Demand Deposit Contracts and Probability of Bank Runs in Nigeria
OGBEBOR PETER IFEANYI, AWONUGA ADESOLA RUKAYAT,
AKANDE FOLORUNSHO ILESANMI, ADEMOLA OLUFEMI CHRISTOPHER
Department of Finance of Finance,
Babcock University,
Ilishan-Remo, Ogun State,
NIGERIA
Abstract: - The problem of bank runs is a global phenomenon and often damaging to the banking systems both in
developed and developing countries. Monetary authorities always find it very difficult to resolve such a crisis;
hence, it became imperative to examine this scenario in the case of Nigeria. Therefore, we examined the effect of
demand deposit contracts on the probability of bank runs in Nigeria. This is considered a major contribution to the
literature on finance from the perspective of an emerging market economy (EME). In this study, a multilevel Tobit
regression approach was employed. This study identified statistically significant and positive effects of liquid
assets (total assets) and total loans (total deposits) on bank runs in Nigeria. Based on the results, the study
concluded that bank-specific factors have an effect on bank runs, and from these variables, liquid assets/total assets
and total loans/total deposits have significant effects on bank runs. As a sequel to the findings and conclusion of
this study, it was recommended that to avoid such a banking crisis, there is a need for deposit money banks in
Nigeria to maintain adequate liquid assets and ameliorate the high level of deterioration in the quality of risk assets
as well as the cost of funds.
Key-Words: - bank runs, demand deposit contracts, deposit money banks, liquid assets, non-performing loans.
Received: April 19, 2023. Revised: February 15, 2024. Accepted: March 6, 2024. Published: April 5, 2024.
1 Introduction
Financial institutions play a dynamic and
fundamental role in the growth of any economy, and
the success of this role further depends on the
structure of the macroeconomy. Banking occupies
one of the most significant positions in the financial
system. A bank run happens if depositors start to
withdraw money from banks out of concern that the
institutions may run out of funds, which, in severe
cases, leads to bank failures. Instead of actual
insolvency, a bank run often results from panic. An
example of a self-fulfilling prophecy would be a bank
run, which is the result of panic pushing a bank into
actual insolvency. The bank faces the risk of failing if
customers keep taking their deposits out of
circulation. Thus, what appears to be panic may
become a genuine default. The failure of banks, in
the opinion of [1], has very serious consequences for
households, businesses, and governments as it
increases the rate of unemployment, a source of
financial disintermediation, resulting in shallow
financial depth, weak capital accumulation, and a
general decrease in purchasing power. This
presupposes that the failure of deposit-taking
institutions should be avoided by national regulators
due to their damaging effects on the whole economy,
as the cost of resolution is always a huge burden on
taxpayers. Besides, [2], noted in their research that in
countries with markets that are tranquil, there are
attempts to avoid crises, and this is done through
general policies such as the introduction of deposit
insurance and the prescription of minimum
benchmarks in the form of capital adequacy levels.
However, deposit insurance has not been adequate in
preventing the collapse of financial institutions, as
the experience of the last global financial crisis has
shown. The types of customers’ bank accounts allow
withdrawals without prior notice, have no maturity
period, and have no limit on the number of
withdrawals; hence, banks that are not well-
capitalized become susceptible to failure when a
large number of depositors withdraw their deposits
en- masse. Banking firms are profit-oriented and earn
income from several sources, but the major source of
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Ogbebor Peter Ifeanyi, Awonuga Adesola Rukayat,
Akande Folorunsho Ilesanmi, Ademola Olufemi Christopher
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these is non-traditional income sources, such as
trading with customers’ deposits and, in the process,
creating risky assets. This inevitably exposes the
entities to risks that, if not mitigated, could cause
both solvency and liquidity issues, such that distress
may set in. Banking, as defined by [3], is the business
of maturity transformation, or “borrowing short to
lend long.” Term lending is one of the arrays of
services banking firms render to households,
corporate entities, and governments. In this direction,
they function to create further wealth out of available
financial resources, taking cognizance of particular
organizational risk parameters. Loanable credit
decisions are generally associated with significant
risks. Sequel to this, [4], averred that these call for
both caution and tact. Some studies, such as those by
[5] and [6], were more concerned with evaluating the
determinants of DMB’s credit portfolios, but how a
solvent, liquid, and profitable bank can fail due to the
nature of demand deposit contracts, which allow
large withdrawals of deposits by customers, has not
been well investigated.
Banking distress has characterized the Nigerian
banking environment. For instance, [7], exposed that
in the early 1990s, Nigeria's domestic savings as a
GDP percentage fell sharply to 6%, and the country's
saving-to-GDP ratio averaged just 11.3% annually
during that time due to the crisis in the banking
industry. Systemic distress in the financial sector can
lead to macroeconomic disequilibrium, which can
negatively affect credit availability with the
consequent reduction in output. On their part, [8],
attested to the damaging effects of macroeconomic
instability caused by disappointment in the banking
business, pointing out that manufacturing capacity
use dropped from 8.7% in 1986 to a low level of
5.4% in 1995 in the domestic economy. According to
[9], the contribution of manufacturing as a percentage
of GDP as of December 2020 stood at 8.5%. [8],
further pointed out that banking distress in Nigeria
weakens its ability to attract foreign direct
investment, leading to a significant rise in the poverty
level in Nigeria. Statistics provided by [10], showed
that net capital flows in Nigeria declined from
US$103,033.18 in 2013 to US$24,804.97 in 2017.
This decline translates to about 315% and justifies
the argument by [8], of the rise in the poverty level in
Nigeria. Based on these statistics and the results of
research findings, the issue of banking distress
deserves more investigation, as the sector is critical
to the economic development of Nigeria. The issue of
the collapse of deposit money banks (DMBs) has
remained a worrisome situation in Africa’s largest
economy, considering its grave implications and
consequences for the overall financial health of the
country. Between 1998 and 2006, licenses for 45
DMBs were revoked in Nigeria, [11]. It can be
argued that poor governance and a high level of non-
performing loans, among other issues, may have
accounted for the high rate of failures of these banks,
but the nature of demand deposit contracts with their
customers and their effects on increasing the
likelihood of bank runs have not been sufficiently
researched, hence this study. This is particularly
worrisome because of the issue of contagion due to
the nature of the interconnection of demand deposit
banks (DMBs). In fact, [12], pointed out that as
DMBs are interconnected with each other due to the
nature of banking activities, the failure of one will
have spillover effects on not only the stakeholders of
the failed entity but on the stakeholders of other
entities due to the contagion effect. Based on this
argument, we hypothesize that demand deposit
contracts have no significant effect on bank runs in
Nigeria. The issue of bank runs remains a major
concern for DMBs’ clients, employees, shareholders,
the government, and other stakeholders. The issue of
bank failures has largely remained unsolved, despite
regulators' persistent efforts, which led to the creation
of the Nigerian Deposit Insurance Corporation
(NDIC). Aside from these recent occurrences, there
isn't much documentation on how deposit
withdrawals from different banks spread throughout
Nigeria.
Despite the contagious nature of Nigerian banks,
there is a dearth of study in the literature concerning
the effect of deposit money contracts being
incomplete contracts on the high rate of bank
failures in Nigeria. More so, the existing literature
points to a growing amount of guidance on the
underlying causes of bank runs in developed
countries, but not enough evidence exists in the case
of emerging economies; hence, this study focuses on
Nigeria. Besides, the role of demand deposit
contracts, which are incomplete, as a primary cause
of bank runs in the case of advanced economies
exists in the literature. Deposit withdrawals from a
distressed bank can cause withdrawals at other
similar banks in the same region, particularly if these
banks have interbank exposures to the distressed
bank, according to recent bank-level evidence, [13].
The motivation for this study is the highly influential
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work of [14], with the same title as this. However,
the implication of this study as a Nigerian case study
was that bank runs are a common occurrence in the
Nigerian banking system, despite the severe crises
that have been prevalent throughout its economic
history. Because the reasons why bank contracts are
less stable than other forms of financial contracts in
a low-income country like Nigeria have not been
adequately addressed by current theoretical analysis,
the study's findings will significantly shed light on
the characteristics of previous bank runs in the
country. Therefore, this is a domestication of that
study in the case of a developing country
characterized by financial crises as well as weak
distress resolution mechanisms based on the high
rate of institutional failures. In fact, [14], claimed
that when numerous clients take all of their money
out of their accounts at once out of concern that the
institution might go bankrupt, there is a liquidity
issue. In fractional reserve systems, deposit-taking
institutions only keep a small percentage of their
assets in cash. As more customers withdraw their
money, there is a likelihood of default in such banks,
and this will trigger more withdrawals to the point
where the outfit runs out of cash. [15], asserts that
the likelihood of bankruptcy increases with the
amount of money taken out, which leads to even
more withdrawals. To address the panic, the
institution may restrict the number of withdrawals
made by any one customer or halt all withdrawals.
Also, the organization may get more cash from other
banks or from the Central Bank to increase its cash
on hand. [16], asserts that since a banking firm
typically keeps only a small percentage of deposits
as cash on hand, it must increase their cash position
to meet the withdrawal demands of their customers.
One method that can be used to increase cash on
hand is to sell off assets, sometimes at significantly
lower prices. This may result in huge losses to the
organization, as sales are often at huge discounts to
solve urgent liquidity needs. The empirical literature
emphasizes the role of firm characteristics, customer
behavior, the nature of bank-customer relationships,
and the extent to which panic triggered could lead to
massive withdrawals of funds by bank customers,
but some of the predictor variables used in the
analysis of this study are scanty in the literature.
This, therefore, presupposes that there is a need to
upscale research in this field following the present
concern regarding the issue being investigated. Non-
performing loans, loan-to-deposit ratio, net interest
margin, firm size, and firm age are important
crucibles that affect the financial performance and,
indeed, the overall stability of banking firms, which
influence customers’ decisions whether to withdraw
or not in the event of financial fragility. The nature
of demand deposit contracts, which may arise due to
the behavioral patterns of bank depositors in the
event of a trigger in bank runs, is, therefore, a cause
for concern in an environment that has witnessed a
mass of bank failures. Besides, economists,
policymakers, academics, and business owners take
cognizance of this fact regarding their perception of
the capability of financial institutions to withstand
shocks that could lead to the instability of such
institutions. Hence, the main objective of this
research is to evaluate the effects of deposit money
contracts on the probability of bank runs in Nigeria.
2 Literature Review
2.1 Theoretical Review
The Modern Theory of Financial Intermediation
serves as the foundation for this investigation. The
modern theory of financial intermediation, which
incorporates both traditional theory and
modifications to the financial environment, was
introduced by [17]. According to [18], financial
development has a big impact on economic
expansion. The author made it clear that the financial
system makes transactions easier, reduces risk,
mobilizes savings, distributes savings, and keeps an
eye on managers' actions after funding projects. This,
therefore, explicates the fact that the efficiency of
operations, especially interest rate management, is
highly imperative. [19], defined financial
intermediation as the process of financial resource
mobilization through intermediaries for subsequent
lending to needy economic units. This theory, as
formalized by the studies of [20], [21] and [22],
views financial markets as pivotal players in
economic development. These studies revolve around
the postulation that financial developments spur
economic growth and account for the differences in
the prosperity of nations. [23], on the contrary,
argues that financial markets merely depend on
domestic industry and, as such, only grow to service
the same. [21] and [22], argue that policies leading to
the repression of such markets reduce the incentives
to save. These authors identified within the context of
this work that bank deposits refer to the various
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compositions of deposits held by banks at any point
in time. [24], assert that generally, deposit rates,
inflation rate, and money supply, among others,
theoretically influence the composition of bank
deposits.
2.2 Empirical Review
[15], averred that the role of a society’s income level
and distribution could also influence the level and
composition of deposits. [25], enthused that
seasonality and festivity factors significantly
influence people’s savings habits, while [15],
observes that inflation tends to negatively affect the
level of banks’ deposits. At the same time, [26],
argues that when other investment outlets seem less
appealing, people tend to patronize time deposit
accounts as an alternative investment outlet for their
surplus funds. [27], stated that concerning the
European and US established, the net interest
margins of banks were significantly influenced by the
different institutional designs of capital-based, but in
the case of continental Europe, bank-based markets.
It can be argued that a well-capitalized firm would be
in a better position to withstand short-term liquidity
shocks that could precipitate a liquidity crisis.
The Russian banking system is used as a testing
ground, [28], to examine the interactions between
risk-based deposit insurance, deposit rates, and bank
failures. The results of a CAMEL analysis show that
when a fixed-rate deposit insurance system is
replaced with a risk-based system with premia linked
to insured deposit rates provided by a bank, the cost
of insured deposits becomes a predictor of bank
failures, private banks lacking excessive capital stop
raising insured deposit rates to fund loan growth and
increases in bank risk lead to a decrease in reliance
on insured deposits. Banks will no longer offer
insured deposit rates that are significantly higher than
the market. The findings imply that risk-based
deposit insurance programs that discourage high
insured deposit rates may aid in lowering bank moral
hazard.
The Diamond-Dybvig model of bank runs is
expanded by [29], to include a deposit amount
requirement. The study establishes an equivalency
result, showing that, if the deposit level is above a
particular threshold, efficient allocation is possible in
equilibrium when the propensity to run is zero. The
lower the deposit level within this range, the more
tempted patient depositors are to withdraw early. The
best banking system involves less-than-full deposits
and follows the equilibrium path when the propensity
to run is positive and specific requirements are
satisfied.
[30], investigated contagion that runs in banks.
The study found that when a player withdraws from
one bank, it increases their belief that other players in
their own company will also withdraw, which
increases their likelihood of withdrawing. This
phenomenon is known as the "trigger" effect. By
emphasizing that panicked withdrawals impact
depositors' beliefs and are therefore contagious, but
only if depositors are aware that there are financial
connections between their institution and the
observed institution, the authors made a crucial
observation. Underscoring the significance of bank-
depositor relationships in preventing bank runs, [13],
established that banks’ relationships with their
depositors help them reduce the issue of financial
fragility and that uninsured depositors are most likely
the first to run. This establishes the role of heuristics
in the probability of bank runs, which extends the
argument of animal instincts among banking firms’
customers since behavior affects customers' decisions
to withdraw their deposits or not.
[31], examined Nigerian savings, inflation, and
the effects these factors have on economic expansion.
Using the 2-stage least squares (2SLS) method to
extract annual time series data from Nigeria from
1980 to 2013, they found that while the exchange rate
had a positive effect on economic growth, inflation
had a negative relationship with both real interest
rates and economic growth. [32], used time series
data from 1990 to 2012 to examine the relationship
between market structure and bank profitability in
Nigeria. The collusion hypothesis was tested using
time-series techniques of co-integration and error-
correction mechanisms to determine whether a long-
run relationship exists between the profits of
commercial banks and concentration in the banking
industry. The findings demonstrated a long-term
correlation between the likelihood of bank runs and
the makeup of the Nigerian banking industry.
[33], used an exploratory research design to
further consider the issues arising from the Nigerian
interbank market. Regulatory interventions
occasionally impede the efficient distribution of
funds in the market, in addition to the inefficiencies
brought on by the interaction of market forces.
bolsters the argument that adjustments to the ratio
should be made infrequently and only when there is a
compelling reason not to use market-based
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instruments (such as government or CBN securities);
this suggests that using government or CBN
securities that represent open market operations is a
viable architecture for the implementation of
monetary policy.
The study between demand deposit contracts and
the probability of bank runs in Nigeria is relevant to
the recent state of the Nigerian banking sector.
However, little literature is available. Furthermore,
the little literature available is concentrated in the
developed economies, with no study documented in
the jurisdiction of this study. Therefore, this study
intends to fill these gaps by examining the effects of
demand deposit contracts on the probability of bank
runs in Nigeria.
3 Methodology
3.1 Research Design, Population, and
Sampling
This study employed an ex-post facto research
design, which is important as the study employed
data that have already been validated. The population
of the study comprised all sixteen (16) banks listed
on the Nigerian Exchange as of December 31, 2021.
The purposeful sampling technique was used in
selecting thirteen (13) banks as of December 2021,
which formed the sample size. These banks were
selected about the volume of their assets over the past
ten years, as well as banks with an updated financial
report and also based on the availability of data. The
thirteen (13) banks listed on the Nigerian Stock
Exchange as of December 2020 are First Bank of
Nigeria Holding Co. (FBNH) Plc., Guaranty Trust
Bank (GTB) Plc., Zenith Bank Plc., Access Bank Plc,
Stanbic IBTC Bank Plc, United Bank for Africa
(UBA) Plc, Fidelity Bank Plc, First City Monument
Bank (FCMB) Plc, Sterling Bank Plc, Unity Bank
Plc., Wema Bank Plc., Union Bank of Nigeria Plc.,
and Ecobank Nigeria Plc. This study covered a
period of twelve (12) years, which is from 2010 to
2021.
3.2 Nature and Sources of Data
Secondary data were employed in this study. The
data were panel in nature and were sourced from
audited annual financial reports and accounts of
selected deposit money banks listed on the Nigerian
Exchange Ltd. The data were sourced in the period
covering 12 years (2010–2021).
3.3 Model Specification
The multilevel Tobit regression model was adopted
and its simple form is presented below:
(1)
(2)
When censorship is applied, the Equ. (1) becomes:
(3)
The Marginal Effects on the latent variables can be
computed as;
(4)
In other to properly capture the work of
Goldstein and Panzer (2005), empirically, the above
models are specified as follows:
(5)
(6)
Where;
NPL = Non-performing loans
LDR = Loan-to-deposit ratio
DSD = Demand Deposit Contracts
NIM = Net Interest Margin
FSZ = Firm Size
FAG = Firm Age
= Random error term
and are observed (latent)
variables from NPL and LDR that are rightly
censored at 5% and 65% threshold (as prescribed by
CBN). The 5% and 65% simply serve as the
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threshold in our regression models because higher
NPL and LDR ratios indicate that the banks are at
greater risk of loss.
3.4 Method of Data Analysis
In this study, a multilevel Tobit regression approach
was used. Multilevel panel-data models or mixed-
effects models are considered to have both fixed
effects and random effects for which the outcome is
censored. This approach has been used extensively
on different outcomes (ordered, counted, or binary)
and in diverse fields. The approach follows the
Maximum Likelihood (ML) approach. Marginal
effects on observed (latent) variables were computed
and interpreted in probability form. The choice of
this approach is informed by the fact that the models
are made for censored (at a threshold h) dependent
variables; they can also fit panel data models; and
they allow the prediction of the probability of having
latent variables above the prescribed limit, which
may lead to bank runs. Under this approach, an LR
test is conducted comparing the multilevel fixed-
effect models with one-level ordinary linear
regression. However, the significance of this test’s
result suggests that multilevel fixed-effect models are
preferred. Before the multilevel fixed-effects
regression analysis, descriptive analysis that gave
basic statistics and highlighted the possible
associations among the variables of interest at a
glance was carried out using common statistical tools
such as mean, median, minimum, maximum, and
standard deviation.
4 Results and Discussion
The results and findings are presented and discussed
in this section. The section opens with a descriptive
statistic regarding the profitability of bank runs in
Nigeria and demand deposit contracts. The
correlation matrix, which illustrates the degree of
association between the dependent and independent
variables, is presented after this. The potential for
multicollinearity among the explanatory variables
was also assessed using the correlation coefficients of
the explanatory variables. The interpretation of the
estimated model's results for non-performing loans
and the loan-to-deposit ratio comes next.
The study's conclusions were put into context by
discussing studies that support and refute the study’s
findings in a subsection titled "General Discussion."
4.1 Descriptive Statistics
Table 1. Descriptive Characteristics of Demand
Deposit Contracts and Profitability
Variables
Obs.
Mean
Std. Dev.
Minimum
Maximum
NPL
156
9.86
11.77
0.30
78.15
LDR
156
51.82
18.41
3.55
108.41
DSD
156
60.28
15.86
11.75
163.65
NIM
156
6.59
2.62
3.58
8.49
FSZ
156
22.17
0.84
18.87
23.46
FAG
156
37.21
16.47
5.00
76.00
Source: Authors’ computation, 2023.
4.1.1 Interpretation for Descriptive Statistics
Table 1 presents the descriptive statistics for demand
deposit contracts and profitability of listed deposit
money banks in Nigeria. On average, the non-
performing loan ratio (NPL) of the banks between
2010 and 2021 is estimated at 9.86%, which is above
CBN's benchmark of 5% for deposit money banks in
Nigeria, indicating the continued resilience of the
Nigerian banking system. The implication of this was
that a higher NPL would cause banks to limit their
credit supply to borrowers, which often causes credit
supply contraction. This indicates that the asset
quality of these banks deteriorated in the period
under review. The highest and lowest NPL ratios
during the period were 78.15% and 0.30%,
respectively, with a standard deviation of 11.77,
which shows that NPL varies across banks. The loan-
to-deposit ratio (LDR) has an average value of
51.82%. This is below the CBN's benchmark of 65%,
which means these banks were unable to comply with
regulatory provisions. The demand deposit ratio
(DSD) is seen to have an average value of 60.28%,
with minimum and maximum values of 11.75% and
163.65%, respectively. This indicates that, on
average, the banks studied exceeded regulatory
requirements; however, some of the banks were
observed to have very low ratios in the region of the
minimum threshold. The net interest margin (NIM)
of the banks during the period hovers between 3.58%
and 8.49%, with an average value of 6.59%, which
appears low as interest is a traditional source of
income for banks. The average values of firm size
(FSZ) and firm age (FAG) during the period were
found to be 22.17 and 37.21 years, respectively.
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4.2 Correlation Analysis
Table 2. Correlation Matrix for Demand Deposit
Contracts and Profitability
Variables
NPL
LDR
DSD
NIM
FSZ
FAG
NPL
1
LDR
0.089
1
DSD
0.329
0.092
1
NIM
0.167
0.068
0.053
1
FSZ
-0.268
0.146
-0.058
0.372
1
FAG
0.091
-0.269
0.141
-0.468
-0.181
1
Source: Authors’ computation, 2023
4.2.1 Interpretation for Descriptive Statistics
Table 2 presents the pairs of correlation between
demand deposit contracts and the profitability of
listed deposit money banks in Nigeria. The results
revealed that demand deposit ratio, net interest
margin, and firm age were positively associated with
non-performing loans, while firm size had a negative
association with the non-performing loans of the
selected listed deposit money banks in Nigeria. In
addition, there is evidence that demand deposit ratio,
net interest margin, and firm size were positively
related to the loan-to-deposit ratio of the selected
listed deposit money banks in Nigeria, while firm age
is negatively related to the loan-to-deposit ratio of the
listed deposit money banks in Nigeria. The
correlation coefficients of the selected variable are
weak because they are all within 0–0.35. This gives
the intuition that the variables are not correlated with
one another, suggesting that there is a possibility that
the variables are non-collinear or less correlated.
4.3 The Tobit Regression
The fixed effect Tobit regression results that
examined the relationship between demand deposit
and liquidity ratio indicators (NPL and LDR) are
presented in Table 3 (Appendix). In this study, the
lower limit for the non-performing loan ratio is 5%
(as prescribed by CBN), while that of the loan-to-
deposit ratio (LDR) is 65% (as prescribed by CBN)
and right-censored. However, to interpret the Tobit
models’ results, marginal effects were estimated and
used.
4.3.1 Interpretation
Table 3 (Appendix) reports the Tobit Panel
regression result for the demand deposit contracts
and profitability of deposit money banks in Nigeria.
To ascertain the appropriate model for the
interpretation of results between the random effect
and the fixed effect Tobit models, the Likelihood
ratio test was used. The significance of the likelihood
ratio test with a statistic of 5.216 and 7.678 at the 5
and 1 percent level, respectively, for the non-
performing loan and loan-to-deposit ratio equations,
suggests that the fixed effect Tobit model is
appropriate. Thus, the likelihood ratio test rejects the
null of the random effect model and accepts the
alternate of the fixed effect model.
Using the results of the marginal effects for each
of the equations, starting with the non-performing
loan equation, there is evidence that demand
deposits, net interest margin, and firm age have a
positive relationship with the non-performing loan,
while firm size is negatively related to the non-
performing loans of deposit money banks in Nigeria.
In addition, the results show the probability of
recording more than 5% of the non-performing loans
by the deposit money banks significantly varies with
demand deposit (DSD) and net interest margin
(NIM). The results showed that the marginal effect of
demand deposit and net interest margin has a
significant impact on non-performing loans of the
deposit money bank in Nigeria (DSD = 0.008, p-
value = 0.001, and NIM = 0.081, p-value = 0.016).
This suggests that demand deposits and net interest
margins are significant factors influencing changes in
non-performing loans at the deposit money banks in
Nigeria.
Conversely, there is evidence that the marginal
effect of firm size and firm age has no significant
impact on non-performing loans of deposit money
banks in Nigeria (FSZ = -0.072, p-value = 0.208, and
FAG = 0.031, p-value = 0.742). This implies that
firm size and firm age are not significant factors
influencing changes in the non-performing loans of
deposit money banks in Nigeria. In addition, the
Wald chi-square was used to test the overall model.
The result showed that at the 1 percent level of
significance, the Wald test statistic of 24.963 is
statistically significant; thus, the model rejects the
null that demand deposit contracts have no
significant impact on the non-performing loans of
deposit money banks in Nigeria and accepts the
alternate hypothesis that demand deposit contracts
have a significant impact on the non-performing
loans of deposit money banks in Nigeria.
The loan-to-deposit ratio equation revealed that
the demand deposit contracts and firm size have a
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DOI: 10.37394/23207.2024.21.75
Ogbebor Peter Ifeanyi, Awonuga Adesola Rukayat,
Akande Folorunsho Ilesanmi, Ademola Olufemi Christopher
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positive relationship with the non-performing loan,
while net interest margin and firm age are negatively
related to the loan-to-deposit ratio of deposit money
banks in Nigeria. The results show the probability of
recording more than 65% LDR by the banks
significantly varies with demand deposit (DSD) and
firm size (FSZ) as well. Explicitly, the results show
that the marginal effect of demand deposit (DSD) on
the loan-to-deposit ratio (LDR) is positive and
statistically significant at the 1% level (DSD = 0.117;
p-value = 0.000), suggesting that the probability of
recording LDR above 65% by the banks is increased
by 11.7% given an increase in DSD. Similarly, the
result reveals that the marginal effect of firm size
(FSZ) on the loan-to-deposit ratio (LDR) is
statistically significant at the 5% level (FSZ = 0.102;
P-value = 0.021), indicating that an increased FSZ
increases the probability of having an LRD ratio
above 65% by 1.02%. Furthermore, the results show
that the effects of net interest margin (NIM) and firm
age (FAG) are found to be statistically insignificant.
In addition, the Wald chi-square was used to test
the overall model. The result showed that at the 1
percent level of significance, the Wald test statistic of
216.215 is statistically significant; thus, the model
rejects the null that demand deposit contracts have no
significant impact on the non-performing loans of
deposit money banks in Nigeria and accepts the
alternate hypothesis that demand deposit contracts
have a significant impact on the loans-to-deposit ratio
of deposit money banks in Nigeria.
4.4 General Discussion
The study ascertained that the marginal effect of
demand deposit contracts on both the non-performing
loan ratio and the loan-to-deposit ratio was positive
and statistically significant, with coefficients of 0.008
and 0.117 and their corresponding probabilities of
0.001 and 0.000, respectively. Similarly, the marginal
effect of the net interest margin on the non-
performing loan ratio was positive and statistically
significant at the 5% level, with a coefficient of 0.081
and a probability value of 0.016. However, the net
interest margin was negative and not statistically
significant in the loan-to-deposit ratio equation. In
addition, the marginal effect of firm size showed a
negative but insignificant effect on non-performing
loans, but firm size was positive and statistically
significant on the loan-to-deposit ratio. The rationale
for the non-significance of bank size on non-
performing loans could be traced to other factors
such as liquidity ratio, capital adequacy ratio, and
inflation rate, which are deemed necessary to be
significant factors influencing the non-performing
loans, [34]. The study also attested that while firm
age was positive on non-performing loans, it was
equally positive on loan-to-deposit ratio; however,
both were not statistically significant. The rationale
why bank age is not a significant factor influencing
non-performing loans and loan-to-deposit in Nigerian
banks is alluded to by the unstable polity as well as
frequent changes in banking laws and regulations,
which led to the collapse of many banks and the
merger and acquisition of the top banks in the
country. This is clear evidence that demand deposits
have positive and significant effects on both non-
performing loans and loan-to-deposit ratios. The
rationale for the positive and significant effect of
demand deposits on non-performing loans and the
loan-to-deposit ratio in Nigeria is that as investors
increase their demand deposits, banks' non-
performing loans will increase because customers'
deposits provide banks with the capital to make such
loans. On its part, firm size only had positive and
significant effects on the loan-to-deposit ratio. This is
because as the bank's size grows, the possibility of
customer deposits also increases, thus increasing the
amount of loans granted to borrowers by the bank.
The study focused on demand deposits and the
probability of bank runs (recoding high NPL or LDR)
in Nigeria using panel data that covers a period from
2010 to 2021. The study analyzed the data using a
censored (right) multilevel Tobit regression
approach. The approach revealed that an increase in
demand deposit contracts increases the probability of
having very high non-performing (NPL) and loan-to-
deposit (LDR) ratios, accordingly, increasing the
probability of bank runs. This is in line with the
assertions of [28], [29], [35] and [36] that the growth
of customer deposits has a positive impact on bank
lending activity. However, [26], argued that a well-
capitalized firm would be in a better position to
withstand short-term liquidity shocks that could
precipitate a liquidity crisis. Following this assertion,
it can be stated that the growth of customer deposits
positively affects bank lending and causes an
increase in non-performing loans and the loan-to-
deposit ratio of the banks, which in turn increases the
probability of bank runs in Nigeria. Also, we found
that increased bank size (FSZ) increases the
probability of recording non-performing (NPL) and
loan-to-deposit (LDR) ratios above the prescribed
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DOI: 10.37394/23207.2024.21.75
Ogbebor Peter Ifeanyi, Awonuga Adesola Rukayat,
Akande Folorunsho Ilesanmi, Ademola Olufemi Christopher
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Volume 21, 2024
limit by CBN, therefore increasing the probability of
bank runs. Furthermore, net interest margin (NIM)
and firm age did not significantly predict the
probability of recording high or low non-performing
(NPL) and loan-to-deposit (LDR) ratios above the
prescribed limits in this study.
5 Conclusion and Recommendation
This study focused on demand deposit contracts and
the probability of selected deposit money banks in
Nigeria to ascertain the significance of demand
deposit indicators (customer deposit/total asset) on
bank runs in Nigeria whose financial standings are of
more concern to the regulatory bodies of the financial
system in the country. This was achieved by
collecting data from thirteen (13) banks’ annual
financial reports from the period 2010 to 2021, while
Tobit regression was used as the estimation
technique. Based on the results, the study concluded
that bank-specific factors have significant effects on
bank runs, and these variables—liquid assets/total
assets and total loans/total deposits—have significant
effects on increasing the probability of bank runs. In
particular, the study posited that bank deposits in
Nigeria are structured largely towards demand
deposits rather than the more stable time deposits;
this, therefore, indicates that there is a need for a
structural shift in the composition of the deposit base
of these banks, which requires far more time deposits
than unpredictable demand deposits.
Based on the findings and conclusion above, the
following recommendations suffice: First, to avoid
bank runs, there is a need for DMBs in Nigeria to
maintain adequate liquid assets, high demand deposit
ratios above the regulatory benchmarks, high total
assets, and reduce bad debt losses and other
associated costs of credit. Banks should evolve a
strategy to engage the services of factoring agents
before their doubtful loans get bad to make them
stable and withstand any stress that could emanate
from bank runs. Second, the top management of
DMBs in Nigeria should develop effective strategies
aimed at mobilizing more time deposits for their
operations, as this has the likelihood of providing a
safety net to guard against bank runs. Third, it may
be pertinent for regulatory authority to consider
urgently the need for ring-fencing of these banks
beyond the current practice of cash reserve and
liquidity ratios to make Nigerian banks healthy and
stable, as demand deposit contracts are unpredictable
and, hence, unreliable in the event of bank runs.
6 Limitation of the Study
This study is limited to deposit money banks in
Nigeria; hence the result cannot be an interpretation
of demand deposit contracts and probability of bank
runs for other financial institutions such as
microfinance banks and finance houses whose
functions have also been extended to the collection of
low value deposits in addition to the provision of
consumer lending services.
7 Suggestions for Further Studies
Future studies should endeavor to look into other
financial institutions such as microfinance banks and
finance houses. In addition, the time frame for the
study could be extended to cover at least between
2008 and 2022 to capture the effects of the financial
crisis of 2008 and the COVID-19 pandemic that
ravaged the global economy from 2019 to 2022.
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Ogbebor Peter Ifeanyi, Awonuga Adesola Rukayat,
Akande Folorunsho Ilesanmi, Ademola Olufemi Christopher
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Akande Folorunsho Ilesanmi, Ademola Olufemi Christopher
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Contribution of Individual Authors to the
Creation of a Scientific Article (Ghostwriting
Policy)
The authors equally contributed to the present
research, at all stages from the formulation of the
problem to the final findings and solution.
Sources of Funding for Research Presented in a
Scientific Article or Scientific Article Itself
No funding was received for conducting this study.
Conflict of Interest
The authors have no conflicts of interest to declare.
Creative Commons Attribution License 4.0
(Attribution 4.0 International, CC BY 4.0)
This article is published under the terms of the
Creative Commons Attribution License 4.0
https://creativecommons.org/licenses/by/4.0/deed.en_
US
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APPENDIX
Table 3. Tobit Regression Result
Dependent Variable = NPL
Dependent Variable = LDR
Independent
Variables
Coeff.
Marginal Effect
Coeff.
Marginal Effect
(Std. Err.) [P>|z|]
dy/dx
(Std. Err.) [P>|z|
dy/dx
(Std. Err.) [P>|z|]
(Std. Err.) [P>|z|
DSD
0.216***
0.008***
0.303**
0.117***
(0.035) [0.000]
(0.003) [0.001]
(0.127) [0.026]
(0.018) [0.000]
NIM
2.421**
0.081**
0.128
-0.084
(0.988) [0.024]
(0.027) [0.016]
(1.895) [0.988]
(0.207) [0.915]
FSZ
-1.808
-0.072
4.741**
0.102**
(1.291) [0.126]
(0.052) [0.208]
(2.291) [0.022]
(0.049) [0.021]
FAG
0.083
0.031
-0.201
-0.186
(0.091) [0.407]
(0.223) [0.742]
(0.385) [0.483]
(0.014) [0.415]
Constant
18.265
-44.79
(27.540) [0.489]
(50.541) [0.789]
Observation
156
156
Wald chi2(4)
24.963***
16.215**
P-val > chi2
0.000
0.014
Log likelihood
-493.487
-367.093
LR vs tobit
5.216**
7.678***
P-val
0.016
0.002
Source: Authors’ computation, 2022. Note: ***, ** and * represents significance at 1%, 5% and 10% respectively
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