Examining the impact of bank cost efficiency on non-performing loans in a dollarised economy: Evidence from Zimbabwe

Ka uka, Blessing; Mudzingi i, Cal in; Vengesai, Edson; Ma i e, Juniou s
A icle
Examining he impac o bank cos e iciency on non-
pe o ming loans in a dolla ised economy: E idence om
Zimbabwe
O ganiza ions and Ma ke s in Eme ging Economies
P o ided in Coope a ion wi h:
Facul y o Economics and Business Adminis a ion, Vilnius Uni e si y
Sugges ed Ci a ion: Ka uka, Blessing; Mudzingi i, Cal in; Vengesai, Edson; Ma i e, Juniou s (2024) :
Examining he impac o bank cos e iciency on non-pe o ming loans in a dolla ised economy:
E idence om Zimbabwe, O ganiza ions and Ma ke s in Eme ging Economies, ISSN 2345-0037,
Vilnius Uni e si y P ess, Vilnius, Vol. 15, Iss. 2, pp. 356-377,
h ps://doi.o g/10.15388/omee.2024.15.17
This Ve sion is a ailable a :
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356
O ganiza ions and Ma ke s in Eme ging Economies ISSN 2029-4581 eISSN 2345-0037
2024, ol. 15, no. 2(31), pp. 356–377 DOI: h ps://doi.o g/10.15388/omee.2024.15.17
Examining he Impac o Bank Cos E iciency
on Non-Pe o ming Loans in a Dolla ised
Economy: E idence om Zimbabwe
Blessing Ka uka (co esponding au ho )
Uni e si y o he F ee S a e, Sou h A ica
blessingka [email protected]
h ps://o cid.o g/0000-0003-4716-8399
h ps:// o .o g/009xwd568
Cal in Mudzingi i
Uni e si y o he F ee S a e, Sou h A ica
Mudzingi iC@u s.ac.za
h ps://o cid.o g/0000-0002-1186-4109
h ps:// o .o g/009xwd568
Edson Vengesai
Uni e si y o he F ee S a e, Sou h A ica
VengesaiE@u s.ac.za
h ps://o cid.o g/0000-0002-9088-2603
h ps:// o .o g/009xwd568
Juniou s Ma i e
Rhodes Uni e si y, Sou h A ica
j.m[email p o ec ed]c.za
h ps://o cid.o g/0000-0002-6648-7582
h ps:// o .o g/016sewp10
Abs ac . This pape in es iga es he e ec s o cos e iciency on non-pe o ming loans (NPLs) in Zim-
babwe du ing dolla isa ion. The esea ch applies he andom e ec s and boo s ap quan ile eg ession
models using he ull dolla isa ion e a da ase o 13 banks om 2009 o 2017. The ob ained esul s
e ealed ha : (i) he a e age cos e iciency sco e o he Zimbabwean banking indus y is 81.36%, (ii)
imp o emen in cos e iciency leads o an inc ease in NPLs bu begins o all o a cos ine iciency le el
o 7.14% and below, (iii) he e ec o bank cos e iciency on NPLs is p ominen and highly signi ican
Recei ed: 8/3/2024. Accep ed: 20/6/2024
Copy igh © 2024 Blessing Ka uka, Cal in Mudzingi i, Edson Vengesai, Juniou s Ma i e. Published by Vilnius Uni e si y
P ess. This is an Open Access a icle dis ibu ed unde he e ms o he C ea i e Commons A ibu ion Licence, which pe -
mi s un es ic ed use, dis ibu ion, and ep oduc ion in any medium, p o ided he o iginal au ho and sou ce a e c edi ed.
Con en s lis s a ailable a Vilnius Uni e si y P ess
357
Blessing Ka uka, Cal in Mudzingi i, Edson Vengesai, Juniou s Ma i e. Examining he Impac o Bank Cos E iciency
on Non-Pe o ming Loans in a Dolla ised Economy: E idence om Zimbabwe
a a highe quan ile (90 h), (i ) he in e ac ion e ec be ween cos e iciency and bank size on NPLs is
nega i e and signi ican . Acco ding o hese esul s, NPLs end o all when la ge banks a e mo e cos -
e icien . Thus, he p esen s udy ecommends ha banks employ s a egies ha simul aneously imp o e
he asse base and cos e iciency.
Keywo ds: non-pe o ming loans, cos e iciency, skimping hypo hesis, dolla isa ion, quan ile eg ession,
quad a ic eg ession
In oduc ion
Non-pe o ming loans a e a big challenge in mos de eloping economies. The domi-
nance o non-pe o ming loans (NPLs) educes he capaci y o banks o lend o eco-
nomic agen s, hus lowe ing he c edi mul iplie e ec (Chen & Lee, 2023). Mo e
so, g ow h in non-pe o ming loans s ock has b oade ami ica ions on he banking
indus y’s pe o mance, and au ho i ies should endea ou o keep hem unde con-
ol since esol ing NPLs ha ha e eached sys emic le els is cos ly and complex
(Baudino & Yun, 2017; Bello i e al., 2021). NPLs can lead o bank ailu es and bank
uns, which p ecipi a es inancial c isis ha s i les economic g ow h. The se e i y o
he impac o bank ailu e on he economy has been wi nessed by he collapse o Ban-
co Popula in Spain in 2017, Lehman B o he s in USA in 2008 and No he n Rock in
he UK in 2007. Also, a mo e ecen case is he collapse o Silicon Valley Bank in he
US which signi ican ly shakened he US banking indus y (Vo & Le, 2023).
The connec ion be ween non-pe o ming loans and bank cos e iciency is a sub-
jec o subs an ial in e es in he banking sec o . While he ela ionship be ween
non-pe o ming and bank cos e iciency loans is mul idimensional, exis ing s ud-
ies posi ha he wo a e in e linked (Büyükoğlu e al., 2021; Khan e al., 2020). As
de ined byKociso a (2014), cos e iciency measu es how close a bank’s expend-
i u e is o a bes -p ac ice bank’s cos o p oducing he same ou pu bundle unde
he same condi ions. Thus, a cos -e iciency es is essen ial because i indica es
whe he he bank’s inpu s should be educed o inc eased. In hei ex ensi e wo k
in he US, Be ge and DeYoung (1997) disco e ed ha declining cos -e iciency
causes NPLs o ise, and hey e med his he bad managemen hypo hesis. In he
same pape , he au ho s also no ed ha high cos -e iciency esul s in high NPLs,
and hey e e ed o his condi ion as he skimping hypo hesis. In addi ion o hese
hypo heses,Be ge and DeYoung (1997) also p opounded he bad luck hypo hesis,
which pos ula es ha ex e nal e en s ins iga e an inc ease in NPLs, which leads o
de e io a ing cos e iciency.
In he Zimbabwean con ex , NPLs we e p e alen be o e and a e dolla isa ion.
As a esul , he g ow h in NPLs e oded banks’ sol ency and p o i abili y (Masun-
da, 2014). The inc ease in NPLs had sys em-wide implica ions ha s opped he
banking sys em om pe o ming i s no mal manda e, hus dis o ing he inancial
in e media ion p ocess.
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ISSN 2029-4581 eISSN 2345-0037 O ganiza ions and Ma ke s in Eme ging Economies
Conce ning indus y’s e iciency, he cos -e iciency a io (measu ed by he
cos - o-income a io) was highly ola ile du ing dolla isa ion. The indus y’s cos -
o-income a io wo sened o 185% in 2011 om 94.38% in 2009. By he end o he
dolla isa ion e a in 2017, he a io had imp o ed o 75.36% (Rese e Bank o Zim-
babwe, 2018). Howe e , he luc ua ions in he cos -e iciency a io a ec banks’
NPLs posi ion as assumed by bad managemen and skimping hypo heses (Mamon-
o , 2013). Low and high cos -e iciency pe iods may ha e igge ed a ise in NPLs
in Zimbabwe. To examine he e ec o cos e iciency on NPLs in Zimbabwe, he
esea che s eso ed o empi ical analysis o he en i e dolla isa ion pe iod. Con-
comi an ly, banks we e epo ed o be p o i ee ing om cha ging exo bi an a es
and ees o bank cus ome s (Abel, 2018). This aised ques ions on whe he Zim-
babwean banks a e e icien o ine icien in hei ope a ions. Following he no ion
ha Zimbabwean banks ollow a adi ional banking model whe e lending is hei
main ac i i y ha c ea es asse s and gene a es mos o hei income, i is impe a i e
o empi ically examine how cos -e iciency ends in luenced NPLs.
The pape ’s main goal is o in es iga e he e ec o bank cos e iciency on NPLs
o ma ion. The pape adds o he exis ing li e a u e in he ollowing ways. While
p e ious s udies ha e explo ed a ious ac o s ha con ibu e o non-pe o ming
loans o ma ion, o he bes o he au ho s’ knowledge, none examined he in e -
ac ion e ec o cos e iciency and bank size and capi alisa ion on NPLs in he li -
e a u e. Mo eo e , li le has been done o es o he possibili y o bo h posi i e
and nega i e e ec s o cos e iciency on NPLs. Fi s , he no el y o his s udy lies
in examining he combined ole o cos e iciency, bank size, and capi alisa ion on
NPL o ma ion, hus p o iding new insigh s in o he nexus be ween e iciency and
non-pe o ming loans. Second, he s udy will es o he possibili y o cos e icien-
cy ha ing bo h posi i e and nega i e e ec s on NPLs h ough he use o a quad a ic
unc ion. Thi d, while o he s udies ha e ocused on gene alising he impac o cos
e iciency on NPLs, his a icle ad ances he cu en li e a u e by examining he
in luence o bank cos e iciency on NPLs ac oss di e en quan iles. Unde s anding
he ela ionship be ween non-pe o ming loans o ma ion and bank cos e iciency
is c ucial o banks and policymake s, as i aids in decision making conce ning ope -
a ional e iciency and isk managemen (Liu & Huang, 2022). Fo example, i banks
can imp o e hei cos e iciency, hey may be be e equipped o mi iga e he isk
o non-pe o ming loans, bene i ing bo h he bank and he b oade economy. The
es o he s udy is o ganised as ollows: li e a u e e iew, da a and me hodology,
empi ical indings and conclusions.
359
Blessing Ka uka, Cal in Mudzingi i, Edson Vengesai, Juniou s Ma i e. Examining he Impac o Bank Cos E iciency
on Non-Pe o ming Loans in a Dolla ised Economy: E idence om Zimbabwe
2. Li e a u e Re iew
2.1 Theo e ical Re iew
Se e al heo ies in li e a u e explain he sou ces o non-pe o ming loans. The ins i-
u ional heo y sugges s ha banks’ non-pe o ming loan (NPL) a es and ope a ion-
al e iciency may be a ec ed by he ins i u ional en i onmen in which hey ope a e
(Adegboye e al., 2020; Webe , 2016). Banks in coun ies wi h poo legal and egula o-
y sys ems may ha e highe non-pe o ming loan (NPL) le els and wo se cos e icien-
cy. The in o ma ion asymme y hypo hesis sugges s ha bank–bo owe in o ma ion
asymme y may aise NPL le els and educe cos e iciency. When bo owe s know
mo e abou hei c edi wo hiness and capaci y o epay loans han banks do, banks
may make subop imal lending decisions ha aise NPL a ios (Kingu e al., 2018).
The discussion abou bank cos e iciency and NPLs nexus is p ima ily based
on Be ge and DeYoung (1997) h ee heo ies: he bad managemen hypo hesis
(BMH), he skimping hypo hesis (SH), and he bad luck hypo hesis (BLH). In
hei e sion, hey p oposed he bad managemen hypo hesis, which s a es ha a
dec ease in cos e iciency causes an inc ease in NPLs. Based on he heo y, mana-
ge ial ine iciencies in loan unde w i ing and moni o ing esul in high NPLs. The
heo y, he e o e, p edic s a nega i e ela ionship be ween NPLs and cos e iciency.
The second hypo hesis p oposed by Be ge and DeYoung (1997) is he skimp-
ing hypo hesis which sugges s a posi i e ela ionship be ween cos e iciency and
NPLs. Due o high-p o i mo i es, manage s alloca e inadequa e esou ces ha im-
p o e bank cos e iciency in he sho un bu comp omise he long- e m quali y
o he loan po olio.
Be ge and DeYoung (1997) also p oposed he bad luck hypo hesis (BLH),
which s ipula es ha he inc ease in NPLs a ises om ex e nal ac o s ha cause
a decline in cos e iciency. Fo example, ex e nal e en s such as egional eces-
sions ha m bo owe s’ epaymen capaci y, esul ing in high de aul a es and is-
ing non-pe o ming loans. Fu he mo e, banks incu high cos s in hei e o s o
eco e de aul ed loans, including expenses o wo kou a angemen s, moni o ing
de aul ed bo owe s, and seizing, main aining, and disposing o asse s (Ahmad &
Bashi , 2013). As a esul , mo e manage ial e o and expense lead o a dec ease in
bank cos e iciency. In b ie , Be ge and DeYoung (1997) concluded ha he BLH
p edic s ha an inc ease in NPLs causes a educ ion in cos e iciency.
2.2 Empi ical Re iew
Close sc u iny o he exis ing empi ical li e a u e e ealed ha NPLs a e indeed a
cause o conce n o banking indus y s abili y (A oi, 2019; Foglia, 2022; Khai i
e al., 2021; Khan e al., 2020; Yi ayaw e al., 2023; Ka uka e al., 2023). In he

360
ISSN 2029-4581 eISSN 2345-0037 O ganiza ions and Ma ke s in Eme ging Economies
US, Phung, Van Vu, and T an (2022) examined he impac o NPLs on bank e -
iciency and he mi iga ing e ec s o bank capi alisa ion. The s udy applied da a
en elopmen analysis (DEA) on panel da a om 1994–2018. Findings sugges ed a
nega i e ela ionship be ween bank e iciency and NPLs. Fu he mo e, hei s udy
also indica ed ha highly capi alised banks could educe he e ec o NPLs on bank
e iciency.
A s udy by Ma aba, Aikaeli and Ki ama (2016) applied an explana o y sequen-
ial esea ch design o examine he linkage be ween cos e iciency and NPLs using
a panel o 9 Tanzanian communi y banks om 2002 o 2014. Da a en elopmen
analysis was employed o es ima e cos e iciency sco es o banks. The Tobi si-
mul aneous equa ion eg ession me hod sugges ed ha bad managemen and bad
luck con ibu ed o NPLs o ma ion in he Tanzanian s udy. Howe e , bad luck
was iden i ied as he p ima y sou ce behind g ow h in NPLs and cos ine iciencies
among banks. The s udy deduced dependen and independen bad luck a iables,
namely, cos e iciency sco e ela i e o he bes bank in he yea and yea ly NPLs,
espec i ely. Howe e , hese wo a iables canno p ecisely accoun o he ex e nal
en i onmen . Bad luck s ems om he ou side en i onmen ; he e o e, he e is a
need o in oduce a mo e app op ia e p oxy o ex e nal e en s. Di e en ly pu , i is
inapp op ia e o p oxy o ex e nal e en s using a bank-le el a iable.
Cascading down o he Zimbabwean con ex , Abel (2018) analysed he ela ion-
ship be ween NPLs and cos e iciency in 11 comme cial banks using bi-annual da a
om 2009–2014. The s udy u ilised DEA unde he cons an e u ns o scale (CRS)
assump ion o examine cos e iciencies. Abel (2018) concluded ha he a e age cos
e iciency o banks du ing 2009–2014 was 81%. This inding ansla es o 19% ine -
iciency in he banking sec o . Fu he mo e, he g ange causali y es esul s poin ed
ou ha cos ine iciency g ange causes NPLs, hus suppo ing he bad managemen
hypo hesis. The esul s a e consis en wi h an Ben hem (2017) in he wo ldwide
and EU comme cial banks da ase . Van Ben hem (2017) concluded ha he bad
managemen hypo hesis was leading in he o e all sample and all sub-samples.
Al hough Abel (2018) made subs an ial p og ess in in es iga ing he ela ion-
ship be ween NPLs and cos e iciency, he s udy lacks se e al essen ial aspec s.
Fi s ly, due o ma ke impe ec ions and o he ma ke ic ions, applying he CRS
assump ion subjec ed he s udy indings o c i icism since CRS only p oduces eli-
able esul s when he e a e no ma ke ic ions, and banks ope a e on he e icien
on ie . This is mos unlikely in de eloping economies’ banking indus ies, such
as Zimbabwe. An imp o emen in he p esen s udy is he applica ion o he a ia-
ble e u ns o scale (VRS) DEA model. Secondly, Abel’s (2018) s udy pa ly co -
e ed he dolla isa ion pe iod, hus ailing o accoun o changes in he beha iou o
a iables o in e es o he en i e dolla isa ion e a. Ou s udy closed he li e a u e
oid by co e ing Zimbabwe’s ull dolla isa ion e a. This is an essen ial s ep in he
361
Blessing Ka uka, Cal in Mudzingi i, Edson Vengesai, Juniou s Ma i e. Examining he Impac o Bank Cos E iciency
on Non-Pe o ming Loans in a Dolla ised Economy: E idence om Zimbabwe
li e a u e as i p o ides a clea pic u e o he ela ionship be ween NPLs and cos
e iciency du ing he o icial dolla isa ion pe iod.
P e ious li e a u e also emphasised he di ec e ec o cos e iciency on NPLs,
ocusing less on he po en ial in e ac ion e ec s be ween cos e iciency and o he
key a iables. As a de ia ion om p e ious s udies, he p esen esea ch en iched
he li e a u e by examining he po en ial in e ac ion e ec be ween cos e iciency,
bank size and capi alisa ion wi h NPLs, which is a new pe spec i e in he li e a u e.
The mo i a ion o examining he in e ac ion e ms is o assess how he changes in
bank size and capi alisa ion when in e ac ing wi h cos e iciency le els in luence
NPLs. Se e al s udies ha e a gued ha size and capi aliza ion in luence bo h NPLs
and cos e iciency, bu he examina ion o he in e ac ion e ec s be ween hese
a iables has emained unde s udied.
3. Da a and Me hodology
3.1 Da a Desc ip ion
The s udy analysed da a om a panel o 13 banks om 2009 o 2017, co e ing Zimba-
bwe’s o icial dolla isa ion e a. The a ionale o selec ing he dolla isa ion e a was due
o a ully unc ional c edi ma ke and a s able cu ency as opposed o he hype in la-
iona y da a ha exis ed be o e and a e ull dolla isa ion. Da a compiled om annual
bank epo s and bank supe ision publica ions we e used in he s udy. The sample
cons i u ed six local banks and se en o eign-owned banks. Table A1 in he Appendix
lis s a iables used in he analysis and expec ed ela ionships as well as he suppo ing
li e a u e. The analysis b anches in o wo s ages. The i s s age ocuses on es ima ing
cos e iciency by banks, and he inal s ep examines i s e ec on NPLs.
3.2 Es ima ing Cos E iciency
The pape assumed an in e media ion app oach whe e banks ans o m inpu s such
as labou , capi al, and deposi s o p oduce a gi en se o ou pu s such as loans and
income. Simila ly, unde he in e media ion app oach, banks se e as a condui
h ough which su plus-spending uni s lend o de ici -spending uni s. The s udy ap-
plied DEA, a non-pa ame ic me hod, assuming a iable e u ns o scale because
he CRS assump ion only p oduces eliable es ima es when banks ope a e on an
op imal scale (Roman e al., 2011). Howe e , such scena ios a e less likely in mos
hi d-wo ld coun ies due o ma ke impe ec ions and o he ic ions in he ma -
ke , such as inancial cons ain s. The e o e, inpu -o ien ed DEA was applied o es-
ima e he cos e iciency sco es o banks assuming VRS.
In he analysis, h ee inpu s, namely labo (x1), capi al (x2) and deposi s (x3)
we e assumed. To al loans (y1) and o al income (y2) we e ea ed as model ou pu s.
362
ISSN 2029-4581 eISSN 2345-0037 O ganiza ions and Ma ke s in Eme ging Economies
The use o inpu s by banks gene a es a cos , and he p ice o each inpu is he cos a-
io o each selec ed inpu . The p ice o deposi s was es ima ed as he a io o o al in-
e es expenses o g oss deposi s (d). Fu he mo e, he p ice o capi al is exp essed
as he a io o ope a ing expenses o ixed asse s (k). Like Rossi, Schwaige and
Winkle (2011) and Abel (2018), he pape used o al asse s da a o p oxy he num-
be o employees due o da a una ailabili y. Thus, he p ice o labou was compu ed
as he a io o labou cos o o al asse s (w). All inpu s and ou pu s a e exp essed
in dolla e ms. Gi en p decision making uni s (DMUs) and ha he j h DMU uses
m inpu s
(
,.,
**
ij mj
xx
)
o p oduce s ou pu s
(
, ..,
ij sj
yy
)
, he cos -e icien
model, based on Kociso a (2014) and Abel (2018), becomes:
min �𝑤𝑤��𝑥𝑥��
∗
�
��� �1�
(1)
subjec o:
�𝑥𝑥��
�
��� 𝜆𝜆��𝑥𝑥
��
∗ ��1,2,3…..,𝑚𝑚
(2)
�𝜆𝜆�
�
��� 𝑦𝑦�� �𝑦𝑦
�� ��1,2,3…..,𝑠𝑠
(3)
�𝜆𝜆�
�
��� �1
(4)
Equa ion (1) speci ies cos e iciency es ima ion using DEA, whe e wiq ep esen s
he inpu p ice o a decision-making uni (DMU)q, x*iq deno es cos minimizing inpu s
o DMUq p o ided ha he inpu s p ice (wiq ) and ou pu (y q) a e speci ied. We de-
ined o e all cos e iciency as ollows:
𝐶𝐶𝐶𝐶�� �∑𝑤𝑤��
�
��� 𝑥𝑥��
∗
∑𝑤𝑤��
�
��� 𝑥𝑥�� �2�
(6)
The nume a o in equa ion (6) is he minimum cos o p oduc ion, while he
denomina o is he obse ed cos o ou pu . In using he DEA me hod, he cos
e iciency a iable (CE) anges om 0 o 1. The e iciency sco e o he mos e i-
cien bank is 1 o 100%, implying ha he bank is ope a ing on he e icien on-
ie . When a bank is loca ed on he e icien on ie (e iciency sco e o 1), i also
means ha i is impossible o expand ou pu wi hou inc easing he inpu s (Řepk-
o á, 2015). On he con a y, a bank wi h an e iciency sco e below 1 is conside ed
ine icien and can a o d o inc ease i s ou pu wi hou necessa ily inc easing i s
363
Blessing Ka uka, Cal in Mudzingi i, Edson Vengesai, Juniou s Ma i e. Examining he Impac o Bank Cos E iciency
on Non-Pe o ming Loans in a Dolla ised Economy: E idence om Zimbabwe
inpu s. In o he wo ds, he bank can achie e he cu en ou pu using ewe inpu s
mix. The s udy es ima ed nine dis inc annual cos on ie s ins ead o a single cos
on ie o he en i e dolla isa ion pe iod. This is so because he bank ha is mos
e icien one yea may no be e icien he ollowing yea .
3.3 Panel Reg ession Models
In he second s age o he analysis, he e ec o cos e iciency on non-pe o ming
loans o ma ion was examined using he andom e ec s eg ession models, which
a e mo e e icien in es ima ing he a iance componen s o he da a han ixed
e ec s and pooled OLS eg ession models (Kan e s, 2022). Guided by he Haus-
man es esul s, he pape i s applied he andom e ec s panel eg ession model
wi hou con ol a iables o unde s and he e ec o cos e iciency on NPLs. This
simple bi a ia e analysis p o ides an in-dep h unde s anding o he ela ionship
be ween cos e iciency and non-pe o ming loans. The ollowing pa simonious
andom e ec panel eg ession model was es ima ed (Khan, Siddique & Sa wa ,
2020):
NPLS୧୲ ൌߚ
଴൅ɘଵCE୧୲ ൅ɂ୧୲
(7)
whe e:
NPLSi = non-pe o ming loans a io o bank i in pe iod
CEi = cos e iciency sco e o bank i in pe iod
β0 = Cons an
εi = E o e m
Fu he o iden i ying he e ec o cos e iciency on NPLs, he pape in es iga ed
whe he he e is a u ning poin whe e NPL s a s o dec ease as cos e iciency in-
c eases. To achie e his, he s udy applied he easible gene alized leas squa es (FGLS)
eg ession model by adding squa ed cos e iciency o equa ion (7) so ha i becomes
a quad a ic model o he o m:
NPLS୧୲ ൌߚ
଴൅ɘଵCE୧୲ ൅ɘଶCE௜௧
ଶ൅ɂ୧୲
(8)
To ind he u ning poin s whe e NPLs will s a dec easing as cos e iciency in-
c eases, he pape di e en ia ed
ω�CE�� �ω�CE��
��0
wi h subjec o CEi o ge :
ω��2ω�CE�� �0
(9)
hen sol ed CEi o iden i y he u ning poin .
To ensu e he esul s a e obus , we es ima ed equa ion (7) using a andom e -
ec s model and a andom e ec s model wi h D iscoll K aay s anda d e o s. Ran-
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ISSN 2029-4581 eISSN 2345-0037 O ganiza ions and Ma ke s in Eme ging Economies
ou , he posi i e ela ionship exis s because banks alloca e ewe unds o loan un-
de w i ing and moni o ing o boos sho - e m p o i abili y, which leads o an in-
c ease in NPLs. These indings suppo he skimping hypo hesis, which s a es ha
high-cos e iciency esul s in ising NPLs.
In addi ion, he s udy obse ed ha he in e ac ion e m be ween cos e iciency
and bank size nega i ely associa es wi h NPLs, and he a iable is s a is ically sig-
ni ican a 1% and 5% in Models 3 and 4. The indings sugges ha NPLs end o
all when la ge-sized banks a e mo e cos -e icien . This is so because banks end o
bene i om economies o scale when hey g ow in size, ha is he asse base, being
con ingen o high e iciency esul ing in educ ion in NPLs. The inding is new
e idence in he li e a u e as mos s udies p ima ily ocused on explo ing he in lu-
ence o bank size and cos e iciency on NPLs in isola ion (Akh e , 2023; Almaska i,
2022; Alnabulsi e al., 2022). The esea ch indings emphasise he impo ance o
bank size in cu bing NPLs. Pu di e en ly, he s udy sugges s ha an inc ease in
asse s base o e s NPLs mi iga ion e ec h ough cos e iciency. Mo e so, he s udy
emphasises ha imp o emen in cos e iciency alone does no cause NPLs o all.
This implies banks need o enhance bank size o elimina e ex eme cos minimisa-
ion beha iou . The inding ha NPLs nega i ely associa e wi h bank size aligns
wi h Anas asiou e al. (2019). Fu he mo e, he s udy documen s ha he in e ac-
ion be ween cos e iciency and bank capi al is s a is ically insigni ican in Models
3 and 4. The indings imply ha bank cos e iciency does no in luence NPLs e en
i bank capi alisa ion is al e ed.
The s udy concluded a nega i e a ilia ion be ween e u n on asse s and non-pe -
o ming loans, and he a iable is signi ican a 1% and 5% in Models 3 and 4. Ac-
co ding o he indings, a 1% inc ease in ROA can cause NPL o dec ease by 1.188%.
The in e p e a ion o his inding is ha banks a e emp ed o issue high- isk loans
ha cause NPLs o ise when he e u n on asse a io dec eases. Mo e so, he s udy
asse s ha p o i able banks a e less likely o ha e a highe NPL a e. The nega i e
ela ionship be ween ROA and NPLs con o ms o he wo k o Khan e al. (2020)
and Obeid (2022). Khan e al. (2020) sugges ed ha p o i abili y has a nega i e
ela ionship wi h NPLs in Pakis an, which is also among de eloping coun ies in
he wo ld.
The eg ession esul s sugges ha he loans o deposi a io has an insigni ican
in luence on NPLs o ma ion in Zimbabwe. The indings con o m o he wo k o
S e ano and Dewi (2022). In a nu shell, he indings sugges ha bank liquidi y du -
ing o mal dolla isa ion in Zimbabwe did no in luence he NPLs ends. Fu he -
mo e, he esul s imply ha policymake s’ e o s o al e na e bank liquidi y do no
signi ican ly in luence g ow h o educ ion in NPLs; hus, he a iable is no i al
when de e mining policies o cu b NPLs.
The indings sugges ha he ex e nal en i onmen (GDP) does no in luence
NPLs in Zimbabwe. The esul s a e iden ical o hose epo ed by Msomi (2022)

371
Blessing Ka uka, Cal in Mudzingi i, Edson Vengesai, Juniou s Ma i e. Examining he Impac o Bank Cos E iciency
on Non-Pe o ming Loans in a Dolla ised Economy: E idence om Zimbabwe
and Apan and İslamoğlu (2019) om s udies conduc ed in wes e n A ican coun-
ies and Tu key’s banking sec o s, espec i ely.
5. Conclusions
The s udy’s objec i e was o examine he e ec o bank cos e iciency on NPLs in
Zimbabwe du ing he dolla isa ion e a. This s udy con ibu es o he exis ing li e a-
u e by examining he in e ac ion e ec o cos e iciency, bank size, and capi aliza-
ion on non-pe o ming loans (NPLs). While p e ious esea ch has explo ed a i-
ous ac o s con ibu ing o NPL o ma ion, his s udy’s no el y lies in in es iga ing
he combined ole o cos e iciency and bank cha ac e is ics. Speci ically, i sheds
ligh on how cos e iciency impac s NPLs ac oss di e en quan iles, p o iding new
insigh s in o he e iciency and non-pe o ming loans nexus.
The cos e iciency sco es we e es ima ed h ough he applica ion o DEA us-
ing yea ly da a gene a ed om a panel o 13 comme cial banks om 2009 o 2017.
The andom e ec s panel eg ession model was u ilised o examine he in luence
o bank cos e iciency on NPLs. A he same ime, Boo s ap quan ile eg ession
was es ima ed o de e mine he e ec o cos e iciency on NPLs ac oss he NPLs
dis ibu ion. The DEA esul s show ha he a e age cos e iciency sco e o he
Zimbabwean banking indus y is 81.36% agains a benchma k o 100%. In addi ion,
he s udy also obse ed ha local banks a e signi ican ly mo e ine icien han o -
eign-owned banks.
The eg ession esul s indica e ha high-cos e iciency inc eases NPLs in Zim-
babwe, and he indings coincide wi h he skimping hypo hesis p oposed by Be ge
and DeYoung (1997). Howe e , he pape sugges s ha NPLs end o all as cos
e iciency inc eases beyond 92.86%. The esul s also show ha a dec ease in ine i-
ciency below 7.14% will lead o a educ ion in NPLs. These indings demons a e
ha he impac o cos e iciency on NPLs is no uni o m. I can ha e a posi i e
e ec up o 92.86% cos e iciency le el and a nega i e e ec beyond ha poin .
This is a no el insigh in he li e a u e, sugges ing ha bo h bad managemen and
skimping hypo heses can coexis in a banking indus y.
In e es ingly, he indings e eal ha he e ec o cos e iciency on NPLs is sig-
ni ican a a highe quan ile, ha is, he 90 h quan ile, implying a s onge ela ion-
ship be ween cos e iciency and NPLs a he uppe end o he NPLs dis ibu ion.
Fu he mo e, he s udy documen s e idence ha he in e ac ion e m be ween cos
e iciency and bank size nega i ely associa es wi h NPLs. In con as , he in e ac-
ion be ween bank capi al and cos e iciency wi h NPLs is insigni ican .
The key ecommenda ion o he s udy is ha banks mus pe iodically moni o
cos –e iciency a ios o a oid cos -cu ing measu es comp omising loan po olio
quali y. The p ac ical signi icance o his s udy lies in i s po en ial o in o m banking
policy and ope a ional s a egies in Zimbabwe and o he simila economies. The
372
ISSN 2029-4581 eISSN 2345-0037 O ganiza ions and Ma ke s in Eme ging Economies
indings highligh he impo ance o cos e iciency in managing NPLs, pa icula ly
in la ge banks. This sugges s ha banks could po en ially educe NPLs by imp o -
ing hei cos e iciency, he eby enhancing hei inancial s abili y and con ibu ing
o he o e all heal h o he economy. Fu he mo e, he s udy’s policy implica ions
sugges ha banks should align hei sho - e m p o i mo i es wi h loan po olio
quali y o p e en an inc ease in NPLs. This could lead o mo e sus ainable banking
p ac ices and con ibu e o economic s abili y.
Limi a ions associa ed wi h his s udy a e ha i ocused only on he o mal dol-
la isa ion pe iod in he Zimbabwean banking indus y. Mo e comp ehensi e esul s
may be ob ained by ex ending he s udy pe iod o include pe iods beyond he o icial
dolla isa ion e a and on egional economies. Fu u e s udies may also a emp o unde -
s and he in e sec ion be ween policy unce ain y, bank cos e iciency and NPLs in
Zimbabwe.
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Appendix
Table A1
Da a Desc ip ion
Va iable Name Desc ip ion Expec ed
ela ionship Suppo ing Li e a u e
Va iables used in Cos DEA es ima ion
Inpu s
x1Labou To al asse s (p oxy o he
numbe o employees)
Rossi, Schwaige and
Winkle , 2011; Abel,
2018
x2Capi al To al ixed asse s Ha sal e al., 2020;
Milenko ić e al., 2022
x3Deposi s To al deposi s E endic, 2017; Sul ana
& Rahman, 2020
Inpu p ices
wP ice o
labou
S a expenses/ o al asse s Abel, 2018; Ma jano ić
e al., 2018; Rossi e
al., 2011
k P ice o
capi al
(To al expenses - labou
expenses)/ o al asse s
Abel, 2018
dP ice o de-
posi s
To al in e es expenses /
o al deposi s
Pa o i & Ma ousek,
2019
Ou pu
y1Loans G oss loans (pe o ming
and non-pe o ming)
Roman e al., 2011
y1To al income Sum o in e es income
and non-in e es income
Be ge & DeYoung,
1997; C e koska e al.,
2021; Fo o a Čiko ić
& Lozić, 2022; Ka im
e al., 2010
Va iables used in panel eg ession
NPL Non-pe o m-
ing loans
Non-pe o ming loans/
To al loans
Jason S e ano & So ia
P ima Dewi, 2022;
Rosenk anz & Lee,
2019; S hembiso
Msomi, 2022
377
Blessing Ka uka, Cal in Mudzingi i, Edson Vengesai, Juniou s Ma i e. Examining he Impac o Bank Cos E iciency
on Non-Pe o ming Loans in a Dolla ised Economy: E idence om Zimbabwe
LTD Loans- o-de-
posi a io
To al loans/ o al deposi + Alnabulsi e al., 2022;
Anas asiou e al.,
2016; Ka uka e al.,
2018; Ribichini, 2018
CE Cos e icien-
cy sco es
Es ima ed using Cos DEA +/- Abel, 2018; Be ge &
DeYoung, 1997; Ma-
aba e al., 2016
ETA Equi y a io To al equi y/ o al asse s +/- Kjose ski & Pe ko ski,
2017; Klein, 2013;
Mak i e al., 2014
ROA Re u n on
asse s
Ne income/ o al asse s - Khan, Siddique & Sa -
wa , 2020; Alnabulsi
e al., 2022;
GDP G oss domes-
ic p oduc
Changes in eal GDP
(Wo ld Bank da ase )
- Alihodžić, 2022;
Ghosh, 2015; Koju e
al., 2018
SIZE Bank size Na u al loga i hm o o al
bank asse s
+/- Anas asiou e al., 2019;
Sahi i & Sahi i, 2021