Peykani, Pejman; Sa golzaei, Mos a a; Tănăsescu, C is ina; Shojaie, Seyed Ehsan;
Kamyab a , Hamid eza
A icle
In es iga ing he ela ionship be ween liquidi y isk, c edi isk, and
sol ency isk in banks lis ed on he I anian capi al ma ke : A Panel
Vec o E o Co ec ion Model
Economies
P o ided in Coope a ion wi h:
MDPI – Mul idisciplina y Digi al Publishing Ins i u e, Basel
Sugges ed Ci a ion: Peykani, Pejman; Sa golzaei, Mos a a; Tănăsescu, C is ina; Shojaie, Seyed Ehsan;
Kamyab a , Hamid eza (2025) : In es iga ing he ela ionship be ween liquidi y isk, c edi isk, and
sol ency isk in banks lis ed on he I anian capi al ma ke : A Panel Vec o E o Co ec ion Model,
Economies, ISSN 2227-7099, MDPI, Basel, Vol. 13, Iss. 5, pp. 1-24,
h ps://doi.o g/10.3390/economies13050139
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Ci a ion: Peykani, P., Sa golzaei, M.,
Tanasescu, C., Shojaie, S. E., &
Kamyab a , H. (2025). In es iga ing
he Rela ionship Be ween Liquidi y
Risk, C edi Risk, and Sol ency Risk in
Banks Lis ed on he I anian Capi al
Ma ke : A Panel Vec o E o
Co ec ion Model. Economies,13(5),
139. h ps://doi.o g/10.3390/
economies13050139
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A icle
In es iga ing he Rela ionship Be ween Liquidi y Risk, C edi
Risk, and Sol ency Risk in Banks Lis ed on he I anian Capi al
Ma ke : A Panel Vec o E o Co ec ion Model
Pejman Peykani 1,* , Mos a a Sa golzaei 2, C is ina Tanasescu 3, Seyed Ehsan Shojaie 4and
Hamid eza Kamyab a 2
1Depa men o Indus ial Enginee ing, Facul y o Enginee ing, Kha am Uni e si y, Teh an 1991633357, I an
2
Depa men o Finance and Banking, Facul y o Managemen and Accoun ing, Allameh Taba aba’i Uni e si y,
Teh an 1489684511, I an; [email p o ec ed] (M.S.); [email p o ec ed] (H.K.)
3Facul y o Economic Sciences, Lucian Blaga Uni e si y o Sibiu, 550324 Sibiu, Romania;
[email p o ec ed]
4Depa men o Indus ial Enginee ing, Science and Resea ch B anch, Islamic Azad Uni e si y,
Teh an 1477893855, I an; [email p o ec ed]
*Co espondence: [email p o ec ed]
Abs ac : In he a e ma h o global inancial c ises and amid inc easing complexi y in
banking ope a ions, unde s anding and managing a ious ypes o isk—especially liq-
uidi y, c edi , and sol ency isks—has become a global conce n o inancial s abili y. This
s udy add esses a c i ical gap in he li e a u e by examining he dynamic in e ela ionships
among hese h ee ypes o isk in he con ex o eme ging ma ke s. Using da a om
21 banks lis ed on he I anian capi al ma ke om 2011 o 2023, we employ a Panel Vec o
E o Co ec ion Model (VECM) alongside panel impulse esponse analysis o assess bo h
sho - and long- e m dynamics. Ou esul s e eal ha an inc ease in liquidi y posi i ely
impac s bank sol ency, while c edi isk nega i ely a ec s sol ency bu does no signi i-
can ly in luence liquidi y isk. These indings con ibu e o he heo e ical unde s anding
o sys emic isk in e ac ions in banking and p o ide p ac ical insigh s o policymak-
e s and inancial ins i u ions seeking o enhance isk managemen s a egies in ola ile
ma ke en i onmen s.
Keywo ds: liquidi y isk; c edi isk; sol ency isk; Panel Vec o E o Co ec ion Model
(VECM); Impulse Response Func ions; a iance decomposi ion
1. In oduc ion
In ecen decades, global inancial sys ems ha e expe ienced epea ed dis up ions—mos
no ably he 2008 inancial c isis and he mo e ecen challenges igge ed by he COVID-19
pandemic. These e en s ha e highligh ed he cen al ole o inancial ins i u ions, especially
banks, in bo h exace ba ing and mi iga ing sys emic isk. Amid such u bulence, ensu ing he
s abili y and esilience o he banking sec o has become a global p io i y. This has inc eased
a en ion o he complex in e play o majo inancial isks, especially liquidi y isk, c edi isk,
and sol ency isk.
Despi e he global ele ance o hese isks, empi ical s udies in eme ging
ma ke s—pa icula ly I an— emain limi ed. I an’s banking sec o , unde he p essu e o
p olonged economic sanc ions, cu ency luc ua ions, and egula o y cons ain s, p esen s
a unique case o in es iga ing how hese isks in e ac . Acco ding o ecen inancial
epo s, se e al I anian banks ha e expe ienced declining capi al adequacy a ios and
Economies 2025,13, 139 h ps://doi.o g/10.3390/economies13050139
Economies 2025,13, 139 2 o 24
ising non-pe o ming loans, aising conce n abou po en ial sys emic ulne abili ies. How-
e e , he na u e and di ec ion o in e dependencies be ween key isks ha e no ye been
clea ly iden i ied.
The banking indus y has always been associa ed wi h a ious complica ions and
isks and has gone h ough mul iple economic c ises. In his complex indus y, he s abili y,
g ow h, and lexibili y o he banks ha e consis en ly been key conce ns o bank manage s
and economic policymake s, especially conside ing he u bulen economic condi ions.
Risk analysis and i s managemen is a p ocess ha helps o ganiza ions, especially inancial
ins i u ions, o p edic , unde s and, and manage bo h sys emic and in e nal isk (Zhang
e al.,2023;Peykani e al.,2023a;Va ma e al.,2022;Bhimjee e al.,2016). Risk managemen
in o ganiza ions enables manage s o imp o e o ganiza ional pe o mance by minimizing
losses and maximizing p o i s. Banks a e among he mos impo an ins i u ions ope a ing
in global inancial and mone a y ma ke s, and hey a e exposed o a wide ange o isks.
Due o he di ec ela ionship be ween banks and all segmen s o socie y—pa icula ly
ollowing he 2008 global inancial c isis and mo e ecen e en s such as he COVID-19
pandemic— he necessi y o isk managemen in banks and inancial ins i u ions has become
a c i ical conce n wo ldwide and is now being pu sued wi h inc eased u gency (Ding &
Wei,2023;Adam e al.,2023;Telg e al.,2023;Galle a e al.,2023).
Due o he la ge social, inancial, and economic dimensions o he inapp op ia e pe o -
mance o some banks, excessi e exposu e o banks o inancial isks can cause bank up cy
and ha e signi ican impac s on he li es o many people (Peykani e al.,2023b;Be ge &
Demi güç-Kun ,2021;Lin & Han,2021;An on & Nucu,2020). By unde s anding he isks
acing banks, go e nmen s can se be e egula ions o encou age p uden managemen
and a ional decision-making (Ma ee e al.,2023;Hoque e al.,2015;Lae en & Le ine,
2009;González,2005). I is also impo an o s a e ha a bank’s abili y o manage isk
a ec s in es o s’ decisions. E en i banks can gene a e a lo o income, hei lack o isk
managemen can se e ely educe p o i s due o loan losses and nega i ely a ec he bank’s
o e all pe o mance in e ms o p o i abili y. I should be no ed ha expe ienced in es o s
in es mo e in a bank ha has he abili y o inance and p o ide p o i and is pe cei ed
as being a a low isk o inancial loss (B ei ens ein e al.,2021;Pa k & Jang,2021;J. Wang
e al.,2021).
The mos impo an isks in banks a e c edi isk and liquidi y isk, which i neglec ed
o imp ope ly managed will lead o i epa able social, poli ical and economic consequences
(Von Tamakloe e al.,2023;A andi e al.,2023;Rez ani e al.,2023;Cahyanda i e al.,2023).
Unde s anding he a ious ypes o isks wi hin banking sys ems helps ins i u ions de elop
e ec i e isk managemen s a egies. Since banks a e exposed o a ious isks, hey ha e
app op ia e isk managemen in as uc u es and a e equi ed o comply wi h go e nmen
egula ions, which a e ypically designed o mi iga e isks and p o ec deposi o s (Adam
e al.,2023;Ding & Wei,2023;Co nwell e al.,2023).
C edi isk is he bigges isk in banking, and i happens when bo owe s do no ul ill
hei con ac ual obliga ions and de aul in paying hei loans’ p incipal o in e es . De aul s
can occu on mo gages, c edi ca ds, ixed income secu i ies, and de i a i es (Pozo & Rojas,
2023;Telg e al.,2023;No iega e al.,2023;Fejza e al.,2022). C edi isk is de ined as he
possibili y o inancial loss due o a bo owe ’s inabili y o epay a loan o mee con ac ual
obliga ions; i e e s o he isk ha he lende may no ecei e he p incipal and in e es on he
loan, esul ing in dis up ed cash lows and inc eased cos s (Uma e al.,2021;B ownlees e al.,
2021;Yanenko a e al.,2021;Doko e al.,2021). To compensa e o c edi isk, lende s may
adjus loan e ms by inco po a ing addi ional cash lows. When he lende aces inc eased
c edi isk, i can be mi iga ed h ough a highe coupon a e ha p o ides mo e cash lows
(Kil e al.,2021;Cheng & Qu,2020;B ei e al.,2020).
Economies 2025,13, 139 3 o 24
Due o he na u e o he business model in he banking sys em, banks canno be ully
p o ec ed agains c edi isk and mus educe he amoun o losses caused by his isk by
using a ious mi iga ion s a egies (Misman & Bha i,2020;Y. Wang e al.,2020;Abbas e al.,
2019). Since c ises in his indus y a e o en unp edic able, banks can only con ol hei c edi
isk o an accep able ex en by di e si ying hei se ices, especially in lending. One o he
mos impo an echniques o cu bing c edi isk in banks is o eplace adi ional bo owe
e alua ion me hods wi h mode n c edi a ing and alida ion models, enabling bank man-
age s and policymake s o mo e accu a ely assess he c edi wo hiness o indi iduals and
legal en i ies (Ghenimi e al.,2017;Kabi e al.,2015;Lopez & Saidenbe g,2000).
Liquidi y isk is de ined as he unp epa edness o banks o p o ide c edi acili ies
o o make imely paymen s on deposi s. This isk is in e connec ed wi h o he inancial
isks, and he e o e i is di icul o measu e and con ol i . I is wo h no ing ha one
o he impo an elemen s o liquidi y isk managemen is he bank’s inancing s a egy,
which aims o p e en any signi ican gap be ween he ma u i y o asse s and liabili ies
(Ba ongo & Mbelwa,2024;Sidhu e al.,2023;Lang e al.,2023). Banks usually measu e
liquidi y isk using in e nal c i e ia and egula o y indica o s, as well as quali a i e analyses
o he indica o s in acco dance wi h he Basel egula ions. The main indica o used o
measu e liquidi y isk is he bank’s Es ima ed Ac i i y Du a ion. This c i e ion measu es
he pe iod du ing which he bank can mee i s paymen obliga ions unde a s ess scena io,
including he una ailabili y o new unding sou ces (Ba ongo & Mbelwa,2024;Choudha y
& Limodio,2022;T ang e al.,2021). One o he mos common and app op ia e me hods
o measu ing liquidi y isk is Value a Risk (VaR) analysis. This c i e ion exp esses he
maximum expec ed loss on he bank’s asse po olio o in es men po olio du ing a
ce ain pe iod o ime unde no mal ma ke condi ions and a a ce ain con idence le el
(Mohammad e al.,2020;Y. Chen e al.,2018;A i & Anees,2012).
I should be men ioned ha when he bank canno pay i s long- e m deb s and long-
e m inancial obliga ions, i is exposed o sol ency isk. Because he sol ency pa ame e
shows how much a inancial ins i u ion can manage i s ope a ions and acili a es he abili y
o plan and manage o he u u e, one o he impo an pa ame e s o e alua ing and
analyzing inancial heal h is a sol ency isk assessmen . Also, i a inancial ins i u ion such
as a bank seeks o assess i s sol ency, i mus examine i s equi y posi ion (Mi za e al.,2023;
Ki ikkaleli & Kaya ,2023;Sakou ogui,2020).
Mos exis ing s udies ha e ocused on ei he indi idual isks o s a ic co ela ions,
wi h li le a en ion paid o he dynamic causal ela ionships among mul iple isks in he
long un. Mo eo e , ew ha e employed obus econome ic amewo ks such as he Panel
Vec o E o Co ec ion Model (VECM) in his con ex . This s udy aims o ill ha gap by
analyzing he long- e m and sho - e m in e ac ions among sol ency, c edi , and liquidi y
isks using panel da a om 21 I anian banks o e he pe iod 2011–2023.
The es o his a icle is as ollows. In Sec ion 2, he de ini ion o impo an banking
isks and he esea ches done in he pas in his ield a e men ioned. In Sec ion 3, he
esea ch me hodology is ully examined. In Sec ion 4, he esul s ob ained om he p o-
posed models a e analyzed based on he in o ma ion used. Finally, in Sec ion 5, he inal
conclusion is s a ed and sugges ions o he u u e o expand he concep a e in oduced.
2. Li e a u e Re iew
In his sec ion, we a emp o p o ide comp ehensi e de ini ions o c edi isk, liquidi y
isk, and sol ency, hen p o ide an o e iew o he applied esea ch on all banks using
di e en models. A numbe o he s udies conduc ed on banks’ isks a e shown in Table 1,
along wi h e e ence o he models used.
Economies 2025,13, 139 4 o 24
Table 1. A Summa y o he S udies Conduc ed.
Yea
Resea ch Model C edi Risk Liquidi y Risk Sol ency Risk
2014
Imbie owicz and Rauch (2014) Panel VAR
2020
Bawa and Basu (2013) Gene alized Me hod o Momen s (GMM)
2020
Chenga e al. (2020) PLS-SEM Analysis
2020
Con e al. (2020) Dynamic Balance Shee unde S ess
2020
Djebali and Zaghdoudi (2020) Panel Smoo h Th eshold Reg ession (PSTR)
2021
Ahamed (2021) Panel Da a Reg ession
2021
Al-Husainy and Jadah (2021) Gene alized Me hod o Momen s (GMM)
2021
Ghenimi e al. (2021) Dynamic Panel Da a
2021
Ma ey (2021) Panel Da a Reg ession
2021
Oino (2021) Gene alized Me hod o Momen s (GMM)
2022
Abdelaziz e al. (2022) Seemingly Un ela ed Reg ession (SUR)
2022
Aldaso o e al. (2022) Simul aneous Equa ion Model (SEM)
2022
Ben Lahouel e al. (2024) CAMELS-DEA
2022
De Band e al. (2022) A Simple Po olio
2022
Naili and Lah ichi (2022) Gene alized Me hod o Momen s (GMM)
2023
Ca e a a e al. (2023) Pa ial Equilib ium Agen -Based
2023
Sha ma e al. (2023) Panel Da a Reg ession
2023
Vuong e al. (2023) LSDVC
2024
Ou Resea ch Panel Vec o E o Co ec ion Model
(VECM)
2.1. Theo e ical Backg ound
The heo e ical ounda ion o his s udy is ancho ed in he Financial Ins abili y Hy-
po hesis p oposed by Hyman Minsky (1975), which posi s ha inancial sys ems na u ally
e ol e owa d ins abili y du ing p olonged pe iods o economic calm. In such phases,
banks and inancial ins i u ions end o assume highe le els o isk, pa icula ly h ough
agg essi e c edi expansion and excessi e le e age. This makes hem mo e ulne able o
sudden liquidi y sho ages and sol ency p essu es. As no ed by Minsky, inancial ins i u-
ions may engage in iskie beha io , inc easing hei ulne abili y o sys emic shocks.
In pa allel, he Basel III egula ions (Basel Commi ee on Banking Supe ision,2010)
p o ide a comp ehensi e amewo k o managing c edi , liquidi y, and sol ency isks,
highligh ing hei in e connec ed na u e. Acco ding o Basel III, insu icien liquidi y
bu e s and poo c edi quali y can se e ely impai a bank’s sol ency, hus posing sys emic
isks. These pe spec i es suppo he need o join ly examine he dynamics o inancial
isks, as unde s anding hei in e ac ions is c i ical o enhancing banking sys em esilience.
The in e ac ion be ween liquidi y and sol ency is c ucial, as poo liquidi y posi ions may
lead o an inabili y o mee obliga ions, hus h ea ening sol ency.
2.2. Concep ualiza ion o Va iables
In line wi h he abo e heo e ical pe spec i es, his s udy concep ualizes i s key
a iables as ollows:
•
C edi Risk e e s o he p obabili y o a bank incu ing losses due o he ailu e o
bo owe s o mee hei inancial obliga ions. I is measu ed using indica o s such
as he Non-Pe o ming Loan (NPL) a io o Loan Loss P o isions. This aligns wi h
Minsky’s idea o inancial agili y h ough excessi e le e age and he Basel s anda ds
on c edi exposu es.
•
Liquidi y Risk is de ined as a bank’s inabili y o mee sho - e m obliga ions wi hou
incu ing unaccep able losses. This s udy adhe es o he Liquidi y Co e age Ra io
(LCR) and concep s such as Liquidi y-a -Risk, as emphasized in Basel III, o ame
his isk.
Economies 2025,13, 139 5 o 24
•
Sol ency Risk cap u es he po en ial o a bank ailing o mee i s long- e m obliga ions,
o en assessed h ough he Capi al Adequacy Ra io (CAR) o Tie 1 Capi al Ra io.
Sol ency e lec s he bank’s abili y o abso b losses and con inue ope a ing, hus ac ing
as a comp ehensi e measu e o inancial heal h.
2.3. Empi ical Li e a u e Re iew
Imbie owicz and Rauch (2014) in es iga e he ela ionship be ween liquidi y isk and
c edi isk in U.S. comme cial banks om 1998 o 2010 and hei impac on bank de aul
p obabili ies. They employ a Panel VAR model o analyze he ela ionship be ween liq-
uidi y isk and c edi isk, as well as a Logi eg ession model o p edic bank de aul s.
The indings e eal no signi ican economic ela ionship be ween he wo isks. Howe e ,
bo h isks indi idually inc ease he p obabili y o de aul (PD). In e es ingly, he join
e ec depends on he bank’s o e all isk le el: i agg a a es PD o mode a ely isky (wi h
10–30 PD
pe cen ) banks bu mi iga es PD o highly dis essed banks (wi h
70–90 PD
pe -
cen ), po en ially e lec ing “gambling o esu ec ion” beha io . These esul s unde sco e
he impo ance o join ly managing liquidi y and c edi isks o enhance a bank’s s abili y.
Bawa and Basu (2013) in es iga es he impac o es uc u ing asse s e o m on bank
c edi isk in India, ocusing on he pe iod 2006–2016. Using he Gene alized Me hod o
Momen s (GMM), he au ho examines he ela ionship be ween bank ope a ional abili y,
liquidi y, p o i abili y, and capi al wi h c edi isk, measu ed h ough non-pe o ming asse s
(GNPA). The indings highligh he use o es uc u ed asse s o conceal bad loans, which
inc eases c edi isk. The s udy also e eals bi-di ec ional causali y be ween hese a iables
and emphasizes he signi ican e ec o egula o y e o ms on imp o ing anspa ency and
educing c edi isk.
Chenga e al. (2020), aking a di e en app oach o analyzing he in e play be ween
isk managemen and bank p o i abili y in Sou h A ica, e eal ha e ec i e managemen o
c edi and liquidi y isks enhances p o i abili y. The use o ad anced PLS-SEM me hodology
con ibu es o unde s anding hese dynamics, p o iding insigh s o in e ac ion among
c edi and liquidi y isk and bank-speci ic isk. Thei es ima es show ha a one-uni
inc ease in c edi isk and liquidi y isk leads o inc eases in p o i abili y o 0.682 and
0.582, espec i ely.
Con e al. (2020) in oduce a comp ehensi e amewo k o assessing sol ency and
liquidi y isks simul aneously in inancial ins i u ions. By in eg a ing he sol ency-liquidi y
nexus, hei p oposed model add esses key limi a ions o adi ional s ess es ing. Using a
syn he ic balance shee , he s udy illus a es how shi s in isk ac o s such as in e es a es
and equi y ma ke shocks impac liquidi y and sol ency me ics. Fo example, unde a
se e e equi y ma ke shock (
−
1500 basis poin s), ma ke able asse s dec ease by €4.3 billion,
demons a ing signi ican liquidi y challenges. Addi ionally, he concep o Liquidi y-
a -Risk o e s a scena io-speci ic ool o e alua ing liquidi y equi emen s, p o iding
ac ionable insigh s o egula o y amewo ks like Basel III.
Djebali and Zaghdoudi (2020) explo e he nonlinea ela ionship be ween c edi and
liquidi y isks and bank s abili y in he MENA egion, iden i ying c i ical isk h esholds
using a Panel Smoo h Th eshold Reg ession (PSTR) model. The indings demons a e ha
isk le els below he h esholds o 13.16% (c edi isk) and 19.03% (liquidi y isk) posi i ely
con ibu e o s abili y, while su passing hese le els leads o des abiliza ion.
Ahamed (2021) examines ac o s in luencing liquidi y isk among comme cial banks in
Bangladesh using panel da a om 23 banks o e he pe iod 2005–2018. The s udy iden i ies
key bank-speci ic ac o s (e.g., bank size, e u n on equi y, and capi al adequacy a io) and
mac oeconomic a iables (e.g., GDP g ow h, in la ion, and domes ic c edi ) ha a ec
Economies 2025,13, 139 6 o 24
liquidi y isk. The indings show ha la ge banks ha e lowe liquidi y isk, in la ion
educes isk, and GDP g ow h and domes ic c edi inc ease i .
Al-Husainy and Jadah (2021) in a s udy examining he p o i abili y o 18 p i a e
comme cial banks lis ed on he I aqi S ock Exchange o e he pe iod 2010–2020, use a
dynamic panel Gene alized Me hod o Momen s (GMM) model o assess he in luence
o liquidi y and c edi isks on hei p oxy o bank pe o mance (ROA). The s udy inds
ha liquidi y isk (LR) has a posi i e, ye mode a e impac on ROA, wi h a coe icien o
0.348, while c edi isk (CR) has a signi ican nega i e e ec , wi h a coe icien o
−
2.012,
indica ing ha highe c edi isk educes a bank’s p o i abili y. Fu he mo e, he esul s
highligh he impo ance o bank size (BSIZE) and GDP g ow h (GDPG), which a e posi-
i ely co ela ed wi h p o i abili y, whe eas in la ion (INFL) shows a nega i e ela ionship,
sugges ing ha highe in la ion nega i ely impac s he p o i abili y o banks. These indings
unde line he impo ance o managing liquidi y and c edi isks e ec i ely o enhance a
bank’s pe o mance.
Ghenimi e al. (2021) iden i y key de e minan s o liquidi y isk in Islamic and con-
en ional banks ac oss he MENA egion om 2005 o 2015, highligh ing di e ences in
sensi i i y o mac oeconomic ac o s. Using GMM modeling, esul s show ha c edi isk
and liquidi y gaps a e signi ican d i e s o liquidi y isk in bo h sys ems. Howe e , Islamic
banks a e mo e in luenced by bank-speci ic ac o s, while mac oeconomic a iables such as
in la ion and GDP g ow h p ima ily impac con en ional banks.
Ma ey (2021) in es iga e he oles o liquidi y isk and c edi isk in de e mining
bank s abili y in Ghana, highligh ing a signi ican nega i e impac o liquidi y isk and an
insigni ican bu nega i e e ec o c edi isk. Employing a ixed-e ec s eg ession model,
he indings emphasize he need o Ghanaian banks o op imize liquidi y managemen
and adhe e o s ic e c edi policies.
Oino (2021) examines he ac o s in luencing bank sol ency, pa icula ly ocusing on
he in e play be ween c edi isk, liquidi y isk, egula o y capi al, and economic condi ions.
Using a panel da ase o he en la ges banks in he UK (2009–2018), he s udy employs
a Gene alized Me hod o Momen s (GMM) app oach. Key indings include a s ong link
be ween c edi isk and liquidi y isk, whe e ising non-pe o ming loans (NPLs) educe
liquidi y, nega i ely impac ing sol ency. Regula o y capi al, especially Tie 1 capi al,
posi i ely in luences bank sol ency and mi iga es isk. E iciency and economic g ow h
also imp o e sol ency, while excessi e economic eedom may inc ease c edi isk. The
s udy emphasizes main aining su icien egula o y capi al bu e s du ing economic booms
o abso b shocks du ing down u ns.
Abdelaziz e al. (2022) in es iga e how c edi and liquidi y isks in luence he p o -
i abili y o banks in he MENA egion. Using a sample o 38 con en ional banks om
10 coun ies o e 2004–2015, he s udy applies he Seemingly Un ela ed Reg ession
(SUR) me hod o analyze hese ela ionships. The indings e eal hese wo isks a e
in e ela ed—c edi isk ampli ies liquidi y isk and ice e sa.
Aldaso o e al. (2022) examine he in e ac ion be ween bank sol ency isk and unding
cos s in Ko ean banks, using a simul aneous equa ion model and p op ie a y da a. I
demons a es a wo-way eedback loop whe e inc eased ma ginal unding cos s aise
sol ency isks, and highe sol ency isks lead o inc eased unding cos s. The indings show
ha a 100-basis-poin inc ease in unding cos s co ela es wi h a 155-basis-poin dec ease in
sol ency. This nega i e ela ionship unde sco es he c i ical connec ion be ween a bank’s
unding cos s and i s sol ency isk, which, in u n, is linked o i s abili y o manage liquidi y
and c edi isk e ec i ely. The s udy also explo es he e ec s o mac op uden ial policies,
such as o eign exchange (FX)- ela ed measu es, in mi iga ing his nega i e eedback loop.
In line wi h hese indings, hei s udy sugges s ha he ela ionship be ween liquidi y and
Economies 2025,13, 139 7 o 24
c edi isks wi h sol ency isk is in e connec ed, wi h changes in one isk ype po en ially
in luencing he o he s. Fo example, highe liquidi y isk can lead o highe unding cos s,
which in u n can inc ease sol ency isk, as demons a ed in he s udy’s indings.
Ben Lahouel e al. (2024) in es iga e he ela ionship be ween liquidi y isk, i-
nancial s abili y, and income di e si ica ion in Eu opean banks pos -2008 c isis using
a CAMELS-DEA amewo k and a nonlinea PSTR model. The indings e eal ha liquid-
i y isk associa ed wi h liquidi y c ea ion enhances bank s abili y, especially unde g ea e
income di e si ica ion.
De Band e al. (2022) in es iga e he de e minan s o banks’ liquidi y in F ance,
ocusing on he in e play be ween ma ke and egula o y liquidi y equi emen s. Using
a heo e ical model and empi ical analysis, he s udy explo es how F ench banks adjus
hei liquidi y holdings unde sol ency and liquidi y cons ain s, especially du ing c ises.
The s udy e eals signi ican in e ac ions be ween liquidi y and sol ency, sugges ing
complemen a y e ec s du ing high-s ess pe iods. They ind a posi i e and signi ican
ela ionship be ween liquidi y and sol ency a ios, whe e a 1% inc ease in he sol ency
a io leads o a 5.20% ise in he liquidi y a io in he ollowing pe iod.
Naili and Lah ichi (2022) in es iga e he de e minan s o banks’ c edi isk in eme ging
ma ke s wi h a ocus on non-pe o ming loans (NPLs). Le e aging a la ge panel da ase , i
highligh s he signi ican impac o mac oeconomic condi ions, bank-speci ic ac o s, and
indus y-le el compe i ion on c edi isk. The indings unde line he impo ance o obus
isk managemen p ac ices and ailo ed egula o y in e en ions o mi iga ing NPL g ow h.
Ca e a a e al. (2023) le e age Minsky’s Financial Ins abili y Hypo hesis o in es iga e
inancial agili y and c edi isk dynamics. They in oduce an in eg a ed compu a ional
model combining agen -based simula ions wi h c edi isk modeling amewo ks o classi y
i ms by hei inancial obus ness. The analysis ocuses on he impac o economic cycles
and i m-le el beha io on sys emic s abili y, o e ing insigh s in o he pe sis ence o
high- isk en i ies (e.g., Ponzi and Zombie i ms) and hei implica ions o c edi isk
managemen and egula o y policies. This app oach p o ides a nuanced unde s anding o
inancial ins abili y and i s b oade economic consequences.
Sha ma e al. (2023) in es iga e he impac o G oss Non-Pe o ming Asse s (GNPA)
on key pe o mance indica o s such as p o i abili y, liquidi y, and sol ency in he Indian
banking sys em. Using panel da a om 30 Indian banks (2014–2020), he s udy applies
a ious eg ession models, including Fixed E ec s, Random E ec s, and Seemingly Un e-
la ed Reg ession (SUR) models, o analyze ela ionships. Key indings indica e ha GNPA
nega i ely a ec s liquidi y a ios (Cash Flow Ma gin Ra io (CFMR), Cu en Ra io (CTR),
and Acid Tes Ra io (ATR)) and Sol ency (Capi al Adequacy Ra io (CAR)).
Vuong e al. (2023) in es iga e he ela ionship be ween bank liquidi y c ea ion and
bank isk- aking in Vie nam’s ansi ion economy. Using a sample o 33 Vie namese
comme cial banks spanning he yea s 2009–2020, he au ho s apply he Bias-Co ec ed
Leas -Squa es wi h Dummy Va iables (LSDVC) me hod o examine he impac . They
ind ha liquidi y c ea ion signi ican ly educes NPLs, sugges ing ha inc eased liquidi y
enhances bo owe s’ epaymen capaci y and s abilizes c edi isk.
Al hough se e al s udies explo e bila e al ela ionships among c edi , liquidi y, and
sol ency isks, e y ew in eg a e all h ee in a dynamic panel amewo k—especially in
he con ex o eme ging economies like I an. This s udy ills ha gap.
3. Me hodology
This esea ch adop s a quan i a i e, explana o y (causal) app oach wi h a longi udinal
design, aiming o examine he dynamic in e ac ions among sol ency isk, c edi isk, and
Economies 2025,13, 139 8 o 24
liquidi y isk in I anian banks o e ime. The s udy also holds applied signi icance, as i s
indings a e ele an o banking supe ision and isk managemen policy.
The in o ma ion used in his esea ch was ex ac ed om he inancial s a emen s o
21 banks lis ed in he I anian capi al ma ke du ing he yea s 2011 o 2023, and i was
collec ed a a equency o six mon hs. Due o da a a ailabili y limi a ions, his s udy
p ima ily elies on semi-annual inancial s a emen s.
The s a is ical popula ion includes all banks lis ed on he Teh an S ock Exchange (TSE)
and I an Fa a Bou se (IFB) du ing he pe iod 2011–2023. F om his popula ion, a sample o
21 banks was selec ed based on da a a ailabili y, con inui y in epo ing, and comple eness
o inancial disclosu es ac oss he 13-yea ho izon. Banks wi h missing o inconsis en da a
in key a iables we e excluded o ensu e obus ness.
The p ima y sou ces om which da a we e collec ed include, Codal.i o audi ed
inancial s a emen s (Equi y, Loan po olio, Cash balances, e c.), Cen al Bank o I an o
mac oeconomic a iables (GDP g ow h, CPI in la ion, ola ili y index), and he TSETMC
and TSE da abases o c oss-check ins i u ional in o ma ion.
To ensu e he alidi y and eliabili y o he da a, c oss- e i ica ion was done ac oss
sou ces, and semi-annual agg ega ion was applied consis en ly o educe seasonali y e ec s.
Only publicly disclosed, egula ed, and audi ed igu es we e included.
As i is men ioned, he da ase o a iables is ex ac ed h ee main sou ces: banks’
inancial s a emen s, a comp ehensi e co po a e da abase, and he da abases o he Cen al
Bank o I an. The inancial s a emen s o he examined banks o m he basis o calcula ing
sol ency, c edi isk, and liquidi y isk. These inancial indica o s a e necessa y o unde -
s and he s abili y and isk cha ac e is ics o he banking sys em. Also, he p ima y da a
o he a iables we e p epa ed om he comp ehensi e da abase o all companies lis ed
on he Codal si e, and he inancial s a emen s we e de i ed om his da a sou ce. Finally,
o ep esen he mac oeconomic elemen s ele an o a banking isk assessmen , da a on
key a iables such as economic g ow h, in la ion, and unce ain y measu es we e ob ained
om publicly a ailable da abases p o ided by he Cen al Bank o I an. Figu e 1shows a
schema ic o he p oposed me hod in his esea ch.
Figu e 1. The Schema ic Summa y o All S eps in he P oposed VECM.
Economies 2025,13, 139 15 o 24
4. Resul s
The explo a ion o dynamics among sol ency, c edi isk, and liquidi y isk u ilized
a sophis ica ed Vec o E o Co ec ion Model (VECM) in his analysis. Spanning an ex-
ensi e da ase ac oss 12 yea s, encompassing 21 banks om 2011 o 2023, he VECM
amewo k was cons uc ed wi h h ee endogenous a iables and h ee exogenous a i-
ables. I s lag o de o 2, de e mined by he Schwa z In o ma ion C i e ion (SIC), enabled a
comp ehensi e unde s anding o empo al ela ionships. To un a el he complex in e play
among hese inancial ac o s, he analysis en u ed beyond me e es ima ion. O hogonal-
ized Impulse Response Func ions (IRFs) and a iance decomposi ion we e me iculously
compu ed pos -VECM es ima ion (Figu e 2). These ools we e ins umen al in disce n-
ing he nuanced impac o each a iable o e he empo al ho izon, shedding ligh on
sho - e m dynamics and long- e m equilib ium ela ionships.
Figu e 2. O hogonalized Impulse Response Func ions along wi h 95% Con idence Le el.
In con igu ing he model, he a iable o de ing, deno ed as Yi = [CRi , SERi , LRi ],
was me iculously aligned wi h he G ange causali y esul s, ensu ing cohe ence and
consis ency. This o de ing, ollowing he Cholesky echnique, s a egically posi ioned
SER as he mos endogenous a iable wi hin he amewo k. Meanwhile, LR eme ged
as he mos exogenous, e lec ing i s limi ed in luence on he dynamics compa ed o
o he a iables in he model. This delibe a e a angemen con ibu es o a comp ehensi e
unde s anding o he in ica e ela ionships among hese c i ical inancial indica o s.
The Impulse Response Func ion (IRF) echnique is a obus analy ical me hod used o
examine he dynamic in e ac ions among a iables in a sys em o e ime. I illumina es
he impac o a one- ime shock o inno a ion o a pa icula a iable on he en i e sys em’s
Economies 2025,13, 139 16 o 24
esponse, depic ing how each a iable eac s and in luences o he s wi hin he sys em. By
compu ing IRFs, analys s gain aluable insigh s in o sho - e m eac ions and long- e m
equilib ium ela ionships among he a iables.
The conduc ed IRF analysis e ealed in iguing insigh s in o he ela ionships among
sol ency, c edi isk, and liquidi y isk in he banking sec o . A pi o al inding was he
in e se ela ionship obse ed be ween a bank’s sol ency and i s c edi isk. A sol en
bank ended o exhibi lowe c edi isk, e lec ing a ce ain le el o inancial obus ness.
Howe e , he e ec o sol ency on c edi isk became cons an a e i e pe iods. On he
o he hand, sol ency did no exhibi a subs an ial e ec on liquidi y isk. Mo eo e , he
s udy indica ed a posi i e impac o a a o able liquidi y posi ion on a bank’s sol ency,
aligning wi h an icipa ed expec a ions. In ac , he esponse o a posi i e shock in liquidi y
showcased a posi i e impac on he sol ency a iable, SER, indica ing an inc ease in
sol ency o e ime. Howe e , his liquidi y-d i en impac exhibi ed a ela i ely lowe
in luence on c edi isk. Con e sely, a highe le el o c edi isk e ealed a nega i e
in luence on a bank’s sol ency, po en ially leading o a decline in sol ency o e ime.
These indings unde sco e he in ica e in e play among hese pi o al inancial a iables
wi hin he banking sec o , shedding ligh on hei complex dynamics and mu ual in luence
o e ime.
Va iance decomposi ion is a powe ul analy ical ool used o disce n he ex en o
which each a iable con ibu es o he o e all a iabili y in a sys em o e a speci ied ime
ho izon. I disen angles he p opo ion o a iabili y in each a iable ha can be a ibu ed
o i s own pas alues (au o eg essi e componen ) and he in luence om o he a iables
wi hin he sys em. By quan i ying hese con ibu ions, a iance decomposi ion aids in
unde s anding he ela i e impo ance o each a iable in explaining luc ua ions wi hin
he sys em. In Table 9p esen s he a iance decomposi ion esul s o he a iables used in
his s udy.
Finally o each model a iable we compu e he a iance decomposi ion. The esul s
o he a iance decomposi ion o e a 12-yea ho izon ollowing he ini ial shock a e sum-
ma ized in he Table 9. The a iances o SER a e in luenced by he a iable CR, wi h CR’s
impac showing a p og essi e inc ease o e ime on SER. The a iance o c edi isk is
pa ially explained by SER, while he e ec o liquidi y is no s a is ically signi ican . The
a iance in liquidi y isk is no signi ican ly explained by he o he a iables. Table 9shows
a iance decomposi ion a he ho izon o 12 yea s o he PVAR a iables.
Diagnos ic es s including esidual au oco ela ion, no mali y, and he e oskedas ici y
we e pe o med o alida e model assump ions. Addi ionally, obus ness checks wi h
a ying lag o de s and sub-sample analysis con i med he consis ency o he main indings.
The empi ical esul s ob ained om he VECM analysis p o ide se e al c i ical insigh s
in o he in e play be ween c edi isk, liquidi y isk, and sol ency in I anian banks. The
nega i e ela ionship be ween c edi isk and sol ency ein o ces he indings o s udies
such as Imbie owicz and Rauch (2014) and Oino (2021), which sugges ha a highe
le el o non-pe o ming loans e odes capi al bu e s and educes inancial s abili y. This
is pa icula ly impo an in he I anian con ex , whe e c edi isk is ampli ied by weak
bo owe assessmen sys ems and p olonged economic ins abili y.
In con as , he posi i e impac o liquidi y on sol ency highligh s he ole o liquidi y
bu e s as a p o ec i e shield du ing inancial s ess. This inding aligns wi h he Basel III
amewo k and suppo s he no ion ha main aining su icien liquid asse s helps banks
abso b shocks and sus ain ope a ions, especially in ola ile en i onmen s. Howe e , he
limi ed e ec o c edi isk on liquidi y obse ed in his s udy con adic s se e al s udies in
ma u e ma ke s, possibly due o he speci ic egula o y s uc u e and cen alized mone a y
sys em in I an.
Economies 2025,13, 139 17 o 24
Table 9. Va iance Decomposi ion o Va iables.
Pe iod S.E. CR SER LR
Va iance Decomposi ion o CR
1 0.126894 100.0000 0.000000 0.000000
2 0.161197 96.23614 3.502368 0.261490
3 0.180135 91.06805 8.654307 0.277638
4 0.193946 85.79814 13.90163 0.300228
5 0.205208 81.14106 18.55515 0.303796
6 0.214977 77.13455 22.56122 0.304231
7 0.223742 73.70028 25.99807 0.301649
8 0.231800 70.72830 28.97357 0.298130
9 0.239333 68.12795 31.57793 0.294124
10 0.246467 65.82818 33.88178 0.290038
Va iance Decomposi ion o SER
1 0.047369 1.892068 98.10793 0.000000
2 0.088837 3.853944 95.81276 0.333297
3 0.127474 6.322745 93.23779 0.439464
4 0.163421 8.815383 90.64604 0.538579
5 0.196785 11.07934 88.31437 0.606285
6 0.227833 13.02877 86.31291 0.658315
7 0.256799 14.66442 84.63792 0.697656
8 0.283910 16.02135 83.25036 0.728290
9 0.309374 17.14385 82.10372 0.752428
10 0.333378 18.07424 81.15399 0.771770
Va iance Decomposi ion o LR
1 0.043281 0.612912 1.527705 97.85938
2 0.051408 0.625126 1.084414 98.29046
3 0.060930 0.529512 0.772592 98.69790
4 0.068266 0.443168 0.646201 98.91063
5 0.075108 0.370005 0.570070 99.05993
6 0.081276 0.315993 0.531194 99.15281
7 0.087023 0.276654 0.508319 99.21503
8 0.092398 0.248407 0.495500 99.25609
9 0.097475 0.227909 0.488043 99.28405
10 0.102298 0.212814 0.483840 99.30335
Ano he impo an implica ion o he indings is he weak in luence o sol ency and
c edi isk on liquidi y isk, sugges ing ha liquidi y in I anian banks is less esponsi e
o undamen al isks and mo e a ec ed by ex e nal cons ain s such as mone a y policy,
sanc ions, and capi al con ols. This di e gence om in e na ional ends emphasizes he
need o con ex -speci ic isk managemen amewo ks in eme ging economies.
Mo eo e , he a iance decomposi ion analysis e eals ha while sol ency and c edi
isk mu ually in luence each o he o e ime, liquidi y isk emains mos ly exogenous. This
has p ac ical implica ions o policy make s, indica ing ha imp o ing bank liquidi y may
equi e b oade inancial e o ms beyond in e nal isk mi iga ion s a egies.
These indings con ibu e o he heo e ical discou se on sys emic isk by emphasizing
he asymme ic and con ex -dependen na u e o in e ac ions among key banking isks.
They also o e p ac ical guidance o egula o s, sugges ing ha c edi quali y and liquidi y
ese es should be managed oge he , bu wi h dis inc ools and p io i ies depending on
he dominan mac oeconomic isks in he en i onmen .
While he empi ical analysis in his s udy is limi ed by he a ailabili y o ce ain
mac oeconomic a iables, i is essen ial o ecognize ha economic channels play a c i ical
ole in in luencing he ela ionships be ween bank isk componen s such as liquidi y isk,
c edi isk, and sol ency isk. In pa icula , go e nmen iscal condi ions, such as budge
de ici s, can ha e di ec and indi ec e ec s on banks’ isk p o iles. As ou lined by Sil a
(2021), go e nmen de ici s can inc ease c edi isk h ough bo h di ec channels, such
as go e nmen gua an ees, and indi ec channels, such as mul iplie s, a ec ing banks’
exposu e o non-pe o ming loans (NPLs). Fu he mo e, de ici s also in luence banks’
Economies 2025,13, 139 18 o 24
liquidi y ia hei e ec s on so e eign bonds and c edi isk, impac ing banks’ p o isions,
which a e a signi ican expense acc ual, ul ima ely a ec ing hei p o i abili y. This in e play
sugges s ha go e nmen iscal policies, including decisions on de ici inancing, di ec ly
shape banks’ inancial heal h and s abili y. The indings by Dan as e al. (2023) also suppo
his iew, indica ing ha go e nmen gua an ees and ea nings smoo hing play signi ican
oles in mi iga ing isks a he bank le el.
Ano he c i ical economic channel, pa icula ly ele an o he pe iod o his s udy, is
geopoli ical unce ain y, wi h e en s like he B exi e e endum and he 2020 COVID-19
pandemic ha ing subs an ial global spillo e e ec s. The B exi o e in oduced signi i-
can unce ain y ac oss bo h de eloped and eme ging-ma ke economies, including I an’s,
despi e i s ela i e economic disconnec ion om he U.S. (Campello e al. (2022)). Such
geopoli ical de elopmen s can impac co po a e in es men , labo ma ke s, and inancial
s abili y, indi ec ly a ec ing bank isk- aking beha io s. Mo eo e , geopoli ical unce ain y
can inc ease ola ili y in bo h co po a e ea nings and so e eign deb ma ke s, u he in lu-
encing banks’ c edi and liquidi y isk exposu e. Gi en he economic in e connec edness
o global ma ke s, including I an’s, egional spillo e s and mac oeconomic shocks du -
ing he sample pe iod likely in luenced he dynamics o isk- aking beha io s wi hin he
banking sec o .
5. Conclusions
This s udy in es iga es he dynamic in e ac ions among c edi isk, liquidi y isk, and
sol ency in I anian banks using a Panel Vec o E o Co ec ion Model (VECM) o e he
pe iod 2011–2023. The esul s e eal a signi ican nega i e e ec o c edi isk on bank
sol ency, highligh ing he ulne abili y o capi al adequacy o loan de aul exposu e. In
con as , liquidi y isk does no appea o signi ican ly in luence sol ency o c edi isk,
sugges ing i s ole is mo e isola ed in he I anian banking con ex . Meanwhile, highe
sol ency le els a e shown o educe c edi isk, unde sco ing he impo ance o s ong
capi al bu e s.
I an’s banking sec o p esen s a unique case o sys emic isk unde pe sis en sanc ions
and in la iona y p essu e. Analyzing isk in e ac ions in his en i onmen no only adds
o he li e a u e on eme ging ma ke s bu also demons a es how banks ope a e unde
p olonged inancial cons ain , o e ing lessons o egions acing economic u bulence o
ins i u ional agili y.
In he I anian banking sys em, liquidi y cons ain s a e p ima ily d i en by unding
liquidi y sho ages a he han ma ke liquidi y, due o he unde de eloped s a e o capi al
ma ke s and limi ed asse adabili y. As sugges ed by B unne meie and Pede sen (2009),
ma ke liquidi y and unding liquidi y a e in e connec ed, bu in I an’s case, he dominance
o go e nmen owne ship and eliance on cen al bank acili ies make unding liquidi y
he mo e ele an dimension. The e o e, he esul s should be in e p e ed wi hin he
amewo k o cons ained unding access a he han impai ed ma ke liquidi y.
Banks ace signi ican exposu e o a ious isks. The 2008 inancial c isis highligh ed
he c i ical impo ance o bank isk managemen and i s a - eaching economic conse-
quences. F om a na ional pe spec i e, banking c ises ha e his o ically led o se e e eco-
nomic dis up ions, demons a ing he sys emic ulne abili y associa ed wi h inancial
ins i u ions. In his s udy, we p o ide new empi ical e idence abou he ela ionship be-
ween bank isks and bank sol ency. We show ha a be e liquidi y posi ion o a bank has
a posi i e e ec on a bank’s sol ency, unde lining he impo ance o liquidi y managemen
in he banking indus y.
Mo eo e , ou indings e ealed an an icipa ed ad e se impac o c edi isk on a
bank’s sol ency. Howe e , i s in luence on liquidi y isk did no demons a e s a is ical
Economies 2025,13, 139 19 o 24
signi icance. This implies ha a loan de aul signi ican ly impac s a bank’s sol ency
compa ed o i s e ec on liquidi y isk. In essence, e icien cash and liquidi y managemen
may no inhe en ly ansla e o imp o ed c edi isk managemen . Addi ionally, a bank
migh no encoun e liquidi y issues e en wi h a highe pe cen age o non-pe o ming
loans, bu concu en ly, his could comp omise i s sol ency.
Regula o y guidelines o en s ipula e he main enance o a ce ain sol ency le el
o ensu e inancial s abili y. Mee ing hese equi emen s could be a p io i y o banks,
di ec ing hei e o s owa d bols e ing sol ency while no di ec ly a ec ing liquidi y
managemen . Also, he quali y o asse s held by banks migh be such ha while non-
pe o ming loans inc ease c edi isk, hey may no di ec ly a ec he liquidi y posi ion.
Banks may main ain su icien liquid asse s o add ess sho - e m obliga ions e en in he
p esence o inc eased c edi isk.
Finally, an inc eased sol ency dec eases a bank’s c edi isk, bu i does no impac i s
liquidi y. Imp o ed sol ency implies a bols e ed capi al base. Banks wi h highe sol ency
a ios a e be e posi ioned o abso b losses om non-pe o ming loans, he eby educing
hei c edi isk. Howe e , his su plus capi al does no di ec ly a ec liquidi y, as i may be
p ima ily ese ed o c edi isk co e age a he han sho - e m liquidi y needs.
Fo p ospec i e a enues o esea ch, da a en elopmen analysis (DEA) models (Hen-
iques e al.,2020;Peykani e al.,2020;Y. C. Chen e al.,2020;Peykani e al.,2022;Ben
Lahouel e al.,2024) and machine lea ning (ML) algo i hms (Bha o e e al.,2020;Pe opou-
los e al.,2020;Bussmann e al.,2021;She y e al.,2022;Shi e al.,2022;A aujo e al.,2023;
Doumpos e al.,2023;Kuma e al.,2023;Usman e al.,2023;Zaki e al.,2024) could be
employed o examine he in e ela ionships among sol ency, liquidi y, and c edi isks in
he banking sys em. Addi ionally, inco po a ing analyses o ope a ional and ma ke isks
would u he en ich he unde s anding o comp ehensi e bank isk dynamics.
This esea ch con ibu es o he heo e ical li e a u e on sys emic isk in eme ging
ma ke s by demons a ing he asymme ic and di ec ional na u e o he ela ionships among
key banking isks. I adds empi ical suppo o Minsky’s Financial Ins abili y Hypo hesis
and alida es elemen s o Basel III’s in eg a ed isk managemen amewo k, especially
ega ding he ein o cing eedback loop be ween c edi isk and sol ency. By using he
VECM amewo k, he s udy emphasizes he necessi y o modeling bo h sho - e m shocks
and long- e m equilib ium in he con ex o inancial agili y.
F om a policy pe spec i e, he indings sugges ha I anian banks and egula o s
should p io i ize s eng hening capi al adequacy as a p oac i e s a egy o mi iga e c edi
isk. While liquidi y bu e s emain impo an , hey appea o play a seconda y ole
in de e mining inancial esilience in he cu en en i onmen . Fu he mo e, egula o s
may conside implemen ing di e en ia ed capi al equi emen s based on he isk p o-
iles o indi idual banks, especially hose wi h high exposu e o non-pe o ming loans.
Risk manage s should also a oid assuming ha liquidi y imp o emen s will au oma i-
cally educe c edi isk and ins ead add ess he wo dimensions h ough a ge ed and
sepa a e policies.
This s udy is subjec o ce ain limi a ions. Fi s , he eliabili y o bank- epo ed da a
in I an may be a ec ed by egula o y incen i es o disclosu e inconsis encies. Second, he
gene aliza ion o he esul s o o he eme ging ma ke s should be made cau iously, gi en
he unique mac o- inancial con ex shaped by sanc ions, in la ion ola ili y, and cen alized
banking egula ions.
Fu u e s udies could explo e addi ional isk dimensions—such as ope a ional isk
and ma ke isk—and hei in eg a ion wi h he cu en amewo k. Mo eo e , Da a
En elopmen Analysis (DEA) and Machine Lea ning (ML) echniques can p o ide al e -
Economies 2025,13, 139 20 o 24
na i e, non-pa ame ic insigh s in o isk e iciency and p edic ion models. C oss-coun y
compa isons could also help con ex ualize he I anian case wi hin b oade global ends.
While his s udy inco po a es VIX as a gene al p oxy o ma ke -based unce ain y,
we acknowledge he limi a ions a ising om he una ailabili y o mo e con ex -speci ic
mac oeconomic indica o s—pa icula ly hose e lec ing iscal dynamics, egional geopoli i-
cal shocks, and b oade global unce ain y spillo e s. Due o da a cons ain s and conce ns
abou he consis ency and eliabili y o such indica o s o I an and i s key economic
pa ne s, we e ained om including hem in ou empi ical model o p ese e in e nal
alidi y. Fu u e esea ch could bene i om he use o egion-speci ic unce ain y indices
and comp ehensi e mac oeconomic da ase s (e.g., om sou ces such as he Economic
Policy Unce ain y Index), enabling a deepe explo a ion o he ansmission mechanisms
linking mac o-le el shocks o bank-le el isk dynamics.
While he cu en s udy has ocused on a ailable da a and highligh ed he limi a ions
o inco po a ing ce ain mac oeconomic a iables, we belie e ha u u e esea ch could
signi ican ly bene i om he inclusion o b oade iscal and geopoli ical da a. Speci ically,
s udies inco po a ing go e nmen de ici da a and geopoli ical e en s (such as ade wa s,
sanc ions, o egional con lic s) would p o ide a mo e comp ehensi e unde s anding o
he ex e nal shocks impac ing banks’ isk p o iles. Fu u e analyses could also explo e he
po en ial in luence o o he economic condi ions, such as GDP g ow h, in la ion, and global
ma ke ola ili y, using mo e egion-speci ic and high-quali y da ase s. These s udies,
ideally d awing om sou ces like Campello e al. (2022), Co es e al. (2024), Sil a (2021),
Zaki e al. (2024), Campello e al. (2023), and Co es e al. (2019), would o e deepe
insigh s in o he complex in e dependencies be ween mac oeconomic condi ions and
bank isks.
Au ho Con ibu ions: Concep ualiza ion, P.P., M.S., C.T., S.E.S. and H.K.; me hodology, P.P., M.S.,
C.T., S.E.S. and H.K.; so wa e, P.P., M.S., C.T., S.E.S. and H.K.; alida ion, P.P., M.S., C.T., S.E.S.
and H.K.; o mal analysis, P.P., M.S., C.T., S.E.S. and H.K.; in es iga ion, P.P., M.S., C.T., S.E.S. and
H.K.; esou ces, P.P., M.S., C.T., S.E.S. and H.K.; da a cu a ion, P.P., M.S., C.T., S.E.S. and H.K.;
w i ing—o iginal d a p epa a ion, P.P., M.S., C.T., S.E.S. and H.K.; w i ing— e iew and edi ing, P.P.,
M.S., C.T., S.E.S. and H.K.; isualiza ion, P.P., M.S., C.T., S.E.S. and H.K.; supe ision, P.P., M.S., C.T.
and S.E.S.; p ojec adminis a ion, P.P., M.S., C.T. and S.E.S.; All au ho s ha e ead and ag eed o he
published e sion o he manusc ip .
Funding: This esea ch ecei ed no ex e nal unding.
Da a A ailabili y S a emen : Da a is a ailable upon eques .
Con lic s o In e es : The au ho s decla e no con lic s o in e es .
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