Onyele, Kingsley Onyekachi; Ikwuagwu, Ebe echi; Umezu ike, Innocen
A icle
Fo mal inancing o small and medium scale en e p ises in
Nige ia: A pa h o economic de elopmen ?
The Jou nal o En ep eneu ial Finance (JEF)
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Sugges ed Ci a ion: Onyele, Kingsley Onyekachi; Ikwuagwu, Ebe echi; Umezu ike, Innocen
(2025) : Fo mal inancing o small and medium scale en e p ises in Nige ia: A pa h o economic
de elopmen ?, The Jou nal o En ep eneu ial Finance (JEF), ISSN 2373-1761, Peppe dine Uni e si y,
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The Jou nal o En ep eneu ial Finance The Jou nal o En ep eneu ial Finance
Volume 27
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A icle 3
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Fo mal Financing o Small and Medium Scale En e p ises in Fo mal Financing o Small and Medium Scale En e p ises in
Nige ia: A Pa h o Economic De elopmen ? Nige ia: A Pa h o Economic De elopmen ?
Kingsley Onyekachi Onyele
Rhema Uni e si y Nige ia
Ebe echi Ikwuagwu
Michael Okpa a Uni e si y o Ag icul u e, Umudike, Abia S a e, Nige ia
Innocen Umezu ike
Michael Okpa a Uni e si y o Ag icul u e, Umudike, Abia S a e, Nige ia
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Managemen Commons
Recommended Ci a ion Recommended Ci a ion
Onyele, Kingsley Onyekachi; Ikwuagwu, Ebe echi; and Umezu ike, Innocen (2025) "Fo mal Financing o
Small and Medium Scale En e p ises in Nige ia: A Pa h o Economic De elopmen ?,"
The Jou nal o
En ep eneu ial Finance
: Vol. 27: Iss. 1.
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Fo mal Financing o Small and Medium Scale En e p ises in Nige ia: A Pa h o Fo mal Financing o Small and Medium Scale En e p ises in Nige ia: A Pa h o
Economic De elopmen ? Economic De elopmen ?
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The Jou nal o En ep eneu ial Finance
Published by Peppe dine Digi al Commons, 2025 Ikwuagwu e al.: Fo mal Financing o SMEs
Fo mal Financing o Small and Medium Scale En e p ises in Nige ia: A Pa h o Economic
De elopmen ?
Ebe echi Ikwuagwu
Michael Okpa a Uni e si y o Ag icul u e, Umudike, Abia S a e, Nige ia
[email p o ec ed]
Kingsley Onyele
Rhema Uni e si y Nige ia, Aba, Abia S a e, Nige ia
[email p o ec ed]
Innocen Umezu ike
Michael Okpa a Uni e si y o Ag icul u e, Umudike, Abia S a e, Nige ia
[email p o ec ed]
Abs ac :
This in es iga ion assessed he in luence o o mal inancing o small and medium-sized en e p ises
(SMEs) on he economic ad ancemen o Nige ia, u ilising annual ime se ies da a anging om 1992 o 2022.
Employing he Cobb-Douglas amewo k, con ol a iables, including capi al o ma ion and labou , which could
in luence economic de elopmen , we e inco po a ed in o he empi ical model o mi iga e bias. Following ini ial
es s o s a iona i y, i was de e mined ha all a iables achie ed s a iona i y upon he i s di e ence, a inding
ha alida ed he Vec o E o Co ec ion Mechanism (VECM) applica ion. The analysis e ealed ha he c edi
ex ended o SMEs by comme cial banks and he loans p o ided by mic o inance banks exhibi ed a nega i e and
signi ican in luence on economic de elopmen , as measu ed by GDP pe capi a, in bo h he long and sho e m.
The nega i e coe icien s associa ed wi h he c edi om comme cial banks o SMEs and he loans om
mic o inance banks indica e ha hese inancial ins i u ions ha e no ye ca alysed he equisi e leap in Nige ia's
economic de elopmen , p obably due o he nega i e e ec s o uns able in e es a es on lending. Bo h g oss
capi al o ma ion and labou demons a ed a signi ican impac on GDP pe capi a; howe e , he e ec o labou
was ound o be nega i e. Consequen ly, i was concluded ha inancing o SMEs h ough comme cial banks’
c edi and mic o inance bank loans had a nega i e and signi ican e ec on Nige ia's economic de elopmen . The
s udy ecommended ha policymake s and egula o y bodies should empowe and acili a e o mal inancial
ins i u ions, such as comme cial banks and mic o inance banks, o ex end inancial se ices o SMEs, he eby
enhancing hei p oduc i i y.
Keywo ds:
SMEs inancing; comme cial banks; mic o inance banks, economic de elopmen ; VECM
1
Onyele e al.: Fo mal Financing o SMEs in Nige ia: A Pa h o Economic De elopmen ?Published by Peppe dine Digi al Commons, 2025
The Jou nal o En ep eneu ial Finance
Published by Peppe dine Digi al Commons, 2025 Ikwuagwu e al.: Fo mal Financing o SMEs
1. In oduc ion
The signi icance o small and medium en e p ises (SMEs) in he ealisa ion o economic
de elopmen , pa icula ly wi hin a de eloping na ion such as Nige ia, canno be o e s a ed. SMEs se e
as bo h he ounda ion and he essen ial building blocks in he pu sui o subs an ial and sus ainable
economic g ow h and de elopmen . They unc ion as he p ima y d i ing o ce behind he achie emen
o indus ial ad ancemen . This is undamen ally a ibu able o hei conside able po en ial in acili a ing
he di e si ica ion and expansion o indus ial p oduc ion, and in ul illing he undamen al objec i es o
de elopmen . In he con ex o a sus ainable economy, SMEs ha e been emphasised as ins umen al in
os e ing a a ou able economic u na ound and in complemen ing he e o s o he p e ailing medium
and la ge-scale indus ies (Ba ancea e al., 2022). The acknowledgemen o he pi o al oles o SMEs as
ca alys s and engines o g ow h has led o an inc eased ocus on specialised educa ion ega ding he
me hodologies and s a egies necessa y o es ablish and main ain a genuinely iable p i a e sec o
p edominan ly cha ac e ised by SMEs. The economic con ibu ions o hese en e p ises a e e iden in
hei capaci y o mobilise do man inancial esou ces, conse e o eign exchange, u ilise local aw
ma e ials, se e as specialised supplie s o la ge co po a ions, enhance a ie y and choice o consume s,
mi iga e monopolis ic endencies, p o ide a sou ce o inno a ion, nu u e new indus ies, and, mos
impo an ly, c ea e employmen oppo uni ies (Olowooke e e al., 2021).
The heo e ical amewo k ha connec s inance and economic g ow h, as posi ed by McKinnon
(1973) and Shaw (1973), unde sco es he impe a i e o inancial libe alisa ion aimed a augmen ing
changes in ac ual sa ings, which subsequen ly diminish in e es a es and enhance in es men and capi al
o ma ion (Olo un emi & Ganiyu, 2016). Consequen ly, i SMEs can success ully a ac a g ea e
p opo ion o sa ings o bols e hei capi al base a a low-income le el, whe e challenges such as low
p opensi y o sa e and in o ma ion asymme y p e ail, a signi ican numbe o SMEs in de eloping
na ions would gene a e su icien income o mee hei basic needs, as he majo i y o hei ea nings
me ely su ice o sa is y physiological equi emen s (Onyeiwu e al., 2020). Schumpe e (1973)
unde sco es he c i ical impo ance o c edi o small en e p ises in inancing inno a ions, he eby
p omo ing ou pu g ow h. This elucida es he necessi y o sus ained c edi suppo o SMEs o a ain
hei ull po en ial. Ne e heless, his asse ion may no hold o nume ous de eloping na ions, including
Nige ia, due o he asymme ic inancial oppo uni ies con on ing small business ope a o s.
Nige ia’s go e nmen has been keen on de eloping SMEs; as such, many mic o inance agencies
ha e been se up o p omo e he g ow h o SMEs in Nige ia. Acco ding o Ikpo e al. (2017), in 1962,
he Nige ian Indus ial De elopmen Bank (NIDB) was es ablished, and he Ru al Banking Ini ia i e
(RBI) was se up in 1977. Also se up was he Ag icul u al C edi Gua an ee Scheme Fund (ACGSF), a
p og am ha gua an ees c edi loans o a me s om deposi money banks (DMBs) o comme cial banks
and he Nige ian Ag icul u al Coope a i e Bank o enhance lending o ag icul u e and SMEs. To cushion
o he nega i e impac o s uc u al adjus men p og ams in he mid-1980s, he go e nmen se up he
Na ional Economic Recons uc ion Fund (NERFUND) o gi e SMEs a concessiona y long- e m loan
o i e o en (5–10) yea s (Ogujiuba e al., 2013). To u he boos he sou ce o inance o SMEs, he
go e nmen in 1991 se up a communi y banking scheme o enhance u al de elopmen and o p o ide
s a -up capi al o smallholde s. Also, he people’s bank and Family Economic Ad ancemen P og amme
(FEAP) we e es ablished in 1997. In 2002, he go e nmen me ged he NERFUND and NIDB wi h he
Bank o Indus y o p o ide loans a an in e es a e o 10 pe cen o he indus ial sec o and SMEs.
Many o he in e en ion schemes we e es ablished o p o ide long- e m o specialised unds o
he p omo ion o SMEs in Nige ia. Acco ding o Tonuchi e al. (2021), hese include he Mic o inance
Ini ia i e (MFI) se up in 2005. In 2010, CBN, in he ques o p o ide adequa e unds o SMEs, se up
₦200 billion in in e en ion unds o inance SMEs ha engaged in manu ac u ing. Also, ₦300 billion in
ai line and o -g id powe unds we e ea ma ked o suppo SME clus e s. O ecen , he es ablishmen
2The Jou nal o En ep eneu ial Finance, Vol. 27, Iss. 1 [2025], A . 3
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DOI: 10.57229/2373-1761.1508
The Jou nal o En ep eneu ial Finance
Published by Peppe dine Digi al Commons, 2025 Ikwuagwu e al.: Fo mal Financing o SMEs
o NIRSAL Mic o- inance Bank o SMEs is a majo boos e o SMEs ac i i ies in he coun y. Howe e ,
hese p ojec s we e cha ac e ised by non- epaymen o loans and ailu e o achie e he s a ed objec i es.
This is because he policies we e os e ed by he go e nmen in he o m o c edi alloca ion, subsidies,
and in e es ceilings. These may ha e led o he de e io a ion o c edi a ailable o SMEs in Nige ia. To
cushion he e ec o he COVID-19 pandemic ha bede illed he wo ld in 2020, which by ex ension has
caused global ha dship o SMEs, he ede al go e nmen , h ough he CBN, in oduced an N50 billion
Ta ge ed C edi Facili y (TCF) as a s imulus package o suppo households and mic o, small, and
medium en e p ises (MSMEs) ha a e a ec ed by he co ona i us pandemic.
I has been obse ed ha comme cial banks, along wi h he p e iously es ablished me chan
banks ha main ained liquidi y le els su passing egula o y equi emen s, ha e exhibi ed a hesi ance o
inance SMEs (Masa o & T oilo, 2015). Al hough mic o inance ins i u ions (MFIs) ha e expe ienced
signi ican expansion in nume ous coun ies, he magni ude o hei c edi o e ings emains cons ained,
ende ing hei suppo insu icien o many medium-scale p ojec s. Fu he mo e, he in e es a es
associa ed wi h mic o-c edi s a e conside ably ele a ed, a ibu able o subs an ial adminis a i e expenses
conce ning hei ope a ional scale (Onyele & Onyekachi-Onyele, 2020). Repo s indica e ha SMEs
con ibu e app oxima ely 75 pe cen o all en ep eneu ial ac i i ies cons i u ing Nige ia’s g oss domes ic
p oduc , wi h 21 pe cen a ibu ed o mic o-en e p ises and 4 pe cen associa ed wi h la ge complex
o ganiza ions. Addi ionally, Nige ia is ecognised o i s subs an ial en ep eneu ial dominance due o i s
capaci y o consolida e skilled and semi-skilled labou (Olaniyi & Adekanmbi, 2022).
O e he yea s, nume ous s udies ha e been conduc ed o assess he in luence o SME inancing
on economic g ow h and de elopmen wi hin Nige ia. Howe e , many o hese in es iga ions u ilised
p ima y da a, which, a bes , e lec he pe spec i es o esponden s ye su e om conside able
inconsis encies in es ima ion me hodologies. Mo eo e , he majo i y o hese s udies p edominan ly
concen a ed on he e ec s o impac s o SME inancing and economic g ow h wi hou adequa ely
add essing he in luence o SME inancing on componen s o economic de elopmen , such as pe capi a
income and human de elopmen . Fu he mo e, p io s udies la gely neglec ed o asce ain he p esence
o absence o causali y be ween hese a iables, which is equally c ucial. Consequen ly, he objec i e o
his s udy is o empi ically analyse he impac o SME inancing on economic de elopmen in Nige ia
and o delinea e he na u e o causali y be ween hese a iables. This s udy u ilised annual ime se ies da a
om 1992 o 2022. Fo u u e esea che s, his s udy aims o ca alyse u he in es iga ion, pa icula ly
in Nige ia, whe e SMEs emain ela i ely unde - esea ched. A he indi idual le el, his s udy enhanced
unde s anding and app ecia ion o he signi icance o de eloping human capi al in pu sui o economic
de elopmen . Fo he go e nmen , i p o ided a amewo k conduci e o policy o mula ion and
implemen a ion. Abo e all, his s udy will con ibu e o he exis ing body o li e a u e and add ess he
exis ing gaps in knowledge. The subsequen sec ions o his s udy a e o ganised as ollows: Sec ion wo
e iewed he pe inen li e a u e, sec ion h ee elabo a ed on he me hodology, sec ion ou p esen ed
da a analysis and in e p e a ion o indings, and sec ion i e o e ed conclusions and ecommenda ions.
2. Re iew o Rela ed Li e a u e
2.1.
Concep ual amewo k
Small en e p ises a e ecognised o hei enhanced adap abili y in he ace o challenging and
e ol ing ci cums ances, p ima ily due o hei o en minimal capi al in ensi y, which enables hem o
modi y p oduc lines and inpu s a a ela i ely low cos . The sub- lexibili y, adap abili y o he sec o , and
egene a i e cha ac e is ics ha e ende ed i a ocal poin o he indus ial de elopmen s a egies o
nume ous na ions, pa icula ly in de eloping egions (Wo ld Bank, 2019). These en e p ises se e as an
3
Onyele e al.: Fo mal Financing o SMEs in Nige ia: A Pa h o Economic De elopmen ?Published by Peppe dine Digi al Commons, 2025
The Jou nal o En ep eneu ial Finance
Published by Peppe dine Digi al Commons, 2025 Ikwuagwu e al.: Fo mal Financing o SMEs
e ec i e mechanism o os e indigenous en ep eneu ship, augmen employmen oppo uni ies pe uni
o expendi u e, and acili a e local echnological ad ancemen . Thei ex ensi e dis ibu ion p o ides a
p o icien me hod o mi iga ing u al-u ban mig a ion and op imising esou ce u ilisa ion (Ogujiuba e
al., 2013). Addi ionally, hey play a i al ole in s eng hening in e -indus ial connec ions by p oducing
in e media e goods u ilised in la ge-scale indus ies.
The lack o access o ela i ely a o dable and e icien inancial sou ces has been iden i ied as he
p ima y impedimen o hei con ibu ion o economic ad ancemen (Ochonogo , 2020). A p e alen
conce n is ha he banking sys em wi hin his sec o , which is expec ed o be he p incipal inancie o
SMEs, is inadequa ely suppo ing new economic ini ia i es, pa icula ly wi h he expansion o SMEs and
he ag icul u al sec o . I has been obse ed ha comme cial and p e iously es ablished me chan banks,
which main ained liquidi y le els exceeding egula o y equi emen s, ha e exhibi ed eluc ance in
inancing SMEs. Al hough mic o inance ins i u ions (MFIs) ha e expe ienced igo ous g ow h in se e al
coun ies, he magni ude o hei c edi emains cons ained, ende ing hei suppo insu icien o
nume ous medium-sized p ojec s. Fu he mo e, he in e es a es associa ed wi h mic o-c edi s a e
exceedingly high due o signi ican adminis a i e expenses ela i e o hei ope a ional scale. The p ima y
ocus o his s udy a ises om he obse a ion ha p op ie o s o small-scale en e p ises lack adequa e
inancing o sus ain hei business ope a ions. This p edicamen can be a ibu ed o he low le els o
income. I is a well-es ablished ac ha SMEs encoun e inancial obs acles.
Figu e 1. Concep ual F amewo k
The esea che s’ concep ual amewo k is illus a ed in Figu e 1. Nume ous s udies ha e
iden i ied inancial cons ain s as he p edominan ba ie o he g ow h o SMEs and economic
de elopmen in de eloping na ions, including Nige ia. Fo example, Adelaja (2003) con ended ha he
absence o access o ins i u ional inance has consis en ly cons i u ed a pe asi e issue o SME
de elopmen in Nige ia. The challenge o inancing SMEs has ga ne ed subs an ial esea ch a en ion
om schola s. Thei indings e eal ou ecu ing issues in SME inancing: he cos o capi al, isk,
inapp op ia e e ms associa ed wi h bank loans, and a lack o equi y capi al. O e he yea s, he
go e nmen has enac ed a ious policies and in oduced schemes aimed a inancing SMEs. Ne e heless,
i is conce ning o obse e ha SMEs con inue o ace signi ican unding sho ages, and he inancing
challenges pe sis . Mahmoud (2005) has concluded ha hese inancial di icul ies es ic he
SMEs Financing
Fo mal C edi
Ex ension
Comme cial
Bank’s
C edi
Mic o inance
Bank’s
C edi
Economic
De elopmen
4The Jou nal o En ep eneu ial Finance, Vol. 27, Iss. 1 [2025], A . 3
h ps://digi alcommons.peppe dine.edu/je / ol27/iss1/3
DOI: 10.57229/2373-1761.1508
The Jou nal o En ep eneu ial Finance
Published by Peppe dine Digi al Commons, 2025 Ikwuagwu e al.: Fo mal Financing o SMEs
de elopmen al po en ial o SMEs wi hin he economy. The e exis s conside able doub ega ding he
capaci y o SMEs o con ibu e o economic de elopmen in ligh o hei limi ed access o unds.
2.2.
Fo mal SMEs inancing in Nige ia: s ylized ac s
The declining a e o unding o SMEs con inues o be a signi ican cons ain ha impedes i s
po en ial con ibu ion o economic g ow h and de elopmen . Speci ically, he e exis ou p incipal
challenges impac ing SMEs in Nige ia, namely, an inhospi able business en i onmen , inadequa e
unding, de icien manage ial compe encies, and limi ed access o con empo a y echnology. The e is a
conspicuous eliance by SMEs on inancial ins i u ions o he p ocu emen o unding, business
expansion, and he acquisi ion o he la es echnologies necessa y o main ain compe i i eness and os e
economic g ow h. Addi ional cons ain s a ise om in as uc u al inadequacies, excessi e axa ion, and
an un a ou able mac oeconomic clima e (Gumel & Ba dai, 2021). Among hese challenges, he sca ci y
o inancial esou ces occupies a pi o al ole.
Acco ding o he O ganisa ion o Economic Co-ope a ion and De elopmen (OECD), he e
exis s a p o ound his o ical con ex ega ding communi y inance, mic o inance, and go e nmen -
suppo ed SME inancing a angemen s aimed a deli e ing inancial se ices o he SME sec o
independen o he comme cial banking amewo k (OECD, 2018). Ne e heless, he pe o mance o
hese ini ia i es emains ques ionable. The c i icism su ounding his pe o mance has p omp ed he
go e nmen o enhance he inancial sec o h ough i s long- e m s a egic amewo k: The Financial
Sys em S a egy (Ohama a, 2017). The inancing o SMEs in Nige ia is signi ican ly hinde ed by a dea h
o da a on SME ope a ions, egula o y amewo ks, he lack o c edible colla e al, and incomple e c edi
his o ies. Policies ega ding SMEs encoun e pe sis en challenges due o inadequa e da a necessa y o
comp ehend he issues and ope a ions o exis ing go e nmen ini ia i es a ge ing SMEs (Onyeiwu e al.,
2021). The cu en c edi in o ma ion sys em ails o co espond wi h he equi emen s o he SME
sec o . To e ec ua e a ans o ma i e na a i e, he Nige ian go e nmen and he o ganised p i a e sec o
mus es ablish a pla o m whe ein p i a ely owned c edi bu eaus, alongside he C edi Risk Managemen
Sys em (CRMS), can adequa ely encompass he SME subsec o .
The Cen al Bank o Nige ia (CBN) has in ensi ied p essu e on inancial ins i u ions, pa icula ly
comme cial banks, o enhance hei lending capaci ies o SMEs (Olowooke e e al., 2021). The heigh ened
isk coupled wi h he p e-exis ing incidence o loan de aul s dissuades banks om ex ending c edi o
small-scale en e p ises. Banks ha e shown a p e e ence o incu ing penal ies o he CBN a he han
disbu sing loans o hese SMEs (Mo di e al., 2014). They end o ocus on a ge sec o s whe e in e es
yields a mo e subs an ial ma gin, accompanied by a commensu a e le el o isk cha ac e ised by global
economic shocks. P e ious endea ou s o p omo e SME inancing ha e yielded mixed ou comes;
howe e , he Nige ian au ho i ies pe sis in ad ancing new ini ia i es and policies o his sec o .
Figu e 2 illus a es he ends in c edi alloca ed by comme cial banks o SMEs and loans
dispensed by mic o inance banks in Nige ia om 1992 o 2022. The igu e indica es ha c edi om
comme cial banks o SMEs su passed ha o mic o inance loans be ween 1992 and 2007. Ne e heless,
om 2008 o 2022, he loans p o ided by mic o inance banks began o ise signi ican ly, o e aking he
c edi ex ended by comme cial banks o SMEs. The ab up inc ease in mic o inance loans in 2008 can
be a ibu ed o he Financial Inclusion Task o ce, which was o icially launched in Feb ua y 2005 o
o e see p og ess on inancial inclusion and o make app op ia e ecommenda ions, he eby enhancing
he ope a ional capabili ies o mic o inance banks (Kama & Adigun, 2013). The subsequen inc ease in
loans om mic o inance banks in 2012 is asc ibed o he Cen al Bank o Nige ia's (CBN) endo semen
o he Na ional Financial Inclusion S a egy (NFIS) in 2012 (CBN, 2018).
5
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Figu e 2. T end SMEs inancing in Nige ia
2.3.
Economic de elopmen in Nige ia
The expansion in he p oduc ion o goods and se ices cons i u es a undamen al de e minan o
economic pe o mance. Dis ibu ing o al p oduc ion ac oss he popula ion illus a es he ex en o which
a na ion's o al ou pu can be alloca ed among i s ci izens. The inc ease in eal GDP pe capi a e lec s
he a e o income g ow h pe indi idual wi hin he popula ion. As a singula composi e measu e, i se es
as a po en summa y indica o o economic de elopmen (Wo ld Bank, 2018). Economic de elopmen
pe ains o he augmen a ion in he numbe o indi iduals wi hin a na ion's popula ion, cha ac e ised by
sus ained g ow h ansi ioning om a udimen a y, low-income economy o a sophis ica ed, high-income
economy. I s scope encompasses he p ocesses and policies h ough which a na ion enhances he
economic, poli ical, and social wel a e o i s populace. Economic de elopmen in Nige ia ep esen s a
comp ehensi e concep ha en ails he enhancemen o he quali y o li e and well-being o he na ion’s
ci izens. Se e al ac o s in luencing Nige ia's economic de elopmen include:
a) The oil sec o : A p incipal con ibu o o Nige ia's GDP;
b) Ag icul u e: A co ne s one o Nige ia's economy;
c) Se ices sec o : Encompassing elecommunica ions and inancial echnology;
d) Manu ac u ing and indus ial de elopmen : A c ucial elemen wi hin Nige ia's economic
amewo k;
e) Poli ical s abili y and go e nance: An essen ial ac o in luencing Nige ia's economic p og ess.
Despi e possessing he la ges economy and popula ion on he A ican con inen , Nige ia
p esen s limi ed oppo uni ies o a subs an ial po ion o i s ci izen y. Indi iduals bo n in Nige ia in 2020
a e an icipa ed o possess a p oduc i i y le el ha is only 36% o hei po en ial, con ingen upon ull
access o educa ion and heal hca e, esul ing in he 7 h lowes human capi al index globally. Insu icien
job c ea ion and en ep eneu ial a enues hinde he in eg a ion o he 3.5 million Nige ians en e ing he
labou ma ke annually, compelling nume ous wo ke s o seek employmen ab oad o imp o ed
p ospec s (Ikwuagwu & Onyele, 2023). The po e y a e is p ojec ed o ha e escala ed o 38.9% in 2023,
wi h an es ima ed 87 million Nige ians subsis ing below he po e y h eshold— ep esen ing he wo ld’s
second-la ges impo e ished popula ion, a e India.
0.00
50,000.00
100,000.00
150,000.00
200,000.00
250,000.00
300,000.00
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
2011
2012
2013
2014
2015
2016
2017
2018
2019
2020
2021
2022
Comme cial Banks Mic o inance Banks
6The Jou nal o En ep eneu ial Finance, Vol. 27, Iss. 1 [2025], A . 3
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Mo eo e , Ezeaku e al. (2017) assessed he in luence o SME inancing on he g ow h o he
manu ac u ing sec o in Nige ia, u ilising annualised da a om 1981 o 2014. A coin eg a ing ela ionship
was iden i ied h ough he Engel and G ange esidual-based app oach, which p o ided e idence o a
long- un ela ionship be ween SME c edi and he g ow h o manu ac u ing ou pu in Nige ia. The
indings indica ed ha SME inancing has posi i ely in luenced he g ow h o he manu ac u ing sec o .
In a ela ed s udy, Oleka e al. (2014) e alua ed he ex en o which mic o inance banks ha e
acili a ed he inancing o SMEs in Nige ia. This s udy encompassed a decade om 2003 o 2013. The
da a employed consis ed o bo h p ima y and seconda y in o ma ion, collec ed ia ques ionnai es and
annual epo s om 300 andomly selec ed small and medium-scale en e p ises ha had accessed unds
om mic o inance banks in Nige ia. The esul s p o ided compelling e idence ha access o
mic o inance signi ican ly bols e ed he g ow h o SMEs in Nige ia.
Mo eo e , Olowe e al. (2013) examined he in luence o mic o inance on he g ow h o SMEs
wi hin he Nige ian con ex . A simple andom sampling me hodology was employed o selec a o al o
82 ope a o s o SMEs, which cons i u ed ou sample size. The analysis o he da a was conduc ed using
he Pea son co ela ion coe icien and mul iple eg ession analysis. The indings om his s udy
indica ed ha he inancial se ices acqui ed om MFBs exe ed a posi i e and signi ican in luence on
he g ow h o SMEs in Nige ia. Fu he mo e, he esul s indica ed ha ele a ed in e es a es, he
equi emen o colla e al secu i y, and he equency o loan epaymen ad e sely a ec ed he expansion
o SMEs in Nige ia.
2.6.
Gap in Empi ical Li e a u e
The culmina ion o a ious empi ical and heo e ical discou ses ega ding he impac o o mal
inancing on he economic de elopmen o SMEs in Nige ia p esen s a di e se a ay o ou comes as
epo ed by di e en schola s in he ield. The discou se su ounding he in luence ha small and
medium-scale en e p ises ha e on economic g ow h and de elopmen , pa icula ly as acili a ed by
inancing om comme cial banks and mic o inance ins i u ions, emains inconclusi e. I is no ewo hy
ha he dispa a e esul s eme ging om hese a ious discussions can be a ibu ed o he p oxy
indica o s and da a u ilised in he analysis o he s udy ou comes. The lending a e, capi al o ma ion, and
labou o ce a e essen ial componen s o his discussion abou small and medium-scale en e p ises, gi en
hei subs an ial cos s and c i ical impo ance o he sus ainabili y o SMEs in Nige ia. The lending a e
e lec s he cos s associa ed wi h o mal c edi access o businesses. Capi al o ma ion signi ies he
pi o al ole o in as uc u e in Nige ia, which is i al o he ope a ional success o nume ous small
en e p ises. The a o emen ioned c i ical a iables ha e been excluded om he esea ch models p oposed
by p eceding s udies. The p esen esea ch endea ou s o add ess his gap by inco po a ing he omi ed
a iables in o he esea ch model o elucida e he ela ionships among he a iables o in e es . The
exis ing gap subs an ia es he necessi y o u he inqui y in o his subjec . Consequen ly, he e is an
impe a i e o unde ake his esea ch o enhance he dep h o li e a u e on his opic and po en ially
in luence economic decision-making in his domain posi i ely.
3. Resea ch Me hodology
This sec ion ea i ms he esea ch me hodology employed in he s udy h ough a concise
exposi ion o he esea ch design, da a collec ion ins umen s, he da a collec ion p ocedu e, and he da a
analysis echnique. Fo his in es iga ion, he selec ed esea ch design is he ex pos ac o esea ch design.
This chosen design deno es a sys ema ic app oach whe eby he esea che is unable o manipula e he
da a owing o i s p io occu ence.
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The selec ion o seconda y da a aligns wi h he choice o in o ma ion in ligh o empo al
cons ain s. Mo eo e , his op ion was a ou ed o e o he po en ial al e na i es due o i s accessibili y
and eliabili y, which a e u he subs an ia ed by he e i iable sou ces om which he da a was de i ed.
The da a o his s udy we e de i ed om seconda y sou ces encompassing he pe iod om 1992 o
2022, speci ically ex ac ed om he CBN S a is ical Bulle in and he Wo ld De elopmen Indica o s
(WDI). The collec ed seconda y da a encompasses a ious economic indica o s, including economic
de elopmen quan i ied by GDP pe capi a, as well as comme cial bank c edi o SMEs and mic o inance
banks, which se e o e alua e he inancing o SMEs, in addi ion o g oss capi al o ma ion and labou
o ce s a is ics, which unc ion as con ol a iables. The selec ion o seconda y da a is p edica ed upon
he unde s anding ha such da a canno be p ocu ed ia p ima y sou ces due o he necessi y o
ex ensi e empo al collec ion.
Since he da a was sou ced om CBN and WDI, which a e ins i u ions o high epu a ion, i is
assumed ha he da a used we e colla ed by well- ained and educa ed pe sonnel ha ensu ed da a quali y
s anda ds as published on hei espec i e websi es. As such, he issue o po en ial limi a ions such as
da a accu acy, comple eness, and he impac o ex e nal ac o s o e he long pe iod we e well managed.
The da a used o he s udy cap u ed SMEs in all economic sec o s in Nige ia. Hence, he popula ion
a he han he sample was used o he analysis.
This esea ch is undamen ally based on he Cobb-Douglas p oduc ion unc ion. The Cobb-
Douglas p oduc ion unc ion ep esen s a speci ic unc ional o m o he p oduc ion unc ion and is
ex ensi ely u ilised o depic he echnological ela ionship be ween mul iple inpu s, pa icula ly physical
capi al and labou , and he esul an ou pu ha can be gene a ed om hese inpu s. O e he pas se e al
decades, nume ous schola s ha e employed hese models o explo e a ious indica o s ha con ibu e o
economic g ow h and de elopmen . Mo eo e , adi ional elemen s such as capi al and labou ha e
expe ienced signi ican ad ancemen s in he academic li e a u e as a consequence o his e olu ion
(B own, 2017). In i s mos con en ional o m conce ning he p oduc ion o a singula good u ilising wo
ac o s, he unc ion is exp essed by equa ion (1):
𝑌 =𝑓(𝐿,𝐾)=𝐴𝐿𝛽𝐾𝛼 (1)
Y = o al p oduc ion ( he eal alue o all goods p oduced in a yea )
L = labou inpu
K = capi al inpu (a measu e o all machine y, equipmen , and buildings; he alue o capi al inpu di ided
by he p ice o capi al)
A = o al ac o p oduc i i y
0< 𝛼 < 1 and 0< 𝛽 < 1 a e he ou pu elas ici ies o capi al and labo , espec i ely.
Capi al and labou a e he wo " ac o s o p oduc ion" o he Cobb–Douglas p oduc ion
unc ion. The choice o his amewo k is owed o i s simplici y in applica ion and he a ailabili y o ime
se ies da a in Nige ia.
In line wi h he Cobb-Douglas p oduc ion amewo k, Onyeiwu e al. (2020) speci ied he model
ep esen ed by equa ion (2):
𝐿𝐴𝑆𝐺𝐷𝑃𝑡= 𝛽0+ 𝛽1𝐺𝐶𝐹+ 𝛽2𝐶𝑆𝑀𝐸+𝛽3𝐿𝑅+𝛽4𝐸𝐷 (2)
Whe e: LASGDP =Na u al Loga i hm o he agg ega e o SME con ibu ion o G oss Domes ic
P oduc GCF = G oss capi al o ma ion. CBSMEs = Comme cial Bank C edi o SMEs. LR = Lending
Ra e. ED = Elec ici y Dis ibu ion.
This s udy modi ied equa ion (2) o cap u e a mo e elabo a e model o economic de elopmen
and SMEs inancing wi h con ol a iables (LNGCF and LNLAB) as speci ied in equa ion (3).
14The Jou nal o En ep eneu ial Finance, Vol. 27, Iss. 1 [2025], A . 3
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𝐿𝑁𝐺𝐷𝑃𝑃𝐶𝑡= 𝛽0+ 𝛽1𝐿𝑁𝐶𝐵𝑆𝑀𝐸𝑠 + 𝛽2𝐿𝑁𝑀𝐵𝐿+𝛽3𝐿𝑁𝐼𝑁𝑇+𝛽4𝐿𝑁𝐺𝐶𝐹+𝛽5𝐿𝑁𝐿𝐴𝐵+µ (3)
Whe e: LNGDPPC is he na u al log o GDP pe capi a; LNCBSMEs measu e he na u al log o
c edi o SMEs by comme cial banks; LNMBL is agg ega e loans ob ained om mic o inance banks;
LNINT indica es he na u al log o he lending in e es a e; LNGCF deno es he na u al log o g oss
capi al o ma ion, while LNLAB measu es he na u al log o labou .
Acco ding o he economic p io i o he signs o pa ame e s, i is expec ed ha 𝛽1,𝛽2,𝛽4,𝑎𝑛𝑑 𝛽5>
0, while 𝛽3 < 0.
The model a icula ed in equa ion (3) may be ep esen ed in he ec o e o co ec ion model
(VECM) amewo k, whe ein LNGDPPC may no ins an aneously e e o i s long- un equilib ium
le els, he eby cap u ing he a e o adjus men be ween he sho - un and long- un le els wi hin he
e o co ec ion equa ion as delinea ed in equa ion (4), whe e ∆ signi ies he change in he dependen
a iable LNGDPPC alongside he independen a iables LNCBSMEs, LNMBL, LNINT, LNGCF, and
LNLAB.
𝐿𝑁𝐺𝐷𝑃𝑃𝐶𝑡= 𝛽0+ ∑𝛽1𝛥𝐿𝑁𝐺𝐷𝑃𝑃𝐶𝑡−1 +
𝑝
𝑖=1 ∑𝛽2𝛥𝐿𝑁𝐶𝐵𝑆𝑀𝐸𝑠𝑡−1 +
𝑝
𝑖=1 ∑𝛽3𝛥𝐿𝑁𝑀𝐵𝐿𝑡−1 +
𝑝
𝑖=1 ∑𝛽4𝛥𝐿𝑁𝐼𝑁𝑇𝑡−1
𝑝
𝑖=1
+∑𝛽5𝛥𝐿𝑁𝐺𝐶𝐹𝑡−1 +
𝑝
𝑖=1 ∑𝛽6𝛥𝐿𝑁𝐿𝐴𝐵𝑡−1 +
𝑝
𝑖=1 𝛽7𝐸𝐶𝑇𝑡−1 + µ𝑡 (4)
This s udy u ilised he VECM me hodology. The s a is ical cha ac e is ics o he se ies we e
sc u inised, ecognising ha a majo i y o economic ime se ies da a exhibi non-s a iona i y o e ime.
This necessi a es an examina ion o he s a is ical p ope ies o he a iables in ques ion. The s a is ical
assessmen s conduc ed o ou se ies include he Augmen ed Dickey-Fulle (ADF) es , employed o
asce ain he s a iona i y le el; he Johansen coin eg a ion es , u ilised o e alua e he long- e m
ela ionship among he model a iables; and G ange causali y es s, which asce ain he causal
ansmission mechanism among he a iables, bo h endogenous and exogenous.
A signi ican p opo ion o economic da a exhibi uni oo s (i.e., non-s a iona i y), which leads
o he issue o spu ious eg ession. To mi iga e his p oblem, he s udy unde akes a s a iona i y es o
he ime se ies da a u ilising he Augmen ed Dickey-Fulle (ADF) and Phillips-Pe on (PP) es s. The
op imal lag leng h o he ADF es will be de e mined by he Schwa z in o ma ion c i e ion (SIC). In
ins ances whe e a uni oo is p esen in he da a, he co esponding ime se ies will be classi ied as non-
s a iona y. The o mal ADF es p ocedu e can be a icula ed as p esen ed in equa ion (5):
𝛥𝑋𝑡= 𝑎]𝜏+𝛽𝑋𝑡−1 +∑𝛿𝑗𝛥𝑋𝑡−1 +µ𝑡 (5)
𝑝
𝑗=1
Whe e 𝑡 is he ime, 𝑝 is he lag o de , and 𝛥𝑋𝑡 is he i s di e ence o he ime se ies da a. I
𝛽 is conside ably nega i e in he ADF esul , he null hypo hesis ha a iable(x) is non-s a iona y
𝐻0:𝛽 =0is ejec ed.
The Philip-Pe on (PP) es , con e sely, shall be u ilised owing o i s addi ional me i o e he
Augmen ed Dickey-Fulle (ADF) es , as i has been modi ied o elimina e he p esump ion ha he e o
e ms a e se ially independen , inco po a ing se ial co ela ion h ough he implemen a ion o he Newey-
Wes (1994) co a iance ma ix. In he PP es , he o de o in eg a ion o ou a iables is de e mined
based on he es ha encompasses bo h he in e cep and ime end. Consequen ly, we can delinea e
he gene al o m o he es u ilising he ollowing equa ion:
15
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𝑋𝑡=𝑎1+𝑏2𝑋𝑡−1 + 𝑎3(𝑡+𝑇
2)+µ𝑡 (5)
Whe e, T is he numbe o obse a ions in he model and 𝑎1, 𝑎2, and 𝑎3 a e he eg ession's
coe icien s. He e, we also es he al e na i e, which asse s he con a y, agains he null hypo hesis,
which s a es ha he se ies has a uni oo . The null hypo hesis was e alua ed a he adi ional 1% and
5% le els o signi icance, and i he a iables a e ound o be non-s a iona y a le el, hey will be con e ed
o i s di e ence o become s a iona y.
When he s a iona i y is con i med, indica ing ha all a iables a e asce ained o possess he
same o de o in eg a ion, we p oceed o in es iga e he p esence o coin eg a ion among he included
a iables. The objec i e he ein is o asce ain whe he a long- e m ela ionship exis s be ween non-
s a iona y da a ha a e coin eg a ed in he same o de . This concep was in oduced by Johansen (1988)
and u he elabo a ed by Johansen and Juselius (1990). The coin eg a ion es is execu ed o sc u inize
whe he ou a iables exhibi a long- e m equilib ium ela ionship. As posi ed by Engle and G ange
(1987), he coin eg a ed se ies mus possess an E o Co ec ion Model (ECM) ep esen a ion. This is
he a ionale behind he popula i y o coin eg a ion analysis, as i u nishes a o mal amewo k o he
examina ion and es ima ion o bo h sho - un and long- un ela ionships among economic a iables.
Fu he mo e, he ECM me hodology o e s a emedy o he po en ial issues associa ed wi h eg ession.
𝛥𝑌𝑡−1 =Ӷ0+Ӷ1𝛥𝑌𝑡−1 + Ӷ2𝛥𝑌𝑡−2 + …+ Ӷ𝑘−1𝛥𝑌𝑡−𝑘 + 𝛱𝑌𝑡−𝑘 +𝜀𝑡 (6)
The de e minis ic end o he model is ep esen ed by Ӷ0, he andom e o e m is ep esen ed
by 𝜀𝑡 and 𝑌𝑡 ep esen s he ap × 1 ec o o non-s a iona y a iables (a le el). The e o co ec ion
e ms (ECT), deno ed by 𝛱, gi e de ails abou how he VECM has been adjus ed o i s long- e m
equilib ium.
As posi ed by Engle and G ange (1987), he coin eg a ed se ies mus possess an ECM
ep esen a ion. This is he eason ha coin eg a ion analysis has gained p ominence, as i p o ides a
o mal amewo k o he examina ion and es ima ion o bo h sho - un and long- un ela ionships
among economic a iables. In addi ion, he ECM me hodology o e s an adjus men o he po en ial
issues associa ed wi h eg ession.
The G ange causali y es , as a icula ed by Ambla d and Michel (2011), s ipula es ha a ime
se ies a iable (designa ed as y) is G ange caused by ano he ime se ies a iable (designa ed as x) i he
u u e alues o y can be mo e accu a ely p edic ed by inco po a ing he pas alues o bo h ‘y’ and ‘x’
compa ed o p edic ions based solely on he pas alues o ‘y.’ This s udy p esen s a s aigh o wa d
bi a ia e model ha es s whe he y is G ange caused by x h ough he subsequen equa ion:
𝑦𝑡=𝑎0+ ∑ƴ11,𝑖𝑦𝑡−𝑗 + ∑ƴ12,
𝑝
𝑗=1
𝑝
𝑗=1 𝑖𝑥𝑡−𝑗 +𝜀𝑡 (7)
F om he equa ion 𝑎0 is he cons an and 𝜀𝑡 ep esen he e o e m.
As elucida ed by he G ange ep esen a ion heo em, G ange causali y s ipula es ha a leas
one o he a ious adjus men coe icien s mus possess a non-ze o alue o a long- e m ela ionship
among he a iables o be sus ained. In i s con en ional o mula ion, he esul s o G ange causali y
demons a e wo-way eedback ela ionships.
16The Jou nal o En ep eneu ial Finance, Vol. 27, Iss. 1 [2025], A . 3
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4. Empi ical Resul s
4.1.
Desc ip i e s a is ic
Due o he implemen a ion o a log-linea econome ic model speci ica ion, he ex eme alues
o all selec ed a iables exhibi minimal a ia ion, wi h he excep ion o he LNMBL and LNGCF
a iables. The s anda d de ia ions epo ed in ela ion o he mean, as illus a ed in Table 1, indica e ha
he da a poin s, ep esen ed in he na u al loga i hm o he a iables, a e no ma kedly dispe sed om
he mean. Rega ding he skewness and ku osis sec ion in Table 1, he con en ional guideline asse s ha
a epo ed alue o less han 3 is classi ied as pla yku ic. Obse ing he epo ed ku osis s a is ic in Table
1 e eals ha all a iables, wi h he excep ion o he LNINT a iable, a e indeed pla yku ic. Adhe ing o
he es ablished guideline, he ku osis s a is ic o he LNINT a iable exceeds 3, he eby allowing he
esea che o cha ac e ize he LNINT a iable as lep oku ic (indica i e o a high peaked dis ibu ion).
The epo ed skewness s a is ic alls wi hin he ange o -0.2 and 0.4, he eby indica ing wi h au ho i y
ha he dis ibu ion is app oxima ely symme ic. The examina ion o no mal dis ibu ion is o hcoming,
and he epo ed Ja que-Be a s a is ic in Table 1 is su icien ly suppo ed by he p- alues, all o which a e
insigni ican a he 5% le el, he eby sugges ing no mal dis ibu ion. The a o emen ioned esul s lead o
he accep ance o he null hypo hesis, he eby concluding ha all a iables p esen ed in Table 1 con o m
o a no mal dis ibu ion.
Table 1. Desc ip i e S a is ic
LNGDPPC
LNCBSMEs
LNMBL
LNINT
LNGCF
LNLAB
Mean
7.079441
10.35039
9.799578
2.867567
8.692251
17.68150
Median
7.537117
10.61752
10.25783
2.867082
8.927350
17.71112
Maximum
8.071204
11.72749
12.47850
3.394508
11.08563
17.96979
Minimum
5.598524
9.282464
4.911183
2.440879
5.982950
17.33200
S d. De .
0.778641
0.734736
2.168155
0.192852
1.327513
0.193934
Skewness
-0.434006
0.106683
-0.437620
0.086333
-0.146834
-0.213615
Ku osis
1.628538
1.739759
1.972512
4.127125
2.365320
1.887472
Ja que-Be a
3.402705
2.110236
2.353128
1.679457
0.631702
1.834480
P obabili y
0.182437
0.348151
0.308336
0.431828
0.729168
0.399621
Sum
219.4627
320.8621
303.7869
88.89459
269.4598
548.1265
Sum Sq. De .
18.18846
16.19510
141.0269
1.115756
52.86871
1.128317
Obse a ions
31
31
31
31
31
31
Sou ce: Au ho s’ compu a ion using EViews 10
4.2.
Uni oo es s
As a p e equisi e o he coin eg a ion analysis, we unde ake a uni oo es u ilizing he wo
p incipal me hodologies o he Augmen ed Dickey-Fulle (ADF) and Phillips-Pe on (PP) es s o
asce ain he s a iona i y o ou a iable. The esul s o he ADF and PP es s a e delinea ed in Table 2.
17
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Table 2. Uni Roo Tes s
Va iable
Lag leng h
ADF s a is ics
PP s a is ics
Rema k
LNGDPPC
7
-0.957005
-1.108759
D(LNGDPPC)
7
-7.021640
-6.697349
I(1)
LNCBSMEs
7
-1.494513
-1.494513
D(LNCBSMEs)
7
-5.424138
-5.423566
I(1)
LNMBL
7
-3.257904
-3.340962
D(LNMBL)
7
-6.834485
-10.03599
I(1)
LNINT
7
-1.127362
-1.745226
D(LNINT)
7
-6.834485
-7.649792
I(1)
LNGCF
7
-2.564645
-2.689021
D(LNGCF)
7
-4.016228
-3.977679
I(1)
LNLAB
7
-2.498267
-1.437917
D(LNLAB)
7
-3.581226
-3.183396
I(1)
C i ical alues
1%
-4.296729
-4.309824
5%
-3.568379
-3.574244
10%
-3.218382
-3.221728
*** ep esen s s a iona y a 1% le el o signi icance; ** ep esen s s a iona y a 5% le el o signi icance;
* ep esen s s a iona y a 10% le el o signi icance
Le el ep esen s Loga i hms o a iables; ‘D’ ep esen s ha he a iable has been di e enced.
The indings indica e ha all a iables a e non-s a iona y a he le el. Howe e , upon
ans o ma ion o he a iables o hei i s di e ence, employing bo h in e cep and de e minis ic end,
hey a ain s a iona i y. Consequen ly, he a iables a e deemed o be in eg a ed o one o de , speci ically
I(1), leading o he applica ion o Johansen coin eg a ion es and VECM.
4.3.
Johansen coin eg a ion es
The esul s o he Johansen coin eg a ion es , p edica ed on he ace es , a e p esen ed in Table
3 (Panel A). The es based on ace s a is ics e alua es he null hypo hesis asse ing he absence o
coin eg a ion among he a iables. We ejec he null hypo hesis i he es s a is ic su passes he c i ical
alues o he ace es s a ei he he 1% o 5% signi icance le el. Table 3 (Panel B) elucida es he
ou comes o he Johansen coin eg a ion es based on he maximum eigen alue. This es (maximum
eigen alue) is conduc ed unde he null hypo hesis conce ning he numbe o coin eg a ing equa ions ( )
agains he al e na i e hypo hesis posi ing an inc ease in he numbe o coin eg a ing equa ions by one (
+ 1). The null hypo hesis is no ejec ed i he es s a is ic emains below he c i ical alue es ablished
o he maximum eigen alue es .
In Table 3 (Panel A), he ace es , which is conside ably mo e s ingen , indica ed he p esence
o no ewe han h ee (3) coin eg a ing equa ions a a signi icance le el o 5%. Consequen ly, he null
hypo hesis o he absence o coin eg a ion was ejec ed, as he ace es s a is ic alues o 133.0034,
86.07811, and 51.61595 exceed he 5% c i ical alues o 95.75366, 69.81889, and 47.85613, espec i ely.
Thus, he ace s a is ics con i med he exis ence o h ee coin eg a ing ela ionships a he 5% le el o
signi icance.
18The Jou nal o En ep eneu ial Finance, Vol. 27, Iss. 1 [2025], A . 3
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The maximum eigen alue es p esen ed in Table 3 (Panel B) sugges s he exis ence o h ee (3)
coin eg a ing equa ions a he 5% signi icance le el. The e o e, i is pe missible o ejec he null
hypo hesis conce ning he absence o coin eg a ing ec o s, gi en ha he eigen alue s a is ics o
46.92524, 34.46216, and 30.69059 su pass he 5% c i ical alues o 40.07757, 33.87687, and 27.58434,
espec i ely.
In ligh o hese indings, i may be deduced ha he e a e h ee (3) signi ican long- un
ela ionships among he a iables, as es ablished by he ace and maximum eigen alue s a is ics.
Recognizing ha he a iables may exhibi bo h sho - un and long- un e ec s, he ec o e o
co ec ion model (VECM), which di e en ia es hese e ec s, was subsequen ly es ima ed.
Table 3. Johansen Co-in eg a ion Tes
Hypo hesized
No. o CE(s)
Eigen alue
T ace
S a is ic
0.05
C i ical Value
P ob.**
Panel A: Un es ic ed Coin eg a ion Rank Tes (T ace)
None *
0.801727
133.0034
95.75366
0.0000
A mos 1 *
0.695276
86.07811
69.81889
0.0015
A mos 2 *
0.652953
51.61595
47.85613
0.0213
A mos 3
0.362014
20.92536
29.79707
0.3623
A mos 4
0.234775
7.891618
15.49471
0.4770
A mos 5
0.004530
0.131661
3.841466
0.7167
T ace es indica es 3 coin eg a ing eqn(s) a he 0.05 le el
* deno es ejec ion o he hypo hesis a he 0.05 le el
**MacKinnon-Haug-Michelis (1999) p- alues
Panel B: Un es ic ed Coin eg a ion Rank Tes (Maximum Eigen alue)
Hypo hesized
Max-Eigen
0.05
No. o CE(s)
Eigen alue
S a is ic
C i ical Value
P ob.**
None *
0.801727
46.92524
40.07757
0.0073
A mos 1 *
0.695276
34.46216
33.87687
0.0425
A mos 2 *
0.652953
30.69059
27.58434
0.0193
A mos 3
0.362014
13.03374
21.13162
0.4491
A mos 4
0.234775
7.759958
14.26460
0.4036
A mos 5
0.004530
0.131661
3.841466
0.7167
Max-eigen alue es indica es 3 coin eg a ing eqn(s) a he 0.05 le el
* deno es ejec ion o he hypo hesis a he 0.05 le el
**MacKinnon-Haug-Michelis (1999) p- alues
Sou ce: Au ho s’ compu a ion using EViews 10
4.4.
Vec o e o co ec ion mechanism (VECM)
The coin eg a ion among he a iables acili a es he es ima ion o he VECM. The esul s o he
es ima ed VECM a e encapsula ed in Table 4. The coin eg a ion es subs an ia es he exis ence o a long-
un ela ionship and se es o disagg ega e he long- un e ec s om he sho - un impac s. The VECM
elucida es how he sho - un disequilib ium ela ionships among he es ima ed a iables a e adjus ed
19
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owa ds he long- un equilib ium ajec o y. The coe icien s o he a iables ep esen he long- e m
elas ici ies o he no malized coin eg a ing ec o s.
The s anda d e o s a is ics a e p esen ed in pa en heses, while he -s a is ics a e enclosed in
b acke s. The coe icien s pe aining o comme cial banks’ c edi o SMEs (LNCBSMEs) and
mic o inance banks’ loans (LNMBL) a e bo h nega i e and s a is ically signi ican . The an icipa ed signs
o bo h a iables we e expec ed o be posi i e; howe e , hey a e obse ed o be nega i e, po en ially
a ibu able o ele a ed in e es a es, he c owding-ou e ec o go e nmen bo owings, o inadequa e
pene a ion o capi al in o economically p oduc i e ac i i ies. This obse a ion aligns wi h he ene s o
he ad e se selec ion heo y, which posi s ha banks a e o en unce ain in hei abili y o iden i y
c edi wo hy bo owe s om he exis ing pool, leading hem o aise in e es a es o mi iga e he isk o
selec ing subop imal bo owe s. Consequen ly, high- isk bo owe s a e inclined o accep such acili ies,
which ul ima ely heigh ens he a e o loan de aul s and diminishes pe capi a ou pu .
Table 4. Long- un Es ima es
No malized Coin eg a ing Coe icien s
LNCBSMEs(-1)
LNMBL(-1)
LNMBL(-1)
LNINT(-1)
LNGCF
LNLAB
C
-0.174364
-0.311302
-0.311302
0.796269
1.877698
-12.70356
203.7908
(0.05897)
(0.06926)
(0.06926)
(0.22111)
(0.24312)
(1.03163)
[-2.95697]
[-4.49447]
[-4.49447]
[ 3.60119]
[ 7.72340]
[-12.3140]
Sou ce: Au ho s’ compu a ion using EViews 10
The long- un coin eg a ing equa ion ex ac ed om Table 4 is as delinea ed by equa ion (8).
𝐿𝑁𝐺𝐷𝑃𝑃𝐶 =203.7908− 0.174364LNCBSMES − 0.311302LNMBL + 0.796269LNINT
+ 1.877698LNGCF− 12.70356LNLAB (8)
The disco e y o a long- un equilib ium ela ionship among he a iables, as e idenced by he
Johansen coin eg a ion analysis, necessi a ed he implemen a ion o he VECM. Th ough his
me hodology, bo h he long- un equilib ium and he sho - un dynamic ela ionships pe inen o he
a iables unde in es iga ion a e elucida ed. The VECM es ima es p esen ed in Table 5 demons a e ha
LNGDPPC exhibi s a nega i e esponse o bo h LNCBSMEs and LNMBL. This esul signi ies ha he
es ablished in luence is s a is ically signi ican a lag 1. I is obse able ha an inc ease o 10% in
LNCBSMEs and LNMBL co esponds o a dec ease in LNGDPPC o app oxima ely 2.0% and 2.3%,
espec i ely. Fu he mo e, LNINT exe s a nega i e e ec on LNGDPPC, while a posi i e e ec is no ed
o LNGCF.
The e o co ec ion e m (ECT) sa is ied he s ipula ed condi ions. The p esence o a nega i e
sign and he s a is ical signi icance o he e o co ec ion coe icien s a e essen ial p e equisi es o any
disequilib ium o be ec i ied. In his con ex , he coe icien o ECT (-1) wi hin he model is -0.452356,
accompanied by a p obabili y alue o 0.0001. This coe icien signi ies ha he a e o adjus men
be ween he sho - un dynamics and he long- un equilib ium in he ini ial model is 45.2%. Consequen ly,
he ECT is poised o e ec i ely ec i y any disc epancies o he sho - un dynamics o i s long- un
equilib ium on an annual basis wi hin he model. Hence, he ou come indica es ha he ECT ec i ies he
disequilib ium om he p eceding pe iods a a a e (o speed) o 45.2% annually.
Ci ing he ou pu o he VECM p esen ed in Table 5, he adjus ed R-squa ed alue epo ed is
app oxima ely 77.9%, sugges ing a obus linea co ela ion be ween LNGDPPC and he chosen
20The Jou nal o En ep eneu ial Finance, Vol. 27, Iss. 1 [2025], A . 3
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independen a iables. Rein o cing he a o emen ioned asse ion, he F-s a is ic (F= 8.330309, p-
alue=0.000170), which is e iden ly signi ican a he 1% le el, posi s ha he independen a iables
(LNCBSMEs, LNMBL, LNINT, LNGCF, and LNLAB) collec i ely elucida e he a ia ions in he
dependen a iable (LNGDPPC). The F-s a is ic delinea ed in Table 5 u he subs an ia es he
signi icance o he model employed in his s udy. The Du bin-Wa son (DW) s a is ic sugges s he absence
o signi ican se ial co ela ion, suppo ing his claim wi h an es ablished guideline ha s ipula es alues
o he DW wi hin he ange o 1.5-2.5 a e gene ally conside ed no mal.
Table 5. Vec o E o Co ec ion Mechanism (VECM)
Coe icien
S d. E o
-S a is ic
P ob.
ECT(-1)
-0.452356
0.085691
-5.278905
0.0001
D(LNGDPPC(-1))
0.749743
0.115547
6.488638
0.0000
D(LNGDPPC(-2))
0.420534
0.110834
3.794267
0.0020
D(LNCBSMEs(-1))
-0.198851
0.046405
-4.285120
0.0004
D(LNCBSMEs(-2))
-0.229393
0.036348
-6.311032
0.0000
D(LNMBL(-1))
-0.076037
0.030283
-2.510828
0.0249
D(LNMBL(-2))
0.065740
0.030193
2.177322
0.0471
D(LNINT(-1))
-0.478650
0.128875
-3.714070
0.0023
D(LNINT(-2))
0.149387
0.090049
1.658958
0.1194
D(LNGCF(-1))
0.116912
0.128626
0.908931
0.3788
D(LNGCF(-2))
0.570244
0.139644
4.083544
0.0011
D(LNLAB(-1))
-2.565558
1.006730
-2.548406
0.0232
D(LNLAB(-2))
-1.972869
1.423667
-1.385766
0.1875
Cons an
0.002147
0.032811
0.065440
0.9487
R-squa ed
0.885522
Mean dependen a
0.068507
Adjus ed R-squa ed
0.779221
S.D. dependen a
0.131691
S.E. o eg ession
0.061878
Akaike in o c i e ion
-2.420451
Sum squa ed esid
0.053604
Schwa z c i e ion
-1.754349
Log likelihood
47.88632
Hannan-Quinn c i e .
-2.216817
F-s a is ic
8.330309
Du bin-Wa son s a
2.277238
P ob(F-s a is ic)
0.000170
Sou ce: Au ho s’ compu a ion using EViews 10
4.5.
Validi y es s
To enhance he eliabili y o he es ima ed model, he esea che unde akes a comp ehensi e
diagnos ic examina ion add essing issues o se ial co ela ion, he e oskedas ici y, and no mal dis ibu ion.
The esul s delinea ed in Table 6 indica e ha he B eusch-God ey Se ial Co ela ion LM Tes con i ms
he absence o se ial co ela ion in he VECM model. This inding co obo a es he Du bin-Wa son
(DW) s a is ic esul p esen ed in Table 5. The subsequen es o he e oskedas ici y e eals ha he
model exhibi s homoskedas ici y. These esul s a e a o able and con i m ha ou o e all indings a e
non-spu ious and consequen ly eliable. The ou comes o he Ramsey es p o ide e idence o he no mal
dis ibu ion o he model. Fu he mo e, he Recu si e CUSUM and CUSMSQ plo s illus a ed in Figu es
4 and 5 a i m he s abili y o he model.
21
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Table 6. Validi y es s
Tes
Obs*
R-squa ed
P ob.
Chi-squa e
F-s a is ic
-S a is ic
P ob.
B eusch-God ey
Se ial Co ela ion LM Tes
2.146112
0.3420
0.639345
-
0.5406
He e oskedas ici y Tes :
B eusch-Pagan-God ey
21.39154
0.2601
1.618498
-
0.2330
Ja que-Be a
No mal dis ibu ion
-
-
-
0.707691
0.7019
Sou ce: Au ho s’ compu a ion using EViews 10
-12
-8
-4
0
4
8
12
09 10 11 12 13 14 15 16 17 18 19 20 21 22
CUSUM 5% Signi icance
-0.4
0.0
0.4
0.8
1.2
1.6
09 10 11 12 13 14 15 16 17 18 19 20 21 22
CUSUM o Squa es 5% Signi icance
Figu e 4. CUSUM plo
Figu e 5. CUSUMSQ plo
4.6.
G ange causali y es s
Th ough he execu ion o his examina ion, he pai wise associa ions among he es ima ed
a iables a e de e mined. Consequen ly, Table 7 is p o ided as ollows.
Table 7. Pai wise G ange Causali y Tes
Pai wise G ange Causali y Tes s
Da e: 01/02/25 Time: 03:28
Sample: 1992 2022
Lags: 2
Null Hypo hesis:
Obs
F-S a is ic
P ob.
LNCBSMES does no G ange Cause LNGDPPC
29
5.95507
0.0079
LNGDPPC does no G ange Cause LNCBSMES
3.80754
0.0302
LNMBL does no G ange Cause LNGDPPC
29
0.01348
0.9866
LNGDPPC does no G ange Cause LNMBL
3.66655
0.0408
Sou ce: Au ho s’ compu a ion using EViews 10
The causal ela ionship be ween LNCBSMES and LNGDPPC exhibi ed a bidi ec ional
na u e. This indica es ha LNCBSMES exe s in luence o e LNGDPPC, and con e sely,
22The Jou nal o En ep eneu ial Finance, Vol. 27, Iss. 1 [2025], A . 3
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DOI: 10.57229/2373-1761.1508
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30The Jou nal o En ep eneu ial Finance, Vol. 27, Iss. 1 [2025], A . 3
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DOI: 10.57229/2373-1761.1508
The Jou nal o En ep eneu ial Finance
Published by Peppe dine Digi al Commons, 2025 Ikwuagwu e al.: Fo mal Financing o SMEs
Appendix 1:
Da a P esen a ion
GDPPC (GDP pe capi a); CBSMEs (comme cial bank’s c edi o SMEs); MBL (mic o inance bank’s
loans); INT (in e es a e on lending); GCF (g oss capi al o ma ion); LAB (labou o ce)
Yea
GDPPC
CBSMEs
MBL
INT
GCF
LAB
1992
477.08
20400.00
135.80
29.80
396.61
33665896.00
1993
270.03
15462.90
654.50
18.32
559.15
34567536.00
1994
320.83
20552.50
1220.60
21.00
744.09
35509739.00
1995
407.28
32374.50
1129.80
20.18
1153.47
36476502.00
1996
460.32
42302.10
1400.20
19.74
1494.75
37359834.00
1997
478.58
40844.30
1618.80
13.54
1697.77
38306242.00
1998
467.94
42260.70
2526.80
18.29
1948.65
39308944.00
1999
496.03
46824.00
2958.30
21.32
2098.54
40378165.00
2000
565.31
44542.30
3666.60
17.98
2404.82
41439754.00
2001
586.83
52428.40
1314.00
18.29
2473.47
42444294.00
2002
733.54
82368.40
4310.90
24.85
3078.78
43376700.00
2003
786.80
90176.50
9954.80
20.71
3846.23
44463288.00
2004
992.75
54981.20
11353.80
19.18
4723.72
45568178.00
2005
1250.41
50672.60
28504.80
17.95
5772.64
46768185.00
2006
1652.15
25713.70
16450.20
17.26
7948.12
47945348.00
2007
1876.41
41100.40
22850.20
16.94
6997.62
49185874.00
2008
2227.79
13512.20
42753.06
15.14
7535.27
50482323.00
2009
1883.89
16366.49
58215.66
18.99
9177.08
51791905.00
2010
2280.11
12550.30
52867.50
17.59
9183.06
53143752.00
2011
2504.88
15611.70
50928.30
16.02
9897.20
54535983.00
2012
2728.02
13863.46
90422.25
16.79
10281.95
53686203.00
2013
2976.76
15353.04
94055.58
16.72
11478.08
52794910.00
2014
3200.95
16069.27
112110.15
16.55
13593.78
53696560.00
2015
2679.55
12949.48
187247.34
16.85
14112.17
54557234.00
2016
2144.78
10747.89
196194.99
16.87
15104.18
55285972.00
2017
1941.88
10747.89
194024.94
17.56
16908.13
57856159.00
2018
2125.83
44822.84
207963.32
19.33
24550.24
60517054.00
2019
2334.02
123932.10
262630.00
15.53
35863.98
63226720.00
2020
2074.61
62510.17
179377.51
12.32
41253.55
62242961.00
2021
2065.75
83740.00
187661.03
11.48
58293.95
62700036.50
2022
2184.42
94460.00
195944.54
12.34
65227.13
63706286.72
Sou ce: CBN S a is ical Bulle in and he Wo ld De elopmen Indica o s (WDI)
31
Onyele e al.: Fo mal Financing o SMEs in Nige ia: A Pa h o Economic De elopmen ?Published by Peppe dine Digi al Commons, 2025
The Jou nal o En ep eneu ial Finance
Published by Peppe dine Digi al Commons, 2025 Ikwuagwu e al.: Fo mal Financing o SMEs
Appendix 2:
Na u al log o Da a
LN = na u al log
Yea
LNGDPPC
LNCBSMEs
LNMBL
LNINT
LNGCF
LNLAB
1992
6.17
9.92
4.91
3.39
5.98
17.33
1993
5.60
9.65
6.48
2.91
6.33
17.36
1994
5.77
9.93
7.11
3.04
6.61
17.39
1995
6.01
10.39
7.03
3.00
7.05
17.41
1996
6.13
10.65
7.24
2.98
7.31
17.44
1997
6.17
10.62
7.39
2.61
7.44
17.46
1998
6.15
10.65
7.83
2.91
7.57
17.49
1999
6.21
10.75
7.99
3.06
7.65
17.51
2000
6.34
10.70
8.21
2.89
7.79
17.54
2001
6.37
10.87
7.18
2.91
7.81
17.56
2002
6.60
11.32
8.37
3.21
8.03
17.59
2003
6.67
11.41
9.21
3.03
8.25
17.61
2004
6.90
10.91
9.34
2.95
8.46
17.63
2005
7.13
10.83
10.26
2.89
8.66
17.66
2006
7.41
10.15
9.71
2.85
8.98
17.69
2007
7.54
10.62
10.04
2.83
8.85
17.71
2008
7.71
9.51
10.66
2.72
8.93
17.74
2009
7.54
9.70
10.97
2.94
9.12
17.76
2010
7.73
9.44
10.88
2.87
9.13
17.79
2011
7.83
9.66
10.84
2.77
9.20
17.81
2012
7.91
9.54
11.41
2.82
9.24
17.80
2013
8.00
9.64
11.45
2.82
9.35
17.78
2014
8.07
9.68
11.63
2.81
9.52
17.80
2015
7.89
9.47
12.14
2.82
9.55
17.81
2016
7.67
9.28
12.19
2.83
9.62
17.83
2017
7.57
9.28
12.18
2.87
9.74
17.87
2018
7.66
10.71
12.25
2.96
10.11
17.92
2019
7.76
11.73
12.48
2.74
10.49
17.96
2020
7.64
11.04
12.10
2.51
10.63
17.95
2021
7.63
11.34
12.14
2.44
10.97
17.95
2022
7.69
11.46
12.19
2.51
11.09
17.97
32The Jou nal o En ep eneu ial Finance, Vol. 27, Iss. 1 [2025], A . 3
h ps://digi alcommons.peppe dine.edu/je / ol27/iss1/3
DOI: 10.57229/2373-1761.1508
