A study on effect of bank resources and consumption on liquidity

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*Corresponding author.

doi: 10.5267/j.msl.2014.6.016

Management Science Letters 4 (2014) 1477–1486

Contents lists available at GrowingScience

Management Science Letters

homepage: www.GrowingScience.com/msl

A study on effect of bank resources and consumption on liquidity

Hussein Panahian, Hassan Ghodrati and Mohammad Ali Parvishi*

Department of Management and Accounting, Kashan Branch, Islamic Azad University, Kashan, Iran

C H R O N I C L E A B S T R A C T

Article history: Received January 4, 2014 Accepted 1 June 2014 Available online June 9 2014

Liquidity management in banks is a conflict between risk and return. On the one hand, the lack of liquidity, in addition to imposing heavy costs of providing resources (including borrowings from the central bank at elevated rates), may also lead banks to face with bankruptcy. On the other hand, the maintenance of excessive liquidity than needed will destroy investment opportunities and potential profitability. Therefore, for proper liquidity management, it is necessary to understand the factors affecting this sector to be able to exert control on each of the elements, and to prevent the incidence of problems or even crisis thereby optimize the bank profitability as far as possible. This study aimed to analyze the resources, expenses, and liquidity operating as the main activity parameters in Bank Shahr. During the study timeframe (2010 until the end of 2012), every 15 days was selected as the sample community, which were selected due to a 15-day trend analysis using census method and not by random sampling. The related data concerning each of the items, i.e. resources, expenses, and liquidity were collected and analyzed by linear regression based on time or periods of time. The above items were compared through analysis of the relative contribution to the total ratio and correlation analysis. The results showed that the growing trends of resources and expenses almost coincide and followed a specific trend and, in general, the growing trend of the resources was rising with a higher slope compared with those of expenses and liquidity. In addition, the growing trend of liquidity was almost identical throughout the entire period of study and no unusual trend was observed.

Keywords:

Liquidity

Liquidity management Resources and expenses Trend analysis Bank Shahr

1. Introduction

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sector to be able to exert control on each of the elements and to prevent the incidence of problems or even crisis thereby optimize the bank profitability as far as possible. Banks depend on a variety of monetary and financial markets through numerous depositors and borrowers, and they are subject to different risks. Hence, banks have always tried to predict and to maintain their optimum amount of cash needed by using various tools and methods. This section will have an overview of the structure

of assets and liabilities, liquidity models, and the predominating risks in the banks (Fecht et al., 2011;

Calvo, 2012). This study aimed to analyze the resources, expenses, and liquidity operating as the

main parameters in one of Iranian banks named Bank Shahr. During the study period from 2010 to the end of 2012, every 15 days was selected as the sample community, which were selected due to a 15-day trend analysis using census method and not by random sampling. The related data concerning each of the items, i.e. resources, expenses, and liquidity were collected and analyzed by linear regression based on time or periods of time. The above items were compared through analysis of the relative contribution to the total ratio and correlation analysis.

2. Literature review

Lovin (2013) investigated the effect of a liquidity shock induced by depositors' behavior on bank portfolio management during financial crises in a system without deposit insurance. The study detected that banks reacted to the liquidity shock sensitively through an increase in their cash holdings not by liquidating bank loans but by selling securities in the financial market. In addition, in their study, banks exposed to local financial contagion adjusted the liquidity of their portfolio mainly by actively selling and buying their securities in the financial market. Distinguin et al. (2013) studied the relationship between bank regulatory capital and bank liquidity measured from on-balance sheet positions for European and US publicly traded commercial banks. They reported that banks decrease their regulatory capital ratios when they encountered higher illiquidity as defined in the Basel III accords or when they created more liquidity. Imai and Takarabe (2011) investigated the causal impacts of liquidity shocks on credit supply by the endogenous relationship between loan demand and liquidity position of banks. They reported that during the period of transition from a blanket guarantee to a partial guarantee, weak banks influenced from a large outflow of partially insured time deposits. Hauck and Vollmer (2013) analyzed a government's incentives to provide financial assistance to a public bank hit by a liquidity shock. They reported that discretionary decisions about emergency liquidity assistance could result in either excessively small or excessively large liquidity injections in a wide variety of circumstances. In addition, adding a lender of last resort does not generally ensure a socially optimal policy. Balasubramanyan and VanHoose (2013) performed a a dynamic banking model survey and their results showed that imposing an LCR constraint generally had theoretically ambiguous impacts on the stability of banks’ optimal dynamic balance-sheet paths.

3. Research hypotheses

The proposed study of this paper investigates the relationship between the resource components with the expenses and liquidity in banking industry and the study is implemented on the information of one of Iranian banks named “Bank Shahr”. The study also investigates the trend on bank’s resources, expenses, liquidity and the relationships between these items. The survey collects 15-day period information over the period 2010-2012. Since there are 24-point data, we end up having 72 sample study. The study uses descriptive, correlation analysis and simple regression analysis to examine the data. Fig. 1 shows different expenses/resources. For trend analysis, linear regression model was used as Y = f (t), where Y is each of resource item, expenses, liquidity, total resources, total expenses, and t is the 15-day periods every year.

4. Research findings

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Expenses (independent variables) Resources (independent variables) Increase or decrease in: Increase or decrease in:

Fig. 1. Analytical model of research

Table 1

Descriptive statistics of the data (non-coefficient numbers are in Million Rials)

Variables Mean Mein Variance Standard

deviation maxmin

Coefficient of skewedness

Elongation factor

Fund 9799527 11315583 2.515 501465 2575669 17053707 -0.121 -1.606

loan bona deposits 26751393004360 1.455 1206126 1556858 7570221 3.5001.777

Prolonged deposits 3101562 2104564 4.406 2098978 900638 7877057 0.742 -0.905

Other deposits 31119181324 1.602 400240 8398 2292470 4.442 21.445

From banks deposits 2169116 1908669 2.975 1724717 1472788 5463783 0.571 -0.945

Debt to the Central Bank. 126624405856 3.077 554221 73412 2000267 1.9611.708

Get bank loans 1104316 1062237 1.561 395113 394521 2021070 0.403 0.625

Pre-pay by customers 10078551025150 3.152 177538 682284 1568838 0.867 1.064

Facilities from foreign exchange

reserves 6096005 4893592 5.282 2298330 3196941 9664811 0.220 -1.779

Incomes 10510170 2673713 1.759 1326 440510 55517879 - 1.279 0.920

Receivables from central bank and

government -694446 -21081 5.284 -2298784 0 9263819 3.357 10.041

Installment sale facilities -8358567-8513871 1.489 -3858970 -207207 1876572 0.424 0.446

Civil Partnership Facility -2801509 -2188564 2.372 -1540073 -802468 5278781 3.357 -1.474

Other Facilities -10329260-10581460 3.525 -5937146 -4578068 27017421 1.107 0.588

Their related receivables past due -2180213 -2026810 5.467 -739406 -838801 3719754 0.050 0.731

Debtors LC & LG -1912544-2048293 4.487 -669846 -977274 328226 0.094 -1.193

Receivables past LC & LG -1318448 -1424780 3.451 -587492 -145553 2320875 -0.602 -0.548

Other assets -4254676-5332467 1.132 -3364369 -1773405 14442702 0.644 0.629

Costs -1135857 -2836364 2.190 -14798992 300098 65212201 1.534 2.181

4.1. Description of the findings

As mentioned earlier, each of the bank’s resources and expenses were classified into nine categories. At the beginning of the first and the fifteenth of each month, cash balances were collected using bank finance management reporting software and they were classified via Excel spreadsheet. According to the descriptive statistical data, the following results were obtained using SPSS software.

- The mean and median values are close together for most variables. This feature was not optimal among the variables of debt to the central bank, receivables from the central bank and the government

and other resources, loans from foreign exchange reserves, civic facilities, and other assets and

expenses. This was due to the presence of large changes in the remains, and also to the unchanged

remains during the past few successive months.

- With the exception of cash and maturities for letters of credit and guarantees having a skewedness to the left, the remaining variables skew to the right because their coefficients of skewedness is positive.

1- Types of deposits including loan bona deposits, prolonged and other deposits 2- Governmental deposits including instant and prolonged deposits from banks 3- Facilities received from central bank or other banks

4- Other resources (other liabilities) such as pre-pays by governmental and non-governmental customers and facilities from foreign exchange reserves

5- Capital resources, including shareholders' equity and incomes (including interest and commitment of funds received, commissions and other incomes)

1- Receivables from central bank and government

2- Public and private facilities and their related receivables past due

3- Documentary credits and guarantees for debtors and their related receivables past due

4- Other expenses (other assets) including investments and partnerships, immovable property, intangible and other assets

5- Both operational and non-operational costs

Dependent variable

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1 -d 4 D a r r t c 4 L t A w n g e r e T E 4 T d u 1480

- The stretc distribution 4.2 Analyzin During the analysis, th respectively review inclu the trend an compared w

4.2.1 Trend

Loan deposi trends of the

As we can o winter 2011 noticeable c general tren estimated pa regression h equation ind Table 2 Estimated tr Row 1 2 3 4.2.2 Trend These depo depositors. upward tren

ching of mo (those who

ng the resou

15 -day tim he horizon y, the timefr ude deposit nalysis of ea with each oth

analyses of

its without ese deposits

observe fro 1. With the changes in t nd of chan

arameters, t has a posit dicates over

rend line for

analysis of

osits are as Fig. 3 show nd over time

Fl l 20 12 Wi nter 20 12 Wi nter 20 12

ore than a h ose stretch c

urces items

meframe for ntal (indepe

rame and an s, loans rec ach of these

her.

f the loan de

interest and s indicating

om the resul e change of the bank’s nges in loan

the regressi tive slope r 48.5 % of

r loan depo

The

f prolonged

sociated w ws the tren e: Su mme r 20 12 Su mme r 20 12 Fa ll 20 12 F a ll 20 12

half of the v coefficient is

data collec endent var ny of the res ceived from

e items, and

eposits:

d awards are that these d

Fig. 2. T

lts of Fig. 2 f the Mayo loan deposi n deposits ion equation for each ti the changes

sits Paramete The width of the The slope of th e coefficient of de

deposits

ith interest nds of these

Wi n te r 2 0 11 Wi nter 20 11 Spri ng 20 12 Spri ng 20 12 variables is s negative).

tion, the da riable) and sources item m other bank

d the overall

e provided deposits had

Trend of loan

2, there was or and of h

its occurred was estima n is as follo imeframe s s.

er e source he line etermination

t and award e deposits S mme r 20 11 Su mme r 20 11 Fa ll 20 11 Fa ll 20 11 above and

ata were ana d vertical ms. The reso ks and other l trend in to

to encourag d relatively

n deposit

s a slow gro his attitude

d but the pr ated using ows: Y = f showing an

ds and they indicating t

Wi nter 20 10 Spri ng 20 11 Spri ng 20 11 S u mme r 20 11

d a half is s

alyzed using (dependent ources empl r sources. T otal resourc

ge the depos upward tren

owth during to Bank Sh roblem was

regression (t) = -1000 n ascending

y are prov that these d

Su mme r 20 10 Fa ll 20 10 Fa ll 20 10 Wi nter 20 10 shorter than

g trend anal t variable) loyed in the The first par es and final

sitors. Fig. nd over tim

g the early hahr in Oc s gradually (Table 2). 0000 + 115 g trend. Th

quantity -10000000 11585.138

0.485

ided to enc deposits ha Spri ng 20 10 Spri ng 20 10 Su mme r 20 10

n the norma

lysis. In this axes are e bank under

rt deals with lly, they are

2 shows the me;

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T w d p -e T E 4 D a t r f a 4 T t s c g e f a The figure winter 2011 deposits. Th presented in -10000000 + estimated eq Table 3 Estimated tr Row 1 2 3 4.2.3 Analys During the analysis, th timeframe a review inclu first part de and finally,

4.2.4 Trend

This include trends of th shows slow changes dur growth in th estimated u follows: Y ascending tr

shows slow 1, an inflat he general n Table 3. U + 11809t, w quation indi

rend line of

sis of the exp

15-day time he horizont

and any of ude total cr eals with the

they are co

analysis of

es the facil hese deposit growth dur ring the rem hese deposi

sing regres = f(t) = -5 rend. The es

Wi nt er 20 12 Wi nt er 20 12 F

w growth du tion and ris

trend of ch Using the est which has a icates over

f prolonged

The

xpenses item

eframe for d tal (indepen the resourc redits, the m

e trend anal mpared wit

f facilities fo

lities given ts indicating ring the earl maining per its. The gen sion (Table 000000 + 5 stimated equ Summer 20 12 Summer 20 12 Fa ll 20 12 Fa ll 20 12

Fig. 3. Tren

uring the ea sing interes hanges in t timated par positive slo 19.6 % of th

deposits Paramete The width of the The slope of th e coefficient of de

ms

data collect ndent varia ces items, re maturities an lysis of each th each othe

or Buy Now

to governm g that these

ly period un riod. Since neral trend o e 4). Using

5133t, whic uation indic Wi nt er 20 11 Wi nt er 20 11 Sp ri n g 20 12 Sp ri n g 20 12

d of prolong

arly period st rates of

the prolong rameters, the ope for each he changes.

tion, the dat able) and v

espectively nd deferred h of these i er.

w Pay Later

mental and e deposits h

ntil October October 20 of changes

the estimat ch has a po cates over 3

Summer 20 11 Summer 20 11 Fa ll 20 11 Fa ll 20 11 Wi nt er 20 11 ged deposit until sprin investment ged deposits e regression h timeframe .

ta were ana vertical (de . The resou d receivable

items, and t

non-govern had relativel

r 2011 and 012, the ba in the facil ted paramet ositive slope 33.9 % of th

Wi t 20 10 Wi nt er 20 10 Sp ri n g 20 11 Sp ri n g 20 11 Summer 20 11 ts

g 2011. Th s led to a s was estim n equation i e showing a

alyzed using ependent v urces emplo s, and final the overall t

nmental cli ly upward t they were a ank facilitie

lities for Bu ters, the reg e for each he changes. Summer 20 10 Fa ll 20 10 Fa ll 20 10 Wi n ter 20 10

he reason is rapid grow mated using is as follow an ascending

quantity -10000000 11809.073

0.196

g trend anal variable) ax oyed in the lly other exp

trend in tot

ents. Fig. 4 trend over t associated w s policy led uy Now Pay gression eq timeframe Sp ri n g 20 10 Sp ri n g 20 10 Summer 20 10

s because in wth in these g regression s: Y = f(t) = g trend. The

lysis. In this xes are the bank under penses. The al resources

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1 T E 4 T d F s p 1482 Table 4 Estimated tr Row 1 2 3 4.2.5 Trend The heading during the s

Fig. 5 show specific cha participation

rend line for

analysis of

g of these f tudied time

ws slow grow anges during

n was estim

Wi nt er 20 12 Wi nt er 20 12 Fa ll 20 12 Wi nt er 20 12 Wi nt er 20 12

Fig. 4. T

r prolonged

Th

f facilities fo

facilities is r eframe indic

Fig. 5.

wth during g the remai mated using r

Summe r 20 12 Summe r 20 12 Fa ll 20 12 Fa ll 20 12 Su mme r 20 12 Su mme r 20 12 Fa ll 20 12

Trend of fac

ddeposits

Paramete The width of th

The slope of t he coefficient of d

or civic part

remarked a cating that th

Trend of fa

the early p ning period regression ( Wi nt er 20 11 Wi nt er 20 11 Spri n g 201 2 Spri n g 201 2 Wi nt er 20 11 Wi nt er 20 11 Sp ri n g 20 12 Sp ri n g 20 12

cilities for B

er he source the line determination ticipation and non-rem hese deposi acilities for period until d. The gene (Table 5). Summe r 20 11 Summe r 20 11 Fa ll 20 11 Fa ll 20 11 Wi nt er 20 11 S 20 11 Su mme r 20 11 Fa ll 20 11 Fa ll 20 11

Buy Now Pa

marked. Fig. its had relat

civic partic

October 20 eral trend of

Wi 20 10 Wi nt er 20 10 Spri n g 201 1 Spri n g 201 1 Summe r 20 11 Wi nt er 20 10 Sp ri n g 20 11 Sp ri n g 20 11 S u mme r 20 11 ay Later

. 5 shows th tively upwar

ipation

012 and they f changes in

Summe r 20 10 Fa ll 20 10 Fa ll 20 10 Wi nt er 20 10 Su mme r 20 10 Fa ll 20 10 Fa ll 20 10 Wi nt er 20 10 quantity -5000000 5133.071 0.339

he trend of rd trend ove

y were asso n the faciliti

Spri n g 201 0 Spri n g 201 0 Summe r 20 10 Sp ri n g 20 10 Sp ri n g 20 10 Su mme r 20 10 Su mme r 20 10

f this outline er time

ociated with ies for civic

e

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T E U w i 4 T h t t ( T E U w i 4 T c t s c Table 5 Estimated tr Row 1 2 3

Using the e which has a indicates ov

4.2.6 Analyz

This headin heading dur trend over t trend of cha (Table 6). Table 6 Estimated tr Row 1 2 3

Using the e which has a indicates ov

4.2.7 Analys

This headin current acco the trend o showed slow changes dur

rend line fac

stimated pa a positive sl ver 14.9 % o

zing the tren

g includes d ring the stu time and we anges in the

F

rend line for

estimated pa a negative s ver 1.1 % of

sis of the liq

ng includes ounts in oth

f this head w growth d ring the rem

Winter 20 12 Winter 20 12

cilities for c

Th

arameters, th lope for eac of the chang

nd for debto

debtors of le udied timef

ere associat debtors of

Fig. 6. Tren

r prolonged

Th

arameters, t lope for eac f the change

quidity trend

the accoun her banks, fo ding indicat during the maining peri Summe r 20 12 Summe r 20 12 Fa ll 20 12 Fa ll 20 12 civic partici Paramete The width of th

he regressio ch timefram ges.

ors of credit

etters of cre frame indica

ted with spe letters of cr

nd for debto

ddeposits

Paramete The width of th

the regressi ch timefram es.

d:

nts of the fu oreign curre ting that it early perio iod. After sp

Winter 20 11 Winter 20 11 Sp ri n g 20 12 Sp ri n g 20 12 pation er he source the line determination on equation me showing

ts letters an

edits letters ating that t ecific chang redits letters

ors of credits

er he source the line determination ion equation me showing und, deposi ency deposi had a rela od until spr pring 2011, Summe r 20 11 Summe r 20 11 Fa ll 20 11 Fa ll 20 11 Winter 20 11

n is as follo g an ascend

nd guarante

and guaran these depos ges during t s and guaran

s letters and

n is as foll an descend

its in the ce its, bonds an atively upw ring 2011 a multiple bo Wi 20 10 Winter 20 10 Sp ri n g 20 11 Sp ri n g 20 11 Summe r 20 11

ows: Y = f(t ing trend. T

es

ntees. Fig. 6 sits had a r the remaini ntees is esti

d guarantees

ows: Y = f ding trend. T

entral bank, nd foreign e ward trend o and were as onds issued Summe r 20 10 Fa ll 20 10 Fa ll 20 10 Wi nt er 20 10 quantity -7000000 8575.656 0.149

t) = -70000 The estimat

shows the t relatively sl ng period. imated using s quantity 6675039 -509.25 -0.011

f(t) = 66570 The estimat

, inventory exchange. F over time.

ssociated w d, increased Sp ri n g 20 10 Sp ri n g 20 10 Summe r 20 10

000 + 8576t ted equation

trend of this low upward The genera g regression

039 − 509t

ted equation

turnover o Fig. 7 shows

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1

a l

T E

U w i

4

F r t g

4

A t

T T

T

1 p 1484

and certifica liquidity wa

Table 7 Estimated tr

Row 1 2 3

Using the es which has a indicates ov

4.2.8 Compa

Fig. 8 comp resources an trend of reso growth was

4.3. Analysi

Assessment the bank rel

Table 8 The Summa

Varia Liqui Resou Consum

This table d

1) There is positive.

ates of depo as estimated

rend line for

stimated par a positive sl ver 46.3 % o

aring the so

pares the it nd expense ources is hig

almost iden

is of the rela

t of the rela ative to eac

ary of Corre able

dity urces mptions

demonstrates

a direct rel

osit led to a d using regre

r liquidity tr

The

rameters, th lope for eac of the chang

ources and u

tems of reso s almost co gher with a ntical throug

ationship be

ationship be ch other was

elation Anal L

s that:

lationship b

a growth in ession (Tab

Fig. 7

rend Paramete The width of the The slope of th e coefficient of de

he regressio ch timefram ges.

uses of cash

ources, exp oincide and

greater slop ghout the en

etween item

etween chan s conducted

lysis Liquidity

1 0.815 0.687

between the

the bank’s ble 7).

7. Liquidity

on equation me showing

h

penses, and follow a p pe than thos ntire study t

ms

nges in the d using corre

e resources

liquidity. T

trend

is as follow g an ascend

liquidity sh particular tre se of the liq timeframe a

items of re elation anal

Resources 0.815

1 0.794

and liquidit

The general

ws: Y = f(t) ing trend. T

howing tha end, and th quidity and and no unus

sources, exp lysis summa

s

ty as the co

trend of cha

quantity -40000000 41541.347

0.463

= -4000000 The estimat

at the growi at the gene expenses. T sual trend ob

penses and arized in Ta

Consum 0.6 0.7 1

orrelation co

anges in the

00 + 41541t ted equation

ing trend o eral growing The liquidity

bserved.

liquidity o able 8.

mptions 687 794 1

oefficient is

e

t, n

f g y

f

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2 p 3 p 4 c 5 6 I e h a I c a w i e p g t a h i

4) The high close to 1.

5) The liqui

6. Conclusi

In this inve employed. I hypothesis analysis:

In this stud classified de ascending g weaker and into three g expenditure past due and growing tre the entire tim almost coin higher with identical thr Wi nter 20 12 Wi nter 20 12 Wi nter 20 12

a direct rel

hest correlat

dity and exp

Fi

ion

estigation, In addition,

testing was

dy, the com eposits, loa growth than slower grow general cate

s. The total d deferred r end of liquid

meframe an ncide and fo

a greater sl roughout th Su mme r 20 12 Fa ll 20 12 Fa ll 20 12 Fa ll 20 12 lationship b

lationship b

tion is betw

penses disp

ig. 8. The T

the data w due to the s avoided. mponents of ans received other categ wing trends egories inclu

l facilities h receivables

dity in the nd not unusu follow a par

lope than th he entire stu

Spri ng 20 12 Spri ng 20 12 Su mme r 20 12 Su mme r 20 12 between the between the

ween the res

play the low

Trend of Con

were collect descriptive This study

f resources d from bank gories. Item

s than other uding total have more a show weak studied tim ual trend is rticular tren hose of the udy timefra Wi nter 20 11 Wi nter 20 11 Wi nter 20 11 Spri ng 20 12 Liquidity resources a e expenses sources and west correlat nsumptions

ted by cens e method fo

was to an

were class ks, and othe

s placed in categories. facilities, p ascending g ker and slow meframe sho

observed. T nd, and tha

liquidity an ame and no

Su mme r 20 11 Fa ll 20 11 Fa ll 20 11 Fa ll 20 11 Consump and expens and liquidit liquidity a

ion with a c

s, Resources

sus method r the trend nswer the fo

sified into t er resources

the facilitie . The compo past due an growth than wer growing ow a slow g The growin at the gener nd expenses unusual tr Spri ng 20 11 Spri ng 20 11 Su mme r 20 11 Su mme r 20 11 ptions

es as the co

ty as the co

s the coeffi

coefficient o

s & Liquidit

d and rand analysis ba following qu

the three g

s. The othe

es received onents of ex nd deferred n other cate

g trends tha growth slop ng trend of r ral growing s. The liquid rend observ Wi nter 20 10 Wi nter 20 10 Wi nter 20 10 Spri ng 20 11 Resources orrelation c orrelation co icient (0.81 of 0.678. ty om samplin ased on time

uestions thr eneral cate er resources from other xpenses wer receivables gories. Item an other cate pe nearly id

resources an g trend of r dity growth

ed. There w

Su mme r 20 10 Fa ll 20 10 Fa ll 20 10 Fa ll 20 10 oefficient is oefficient is

5), which is

ng was no eframes, the

rough trend

gories were s have more banks show re classified s, and other ms placed in egories. The dentical over nd expenses resources is was almos was a direc

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1486

relationship between the resources and liquidity as the correlation coefficient was positive. Similarly, there was a direct relationship between the resources and expenses as the correlation coefficient was positive. In addition, there was a direct relationship between the expenses and liquidity as the correlation coefficient was positive. In our survey, the highest correlation was between the resources and liquidity as the coefficient (0.815) was closer to 1 and the liquidity and expenses represented the lowest correlation with a coefficient of 0.678.

Acknowledgement

The authors would like to thank the anonymous referees for constructive comments on earlier version of this paper.

References

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Distinguin, I., Roulet, C., & Tarazi, A. (2013). Bank regulatory capital and liquidity: Evidence from

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conditions and bank characteristics. Journal of Financial Economics,102(2), 344-362.

Imai, M., & Takarabe, S. (2011). Transmission of liquidity shock to bank credit: Evidence from the

deposit insurance reform in Japan. Journal of the Japanese and International Economies, 25(2),

143-156.

Hauck, A., & Vollmer, U. (2013). Emergency liquidity provision to public banks: Rules versus

discretion. European Journal of Political Economy, 32, 193-204.

Lovin, H. (2013). Determinants of the liquidity in Romanian interbank deposits market. Procedia