The study's main objective is to explore accountants' perceptions and attitudes towards Bangladesh's social accounting practices (SAP). Eighty accountants (chartered accountants and chartered management accountants working in the professional field level) of different firms were selected based on access priority from DSE. The study specifically used a mixed method. The study yielded a general overview of SAP in Bangladesh, where almost 77% of accountants followed SAP at their respective organizations differently. The study emphasized that SAP has a multifaceted conception where the company, managerial, and single firms act together. The practical implementation of this study relates to the professional level of education required for social accounting practice. This study concludes that SAP in Bangladesh is not up to the mark and needs to redesign a strategic plan.
... However, more recent research places the focus on other variables as well (Polyzos, Abdulrahman, & Christopoulos, 2018). Holm-Hadulla and Thürwächter (2021) demonstrate that corporate debt structure is an important determinant of the transmission on monetary policy, suggesting the yield curve as the potential engine. ...
Article
The current paper examines the asymmetric effects of changes to monetary and fiscal variables on different types of firms in the UAE. We compute impulse responses based on local projections and select shock and switching variables using machine learning. We examine 180 firms listed in the UAE exchanges and find significant asymmetries among financial and non-financial firms and among low- and high-debt firms when there is a shock to macroeconomic monetary or fiscal variables. Quartile analysis shows that firms belonging to the first and last quartile of debt respond negatively to expansionary policies, while middle-quartile firms respond more positively. Our results demonstrate the importance of comprehending the heterogeneity in the micro characteristics of the underlying corporate environment when evaluating macroeconomic policies. Our work can facilitate the design and implementation of policy in the UAE and helps explain the transmission mechanisms towards corporations.
... This study is in line with the results of Samuel's (2014) study. In the research results of Polyzos, et al. (2018) stated that the LDR variable has a positive and significant effect on financial distress. Meanwhile, NPL has a negative and significant effect on financial distress. ...
Article
Full-text available
This study aims to investigate determinants of financial distress rural banks in Indonesia using logit approach. The method used in this study uses logit. The data used are secondary data obtained from Bank publication reports during period 2014-2018. The population used in this study is rural banks in Indonesia and sample selection based on purposive sampling evidence East Java. The results showed that capital, profitability and productivity have significant influence to financial distress bank. Rural banks should maintain adequate capital, increase profits and maintain credit growth in order to avoid financial distress. This study is useful to determine the determinants of rural bank financial distress in Indonesia by using the logit approach, adopting the Altman variable and adding the credit risk variable.
... Banking supervision pays little importance to the corporate governance features of financial institutions pre-and post-merger. Recent evidence shows that authorities seem to focus more on capital requirements, which hinder banking activity, with adverse effects on the real economy and society and focus less on corporate governance (Polyzos et al., 2018). ...
Article
Full-text available
Purpose The purpose of this paper is to examine the effects of bank mergers on systemic and systematic risks on the relative merits of product and market diversification strategies. It also observes determinants of M&A deals criteria, product and market diversification positioning, crisis threshold and other regulatory and market factors. Design/methodology/approach This research examines the impact and association between merger announcements and regulatory reforms at bank and system levels by investigating the impact of various bank consolidation strategies on firms’ risks. We estimate beta(s) as an index of financial institutions’ systematic risk. We then develop an index of the estimated equity value loss as the long-rum marginal expected shortfall (LRMES). LRMES contributes to compute systemic risk (SRISK) contribution of these firms, which is the capital that a firm is expected to need if we have another financial crisis. Findings Large acquiring banks decrease systemic risk contribution in cross-border M&As with a non-bank financial institution, and witness profitability (ROA) gains, supporting geographic diversification stability. Capital requirements, activity restrictions and bank concentration increase systemic risk contribution in national mergers. Bank mergers with investment FIs targets enhance productivity but impair technical efficiency, contrary to bank-real estate deals where technical efficiency change accompanied lower systemic risk contribution. Practical implications Financial institutions are recommended to avoid trapped capital and liquidity by efficiently using local balance sheet and strengthening them via implementing models that clearly set diversification and netting benefits to determine capital reserves and to drive capital efficiency through the clarity on product–activity–geography diversification and focus. This contributes to successful ringfencing, decreases compliance costs and maximises returns and minimises several risks including systemic risk. Social implications Policy implications: the adversative properties of bank mergers in respect of systemic risk require strict and innovative monitoring of bank mergers from the bidding level by both acquirers and targets and regulators and competition supervisory bodies. Moreover, emphasis on regulators/governments intervention and role, as it provides a stabilising factor of the markets and consecutively lower systemic risk even if the systematic idiosyncratic risk contribution was significant. However, such roles have to be well planned and scaled to avoid providing motives for banks to seek too-big-too-fail or too-big-to-discipline status. Originality/value This research contributes to the renewing regulatory debate on banks sustainable structures by examining the risk effect of bank diversification versus focus. The authors aim to address the multidimensional impacts and risks inherent to M&A deals, by examining the extent of the interconnectedness of M&A and its implications within and beyond the banking sector.
... They find that systemic risk in the sample economies is mostly responsive to own-country financial shocks, even though shocks from neighboring countries may also be propagated to a certain extent. Polyzos et al. (2018) show that systemic risk could also stem from governance issues related to each banking institution. On the other hand, Zimmer (2014) proposes a copula-based approach to model co-movements in house prices and finds that conflicting results between the US and other OECD countries. ...
Article
Full-text available
This paper discusses the volatility spillovers between the Greek Debt crisis and the Cypriot financial crisis. Cyprus was in the spotlight of financial markets due to significant problems stemming from the banking sector, which were dealt with by EU regulators with a bail-in on bank deposits. The current analysis aims to shed light on the reasons behind the implementation of this novel approach to bank distress. The study uses a Dynamic Conditional Correlation model on the returns of the stock markets of the two countries, which shows strong spillover effects during the period leading up to the 2013 Cypriot crisis, but a significant decrease of these effects from then on. The results confirm the close interdependence of the Greek and Cypriot economies before 2013 but also show that this interdependence was limited from that point onwards. This would indicate that since the risk of contagion to the Eurozone had diminished, regulators were able to test the bail-in solution in Cyprus in 2015. The current work contributes to the discussion on the interdependence of European economies. The paper’s findings can also be applied to other emerging European economies.
... The concept of board independence (i.e., the inclusion of non-executive and independent non-executive members on corporate boards) is considered fundamental in governance literature and dates back as early as in the mid-'70s (see Jensen and Meckling, 1976). The main argument is that board independence can reduce agency problems since the addition of outsiders can increase the monitoring of executive directors and mitigate the level of investment risk undertaken by risk-seeking executives (Brick and Chidambaran, 2008;Pathan, 2009;Polyzos et al., 2018). The so-called as 'reputation hypothesis', as defined by Fama (1980), supports that non-executives will honour their role as stakeholders' 'protection shield' against excessive corporate risk-taking, simply because they would not jeopardise their own reputation in the business world. ...
Article
This paper investigates the impact of a variety of corporate governance mechanisms on the performance of banks listed on the London Stock Exchange (LSE), by utilising data collected for 52 banking institutions for the period 2012 to 2017. Exhaustive results derived from multi-model applications document the superiority of GMM models to examine these relationships. Based on robust empirical findings, we support that increasing board size, especially the number of non-executive directors, and the frequency of board meetings up to a certain point could prove to be beneficial for the listed banks on the LSE. Moreover, our findings imply that simply complying with the Governance Code including independent board members or following the trend of gender diversity without proper evaluation of executives’ skills could damage bank efficiency. Finally, this study fails to discern significant links between the number of foreign directors and CEO-Chairman duality with the performance of the UK banks.
Article
Purpose This paper models the benefits of Islamic banking on the efficiency of the banking sector and on societal happiness. This paper aims to examine how the adoption of Islamic banking to various degrees affects economics outcomes. Design/methodology/approach This study uses machine-learning tools to build a happiness function and integrate it in an agent-based model to test for the direct and indirect welfare effects of implementing Islamic banking principles. Findings This study shows that even though Islamic banking systems tend to reduce economic activity, financial stability and societal happiness is improved. Additionally, a banking sector using Islamic principles across all its members is better equipped to handle banking crises because contagion to both economic activity and societal welfare is greatly reduced. At the same time, adoption of the profit-and-loss sharing (PLS) paradigm by banks may also slow down economic growth. Research limitations/implications The findings extend existing literature on the advantages of Islamic banking, by quantifying the welfare benefits of the PLS paradigm on happiness and financial stability. Originality/value To the best of the authors’ knowledge, this paper is the first to combine agent-based modelling with machine learning tools to examine the benefits of the Islamic banking model on financial stability, social welfare and unemployment.
Article
This study investigates the regional differences in how consolidation has affected the efficiency of Shinkin banks, a representative cooperative financial institution in Japan, using the stochastic meta‐frontier approach based on cost and profit functions. The findings support the quiet life hypothesis that a significant negative relationship exists between efficiency‐adjusted Lerner indices and cost efficiency. By contrast, the relation between market power and profit efficiency is consistently positive. Moreover, independent Shinkin banks not involved in mergers exhibit higher costs and profit efficiency than other banks, suggesting that mergers can deteriorate efficiency.
Article
Full-text available
The board of directors typically selects and removes officers, initiates fundamental changes, determines capital structure, adds, amends, or repeals bylaws (such as mergers and divestitures), declares dividends and sets the compensation for officers and management. The segregation of duties involves assigning different employees to perform functions so that an employee acting alone is prevented from committing an error or concealing a fraud in the normal course of their duties. Four types of functional responsibilities should be segregated: the authority to execute transactions, the recording of transactions, custody of the assets affected by the transactions and periodic reconciliation of existing assets to recorded amounts. There are several studies on the influence of corporate governance in developed markets relating to a variety of aspects. However, in the context of the Jordan market, such researches are rare. The paper analyses the governance practices of 13 Jordanian listed banks listed. The main findings of the study are that there is a positive relationship between board sizes and earnings management (EM) through discretionary accruals, that there is no relationship between independence and segregation of duties, and that EM through discretionary accruals and board size mediates the association between corporate governance structure and (EM) through discretionary accruals.
Article
Full-text available
As the UK and the EU prepare to start negotiations for Brexit, it is important for both sides to comprehend the full extent of the consequences of this process. In this paper, we employ an agent based simulation framework in order to test for the short-term and long-term effects of Brexit on financial stability on both sides of the Channel. The relative strength of the UK economy and the banking sector vis-à-vis the EU is taken under consideration. Our results confirm predictions in the relevant literature regarding the output cost of Brexit, with particular emphasis on the EU, and show that financial stability is an important issue, with the banking system suffering significant losses on both sides, particularly over the longer term. Our findings also suggest that policymakers should take into account dynamic effects that may be caused by UK banks moving to the EU after Brexit. The model results show that if banks in the UK chose to move across the Channel, the negative effects in the EU are mitigated.
Article
Full-text available
This study addresses a critical regulatory shortfall by developing a platform to extend stress testing from a microprudential approach to a dynamic, macroprudential approach. This paper describes the ensuing agent-based model for analyzing the vulnerability of the financial system to asset- and funding-based fire sales. The model captures the dynamic interactions of agents in the financial system extending from the suppliers of funding through the intermediation and transformation functions of the bank/dealers to the financial institutions that use the funds to trade in the asset markets. The model replicates the key finding that it is the reaction to initial losses, rather than the losses themselves, that determine the extent of a crisis. By building on a detailed mapping of the transformations and dynamics of the financial system, the agent-based model provides an avenue toward risk management that can illuminate the pathways for the propagation of key crisis dynamics such as fire sales and funding runs.
Article
Full-text available
Purpose This paper examines the effect of ownership structure on bank risk-taking and performance in emerging economies by using India as a case study. Design/methodology/approach We use generalised method of moments (GMM) estimation technique to analyse an unbalanced panel data set covering 217 bank-year observations from 2008 to 2011. Findings Overall, our study results suggest that government ownership is positively associated with default risk and negatively related to bank profitability. Interestingly, we find foreign ownership having a positive effect on default risk and a negative effect on profitability among the listed commercial banks. The effect of ownership concentration on bank risk-taking and profitability appears to be statistically insignificant. Originality/value This study is among the first to consider the impact of ownership on bank risk-taking and profitability from an emerging economy perspective. It also addresses the problem of endogenous relationships among ownership, risk-taking and performance of a bank. This study is likely to have implications for policymakers in undertaking regulatory reforms relating to ownership, risk management and banking sector stability.
Article
Purpose This study aims to investigate the relationship between corporate governance risk and agency costs across different countries. Design/methodology/approach Corporate governance risk indicators were obtained from the Institutional Shareholder Services Europe (S.A.) for 4,135 firms across 27 countries. Agency costs and other control variables were derived from companies’ annual financial reports using the DataStream database. Ordinary least squares multiple regression analysis model was used to test the study hypothesis. Findings Agency costs have a significant negative impact on corporate governance risk across countries. The extent of corporate governance mechanisms used, however, varies across geographic regions and industry types. The relationship between corporate governance risk and agency costs is more obvious in the non-financial than financial sector. These results were robust after several statistical checks. Practical implications The findings will help stakeholders, including corporate management, regulators and investors to improve corporate governance mechanisms and capital allocation decisions across countries. Originality/value Evidence is provided on the role of agency costs in corporate governance risk across geographic regions for financial and non-financial companies. The paper also overcomes common problems in corporate governance research such as construct validity, limited data and endogeneity.
Article
Purpose In light of frequent corporate scams and frauds, this paper aims to investigate the relationship of corporate illegality with the board of directors’ characteristics in Indian manufacturing companies. Design/methodology/approach The board of director characteristics of sample companies charged with violation of the Securities Exchange Board of India (SEBI) regulations from 2008 to 2013 are matched to an equivalent-sized control data set. A cross-sectional logistic regression model is applied to test the hypothesized association. Findings The findings suggest that the SEBI violations are less likely to occur when a large fraction of the board of directors consists of independent directors and when the individual directors have multiple appointments on the boards of other companies. However, it is observed that the size of the board and its meetings have no observable association with violation of the SEBI regulations. Research limitations/implications This work is likely to aid future research in exploring the impact of governance mechanisms on the occurrence of illegality. In future, studies may be conducted to investigate the probability of illegal corporate events using a larger sample size and corporate governance variables which have not been examined in the present study. Practical implications The analysis provides corporate policy makers and investors an insight to evaluate the vulnerability of a company being engaged in illegality based on its board features. Originality/value The present study is distinct from previous reports as it makes a novel attempt to gauge the relationship between the board of directors’ characteristics and the occurrence of illegality in the Indian corporate section.
Article
Purpose – The purpose of this paper is to analyse the importance of interbank connections and shocks on banks’ capital ratios to financial stability by looking at a network comprising a large number of European and UK banks. Design/methodology/approach – The authors model interbank contagion using insights from the Susceptible Infected Recovered model. The authors construct scale-free networks with preferential attachment and growth, applying simulated interbank data to capture the size and scale of connections in the network. The authors proceed to shock these networks per country and perform Monte Carlo simulations to calculate mean total losses and duration of infection. Finally, the authors examine the effects of contagion in terms of Core Tier 1 Capital Ratios for the affected banking systems. Findings – The authors find that shocks in smaller banking systems may cause smaller overall losses but tend to persist longer, leading to important policy implications for crisis containment. Originality/value – The authors infer the interbank domestic and cross-border exposures of banks employing an iterative proportional fitting procedure, called the RAS algorithm. The authors use an extend sample of 169 European banks, that also captures effects on the UK as well as the Eurozone interbank markets. Finally, the authors provide evidence of the contagion effect on each bank by allowing heterogeneity. The authors compare the bank’s relative financial strength with the contagion effect which is modelled by the number and the volume of bilateral connections.
Article
Purpose – In 2001, the China Securities Regulatory Commission required that at least one-third of the members of corporate boards of directors come from outside the organization. The purpose of this paper is to investigate the impact of this change of regulation on corporate governance in China. In particular, the authors examine whether the increase in the proportion of outsider directors can increase the monitoring quality of the board. Design/methodology/approach – The basic empirical methodology is a logit regression in which the dependent variable is a binary variable that represents one of the three “negative events” identified as the indicators of poor monitoring quality. The independent variables are firm-level control variables. Findings – Using Chinese stock data from 1999 to 2005, the authors find that the resulting increase in board independence has reduced the occurrence of connected transactions and violations such as financial statement fraud, illegal insider trading, and asset misappropriation. However, this positive effect of board independence is not uniform across firms. The authors show that a higher degree of fundamental uncertainty in a firm impedes the effectiveness of board independence. The authors also document that the level of board independence is positively associated with firm performance, as measured either in stock market return or accounting return. Originality/value – In this paper, the authors aim to investigate the effectiveness of outsider directors in a more direct way than has previous research. The authors measure the improvement in the quality of board monitoring by the reduction of the likelihood of those corporate events that could reduce firms’ value. In particular, the authors examine the relationship between the board independence and the occurrence of “negative” corporate events in China. To the best of the knowledge, this is the first study that explores the link between board independence and the probabilities of these events.
Article
The prediction and consequences of banking crises continue to be a fab in academic and political discussions. Researchers attempt to describe the link between these crises and the real economy. In this paper, we present an object oriented model that attempts to establish the relation of the real economy to banking crises and contagion. We describe a set of extensions to Virtual Banking, an object oriented model which can be used to carry out simulations on the banking system of a hypothetical economy. We expand our existing work by proposing a link between the banking system and the real economy, incorporating fiscal issues. We present the empirical results of the model and discuss proposed policy implications. Our findings confirm existing literature which places criticism on the ability of the regulatory measures of Basel III to prevent or handle banking crises. However, the proposed measures seem to be effective in protecting the real economy from financial crises.