Ezeibekwe, Obinna F anklin
A icle
E ec s o bu eauc a ic co up ion on i ms' inancial
cons ain s
The Jou nal o En ep eneu ial Finance (JEF)
P o ided in Coope a ion wi h:
The Academy o En ep eneu ial Finance (AEF), Los Angeles, CA, USA
Sugges ed Ci a ion: Ezeibekwe, Obinna F anklin (2025) : E ec s o bu eauc a ic co up ion on i ms'
inancial cons ain s, The Jou nal o En ep eneu ial Finance (JEF), ISSN 2373-1761, Peppe dine
Uni e si y, G aziadio School o Business and Managemen and The Academy o En ep eneu ial
Finance (AEF), Malibu, CA and Los Angeles, CA, Vol. 27, Iss. 1, pp. 1-30,
h ps://doi.o g/10.57229/2373-1761.1505
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Volume 27
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A icle 1
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E ec s o Bu eauc a ic Co up ion on Fi ms' Financial Cons ain s E ec s o Bu eauc a ic Co up ion on Fi ms' Financial Cons ain s
Obinna F anklin Ezeibekwe
No he n Illinois Uni e si y
Follow his and addi ional wo ks a : h ps://digi alcommons.peppe dine.edu/je
Pa o he Econome ics Commons, Finance Commons, and he G ow h and De elopmen Commons
Recommended Ci a ion Recommended Ci a ion
Ezeibekwe, Obinna F anklin (2025) "E ec s o Bu eauc a ic Co up ion on Fi ms' Financial Cons ain s,"
The Jou nal o En ep eneu ial Finance
: Vol. 27: Iss. 1, pp. 1-30.
DOI: h ps://doi.o g/10.57229/2373-1761.1505
A ailable a : h ps://digi alcommons.peppe dine.edu/je / ol27/iss1/1
This A icle is b ough o you o ee and open access by he G aziadio School o Business and Managemen a
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Effec s o Bu eauc a ic Co up ion on Fi ms’ Financial Cons ain s
Obinna F anklin Ezeibekwe
No he n Illinois Uni e si y, DeKalb, IL USA
obi [email protected]
Abs ac : This s udy p o ides he fi s empi ical assessmen o he causal impac o bu eauc a ic
co up ion on fi ms’ financial cons ain s in Nige ia by calcula ing ea men effec s using linea
and non-linea es ima o s o accoun o po en ial he e ogeneous ea men effec s ac oss fi m
g oups. Fo mally, he heo e ical amewo k models how co up ion may acili a e o es ain
fi ms’ financial access by shaping hei cos unc ions, which consequen ly influences hei
success o ailu e and abili y o aise he colla e al o bo owing. My analysis, using he
bi a ia e p obi me hod and wo bina y ins umen s, e eals ha co up ion significan ly
inc eases he p obabili y o a ep esen a i e MSME and fi m being financially cons ained by
app oxima ely 62 o 64 and 61 o 63 pe cen age poin s, espec i ely. When he IV es ima o is
u ilized o calcula e local effec s, I find ha he effec is abou 90 o 91 pe cen age poin s o a
ypical MSME acing obs acles wi h ob aining business licenses and ax adminis a ion,
espec i ely. The effec is 92 pe cen age poin s o all fi ms using bo h ins umen s. Fu he mo e,
he esul s show ha Nige ian MSMEs a e abou 17 o 19 pe cen age poin s mo e likely o be
financially cons ained han la ge fi ms and ha co up ion’s impac on fi ms’ access o finance
does no depend on fi m size. Finally, fi ms ha pe cei e co up ion as a “mino ” ba ie
expe ience he mos difficul y ob aining ex e nal finance. This s udy highligh s he se e e
cons ain ha co up ion poses o Nige ian fi ms’ access o finance and ad oca es o egula o y
amendmen s o add ess issues wi h he ax adminis a ion and he ease o ob aining business
licenses and pe mi s.
Keywo ds: Co up ion, Financial cons ain s, Nige ia, MSME, Bi a ia e p obi
1
Ezeibekwe: Bu eauc a ic Co up ion and Fi ms' Financial Cons ain sPublished by Peppe dine Digi al Commons, 2025
1.
In oduc ion
Mic o, small, and medium en e p ises (MSMEs) a e c ucial o less-de eloped coun ies
(LDCs) by c ea ing employmen oppo uni ies, d i ing economic g ow h, and educing po e y
(Maksimo e al., 2017). Howe e , MSMEs equi e access o sus ainable finance o pe o m
hese c i ical de elopmen al unc ions. Un o una ely, acco ding o a 2021 su ey epo by he
Small and Medium En e p ises De elopmen Agency o Nige ia (SMEDAN) and he Na ional
Bu eau o S a is ics (NBS), access o finance emains he bigges challenge o MSMEs’ g ow h
in Nige ia.1 Fi ms ace financial cons ain s due o se e al ac o s, such as domes ic owne ship
(Blalock e al., 2008), unde de eloped financial a chi ec u e (Lo e, 2003), and a weak legal and
ins i u ional en i onmen (Qian and S ahan, 2007). One significan ac o ha unde mines
he ins i u ional en i onmen is co up ion; howe e , he e a e s ill significan esea ch gaps
ega ding how co up ion impac s MSMEs’ access o finance in LDCs. The e o e, he p ima y
objec i e o his esea ch is o es ima e he ea men effec s o co up ion on Nige ian fi ms’
financial cons ain s by compa ing ea men effec s es ima es de i ed using linea and non-linea
es ima o s.
Co up ion, defined as he misuse o en us ed powe o p i a e gain, emains a
subs an ial economic and social issue in mos LDCs and i s sys emic na u e makes i challenging
o add ess. Economic esea ch p o ides conflic ing p edic ions ega ding he impac o
co up ion on en e p ises’ access o finance. On he one hand, co up ion could “sand he wheels”
o access o finance in se e al ways. Fi s , b ibes educe fi m g ow h e en mo e han axa ion,
making i mo e difficul o fi ms o aise colla e al and acqui e loans om financial ins i u ions
(Fisman and S ensson, 2007). Second, co up ion dep esses economic g ow h, which could
consequen ly affec he abili y o banks o lend (Johnson e al., 2011;
G
u
¨
ndle
and Po a ke,
2019; Mo, 2001;
M
´
eon
and Sekka , 2005).
Thi d, co up ion nega i ely affec s us (Mo is and Klesne , 2010; Bane jee, 2016),
which could esul in fi ms doub ing hei abili y o acqui e ex e nal finance o banks doub ing
hei abili y o eco e loans in he e en o de aul , he eby p e en ing hem om lending.
Fou h, co up public officials and agencies could misapp op ia e unds in ended o he benefi
o fi ms o indus ies o o he pu poses (S ensson, 2005; Mau o, 1998). On he o he hand,
co up ion could “g ease he wheels” o access o finance o fi ms by educing bu eauc acy and
ed ape associa ed wi h ob aining ex e nal finance (D ehe and Gassebne , 2013), educing he
ime spen on queues (Lui, 1985), assis ing fi ms o bypass go e nmen egula ions (Jiang and Nie,
2014), and imp o ing efficiency in coun ies wi h weak ins i u ions
(M
´
eon
and Weill, 2010).
Fi ms ope a ing in Nige ia ace se e al challenges, including mul iple axa ion, le ies, and
ex o ion by public officials and loosely o ganized gangs known as “a ea boys.” These challenges,
e e ed o as “lowe -le el co up ion,” esul in a significan inc ease in he cos o doing busi-
ness. Howe e , “Uppe -le el co up ion” en ails he illegal di e sion o go e nmen esou ces
in ended o suppo fi ms, he eby unde mining business g ow h and impac . The his o y o
an i-co up ion effo s, o add ess bo h uppe - and lowe -le el co up ion, in Nige ia may be
aced o he Second Republic when he pionee an i-co up ion agency, he Code o Conduc
Bu eau (CCB) was es ablished in 1979. The Fou h Republic which s a ed in 1999 wi nessed
he es ablishmen o he Independen Co up P ac ices Commission (ICPC) in 2000 as a spe-
1h ps://smedan.go .ng/wp-con en /uploads/2022/03/2021-MSME-Su ey-Repo _1.pd
2The Jou nal o En ep eneu ial Finance, Vol. 27, Iss. 1 [2025], A . 1
h ps://digi alcommons.peppe dine.edu/je / ol27/iss1/1
DOI: 10.57229/2373-1761.1505
cialized agency o ackle public sec o co up ion, including g a , b ibe y, and abuse o office.
The Economic and Financial C imes Commission (EFCC) was in oduced h ee yea s la e as a
law en o cemen agency o in es iga e financial c imes like money launde ing, ad anced- ee aud
(known in Nige ia as “419”), and ela ed offenses. These agencies ha e been ins umen al in cu b-
ing co up ion in Nige ia, bu mo e wo k needs o be done o c ea e a mo e enabling en i onmen
o businesses o h i e and con ibu e o Nige ia’s economic g ow h and de elopmen .
Addi ionally, he go e nmen has made effo s o ensu e ha small businesses h i e. Fo
example, SMEDAN was es ablished in 2003 o coo dina e he de elopmen o he MSME sub-
sec o . Howe e , i s lack o anspa ency makes i difficul o s udy i s budge a y p ac ices o
iden i y he beneficia ies o i s p og ams. The Cen al Bank o Nige ia (CBN) has also launched
a ious p og ams aimed a suppo ing MSMEs, such as lending o go e nmen de elopmen fi-
nance ins i u ions o enable MSMEs o access finance a mo e affo dable a es. No ably, he
CBN’s Small and Medium En e p ises Equi y In es men Scheme (SMEEIS) manda es all banks
o ese e 10 pe cen o hei a e - ax p ofi o equi y in es men o o offe single-digi in e es
a e loans o small businesses. Simila ly, he CBN app o ed ₦500 billion Nai a deben u e s ock,
o be issued o small fi ms by he Bank o Indus y (BOI), and he ₦200 billion Nai a Small
and Medium En e p ises C edi Gua an ee Scheme (SMECGS) was aimed a enhancing c edi o
MSMEs.2 None heless, he effec i eness o hese CBN in e en ions is elian on he deg ee o
moni o ing ca ied ou by he CBN.
These effo s a ge ed a MSMEs and o he fi ms a e aimed a educing high po e y and
unemploymen a es. Despi e hese effo s, po e y and unemploymen a es in he coun y o
211 million people con inue o sky ocke . The NBS, in collabo a ion wi h he Na ional So-
cial Sa e y-Ne s Coo dina ing Office (NASSCO), he Uni ed Na ions De elopmen P og amme
(UNDP), he Uni ed Na ions Child en’s Fund (UNICEF), and he Ox o d Po e y and Hu-
man De elopmen Ini ia i e (OPHI), de eloped he Na ional Mul idimensional Po e y Index
(NMPI)3 o p o ide a mo e comp ehensi e measu e o po e y ha conside s mone a y po e y,
educa ion, and basic in as uc u e. Acco ding o he NMPI, abou 63 pe cen o Nige ians we e
mul idimensionally poo in 2022, wi h 65 pe cen o his popula ion li ing in No he n Nige ia
and 72 pe cen li ing in u al a eas. Addi ionally, he unemploymen a e in Nige ia inc eased
om 14 pe cen in 2017 o 33 pe cen in 2020, as epo ed by he NBS.
Because co up ion may impac he g ow h o MSMEs and all fi ms, his esea ch p o ides
he fi s empi ical assessmen o he effec s o bu eauc a ic co up ion on Nige ian fi ms’ financial
cons ain s. Addi ionally, I es ima e he models using da a o MSMEs and all fi ms. Using wo
bina y ins umen s ha a e ele an and alid, I employ he ins umen al a iable es ima o o
es ima e he linea model and a bi a ia e p obi es ima o o es ima e he a e age ea men effec
(ATE) o complie s and non-complie s. This app oach is impo an because he local effec is
unlikely o be equi alen o he ATE when he e a e he e ogeneous ea men effec s ac oss fi m
g oups. Addi ionally, applying diffe en es ima o s highligh s he beha io o diffe en es ima o s
when ce ain assump ions a e made.
The e a e many easons why his esea ch is essen ial. Fi s , Nige ia, being he mos pop-
ulous coun y in Sub-Saha an A ica, is ep esen a i e o he egion and aces simila de elopmen
challenges such as co up ion and an unde de eloped MSME sub-sec o , as o he coun ies in he
2
h ps://www.cbn.go .ng/De in/sme inance.asp
3
h ps://mppn.o g/wp-con en /uploads/2022/11/MPI_web_No 15_FINAL.pd
3
Ezeibekwe: Bu eauc a ic Co up ion and Fi ms' Financial Cons ain sPublished by Peppe dine Digi al Commons, 2025
egion. The e o e, he esul s o his s udy could be gene alized o o he coun ies in he egion.
Also, his s udy is ele an because o he emphasis placed on e adica ing co up ion and
g owing MSMEs du ing Nige ia’s jus concluded 2023 gene al elec ions. This pape p o ides
policymake s wi h he fi s empi ical e idence o how fi m- ela ed co up ion, no co up ion in
gene al, affec s he economy. Finally, his esea ch would help o de e mine whe he he p esen
and u u e go e nmen s o Nige ia should p io i ize an i-co up ion campaigns.
The second sec ion e iews he li e a u e and he me hodology is desc ibed in he hi d
sec ion. The ou h sec ion p esen s he esul s and he fi h and final sec ion concludes.
2.
Li e a u e Re iew
The exis ing li e a u e examines he effec s o co up ion on fi ms’ financial access, bu
limi ed esea ch exis s o coun ies in he Sub-Saha an A ican egion. The li e a u e also
explo es co up ion- ela ed ac o s ha may affec fi ms’ access o finance.
The main objec i e o Xu and Yano (2017) is o es ima e he effec o an i-co up ion
effo s on he financing o and in es ing in inno a ion using fi m-le el da a ob ained om he
China S ock Ma ke and Accoun ing Resea ch (CSMAR) da abase o 1895 es ablishmen s om
2009 o 2015. An i-co up ion effo s can imp o e he financing o and in es men in inno a ion
by educing he exp op ia ion p oblem, which a gues ha fi ms a e less likely o unde ake
isky inno a i e pu sui s i hey ea ha en s acc uable om inno a ion could be exp op ia ed
by co up public officials he eby inc easing he cos s associa ed wi h inno a ion. The s udy
employs a p obi , GMM, and dynamic GMM model wi h h ee ex e nal ins umen s o accoun
o endogenei y and es ima e he financial access equa ion. The esul s indica e ha s onge an i-
co up ion effo s a e associa ed wi h imp o ed access o finance, pa icula ly long- e m deb , o
fi ms. U ilizing he da a o 79 coun ies, Amin and Mo a (2023) in es iga e how bu eauc a ic
co up ion affec s he access o finance o manu ac u ing small and medium en e p ises (SME).
The findings sugges ha co up ion inc eases he p obabili y o hese fi ms being financially
cons ained. The p obabili y o being financially cons ained inc eases by abou 4 o 5 pe cen age
poin s o a s anda d de ia ion ise in co up ion. The ise in he p obabili y o being financially
cons ained is smalle in coun ies whe e c edi bu eaus ope a e and c edi ma ke s unc ion mo e
eely. Pa k (2012) analyzes he impac o co up ion on bo h he banking sec o and economic
g ow h, elying on da a om 76 coun ies. The esul s indica e ha co up ion exace ba es
issues ela ed o non-pe o ming loans in he banking sec o . Addi ionally, co up ion hampe s
economic g ow h by dis up ing he alloca ion o bank esou ces, di e ing hem om iable
p ojec s o de imen al ones. This educes he quali y o p i a e in es men s, consequen ly leading
o a decline in economic g ow h.
Wellalage e al. (2019) s udy how co up ion affec s he access o c edi o small and
medium en e p ises (SMEs) in Sou h Asia. The me hods used a e he p obi es ima o and he
ins umen al a iable p obi o accoun o endogenei y. Acco dingly, he bina y dependen a i-
able measu es whe he an SME is c edi -cons ained o no . The da a is ob ained om he 2014
WBES o A ghanis an, Bangladesh, India, Nepal, and Pakis an. The esul shows ha co up ion
inc eases he likelihood o SMEs being c edi -cons ained by abou 7.6 pe cen . On he con a y,
some esea ch p o ides e idence ha b ibe y may acili a e fi ms’ access o bank c edi acili ies.
In a s udy o 14 ansi ion economies,
F
ung
´
a
ˇ
co
´
a
e al. (2015) employ fi m-le el accoun ing da a
4The Jou nal o En ep eneu ial Finance, Vol. 27, Iss. 1 [2025], A . 1
h ps://digi alcommons.peppe dine.edu/je / ol27/iss1/1
DOI: 10.57229/2373-1761.1505
o e alua e how b ibe y affec s fi ms’ o al bank deb a ios, he o al amoun o bank deb di-
ided by he o al amoun o asse s. Thei findings indica e ha highe le els o b ibe y inc ease
he o al bank deb a io, sugges ing ha b ibe y s imula es bank lending. Fu he mo e, b ibe y
acili a es sho e - e m bank deb a ios bu impedes longe - e m bank deb a ios.
Ano he s and o li e a u e s udied how ac o s ela ed o co up ion cause fi ms’
financial cons ain s. Deploying a sample o 43 coun ies, Qian and S ahan (2007) eg ess he
e ms o loan con ac s on some ins i u ional and legal a iables. Loan a ailabili y inc eases wi h
s onge c edi o igh s because banks a e mo e willing o ex end cheape loans wi h longe
ma u i ies i hey can be p o ec ed du ing bank up cy. Also, o eign banks end o ha e a highe
lending olume in coun ies wi h s onge c edi o igh s. Ano he s udy by Lo e (2003) u ilizes
da a om abou 5,000 fi ms om 36 coun ies om 1988 o 1998 o in es iga e how financial
de elopmen educes financial cons ain s. This e idence sugges s ha financial ma ke
de elopmen educes he financial cons ain s aced by fi ms, leading o mo e efficien alloca ion
o esou ces and enhancing economic g ow h.
This esea ch diffe s om pas s udies by being he fi s o s udy he ea men effec s
ac oss g oups by compa ing ea men effec s es ima es de i ed om linea and non-linea
me hods. In con as o he s udy by Xu and Yano (2017), which ocused on China, his esea ch
pape
ocuses on Nige ia, which p o ides a be e se ing o examining co up ion and i s
impac on fi ms’ financial cons ain s o some easons. Fi s , Nige ia’s co up ion le el,
acco ding o he Co up ion Pe cep ion Index (CPI) p esen ed by T anspa ency
In e na ional,
4
is highe han
ha o China, despi e he an i-co up ion campaigns and
amewo k es ablished by diffe en pas
go e nmen s. The CPI anks coun ies wo ldwide on a
scale o 0 o 100 based on he pe cei ed
le el o public sec o co up ion, whe e 100 means leas
pe cei ed public sec o co up ion and 0 means mos pe cei ed public sec o co up ion.
Nige ia’s 2015 and 2022 CPI sco es o 26 and
24 a e in he 18 h and 14 h pe cen ile while
China’s 2015 and 2022 CPI sco es o 37 and 45 lie
in he 50 h and 64 h pe cen ile o he 168
and 180 coun ies s udied, espec i ely. This e idence
shows ha co up ion has go en wo se
in Nige ia o e ime.
Second, Nige ia’s non-bank and non- a m p i a e MSMEs a e less de eloped han hose
o China. Fo ins ance, small fi ms in China con ibu e o e 60 pe cen o he coun y’s g oss
domes ic p oduc , whe eas in Nige ia, i is abou 48 pe cen . Mo eo e , unlike Xu and Yano
(2017) ha in es iga ed he impac o an i-co up ion on he financing o all Chinese fi ms, his
esea ch ocuses on how co up ion affec s he financing o MSMEs, which a e mo e likely o
ace financial cons ain s (Oli ei a and Fo una o, 2006; Hyy inen and
V
¨
a
¨
an
¨
anen
,
2006), as well
as all fi ms. In de eloping he heo e ical unde pinnings o his s udy, I build upon he p ofi
maximiza ion p oblem using a Cobb-Douglas unc ion while demons a ing how co up ion in-
c eases o dec eases he cos s o inpu s he eby affec ing fi m g ow h and consequen ly impac ing
fi ms’ abili y o access ex e nal finance.
2.1.
Theo e ical F amewo k
This s udy employs a p ofi maximiza ion model o examine how co up ion affec s fi ms’
financial cons ain s. Since co up ion can ei he sand o g ease he wheels o financial access, his
s udy’s heo e ical amewo k o mally demons a es how co up ion could hinde o s imula e
4
h ps://www. anspa ency.o g/en/cpi/2022
5
Ezeibekwe: Bu eauc a ic Co up ion and Fi ms' Financial Cons ain sPublished by Peppe dine Digi al Commons, 2025
∂C
fi ms’ access o finance by affec ing fi m g ow h. When fi ms ha e o pay b ibes o ope a e
no mally, access go e nmen business suppo se ices, o secu e con ac s, hei cos s o inpu s
and business expenses inc ease, which unde mines hei g ow h and abili y o ob ain he colla e al
o accessing finance. Howe e , in some cases, co up ion can dec ease inpu cos s o fi ms,
allowing hem o ci cum en compliance cos s, ge p e e en ial ea men , ecei e mo e subsidies,
o access esou ces a cheape a es. These ad an ages can enable fi ms o educe cos s and alloca e
esou ces mo e efficien ly.
I employ a Cobb-Douglas p oduc ion unc ion ha accoun s o wo inpu s, namely
capi al (K) and labo (L). This unc ion app oxima es an ac ual p oduc ion unc ion and is
easy o analyze. The p oduc ion unc ion o a ep esen a i e p ofi -maximizing Nige ian fi m,
wi h Y
∈
R
≥
0, K
∈
R
≥
0, and L
∈
R
≥
0, is gi en as ollows.
Y = K
α
L
β
, 0 < α < 1 and 0 < β < 1
(1)
I assume ha ou pu inc eases by less han he p opo ional change as all inpu s. Also, fi ms ha e
no ini ial unds and mus acqui e all he necessa y inpu s h ough bo owing. The o al cos (TC)
unc ion is:
TC = wL + K
(2)
The cos s o inpu s L and K a e ep esen ed by w and , espec i ely. I ep esen he effec o
co up ion as an addi ional cos o benefi (E) incu ed due o co up ion and i is p opo ional
o he le el o co up ion (C) in he economy.
E
=
ϕC, ϕ
∈
R and C
∈
R>0 (3)
The coefficien ϕ deno es he magni ude o he effec o co up ion on inpu cos s. The condi ions,
C
∈
R>0 and >
|
ϕC
|
< w, ensu e ha he co up ion le el is posi i e and inpu cos s a e ne e
ze o o nega i e.
Compu ing
∂E
gi es ϕ.
When ϕ > 0, co up ion leads o an inc ease in
inpu cos s. Fi ms e eal hei highe le el o financial cons ain s due o co up ion by choosing
subop imal inpu le els. Con e sely, when ϕ < 0, co up ion esul s in a dec ease in inpu cos s.
This causes fi ms o e eal hei lowe le el o financial cons ain s by choosing mo e op imal
inpu le els. When ϕ = 0, fi ms ace financial cons ain s ha a e un ela ed o co up ion.
Adjus ing he cos unc ion o accoun o he influence o co up ion gi es:
TC = (w + ϕC)L + ( + ϕC)K
(4)
I assume ha ϕC is iden ical o all inpu s. The op imiza ion p oblem, subjec o he inpu cos
being less han o equal o he budge cons ain , is:
max
K, L
pK
α
L
β
−
( + ϕC)K
−
(w + ϕC)L
(5)
Taking he fi s pa ial de i a i e o (5) wi h espec o K and L yields:
∂π
= αp
𝐾
α−1
L
β
= + ϕC
(6)
∂K
∂π = βp
𝐾
α
𝐿
β−1
= w + ϕC
(7)
∂L
Di iding (6) by (7) and sol ing o L, he alue o L can be ob ained.
β( + ϕC)
L = α(w + ϕC) K
(8)
6The Jou nal o En ep eneu ial Finance, Vol. 27, Iss. 1 [2025], A . 1
h ps://digi alcommons.peppe dine.edu/je / ol27/iss1/1
DOI: 10.57229/2373-1761.1505
∂C
∂C
Plugging (8) in o (6) p oduces he op imal capi al inpu , K
∗
.
𝐾∗= ( 𝑝α
𝑟+ϕ𝐶)1−β
1−α−β (𝑝β
𝑤+ϕ𝐶)β
1−α−β (9)
Plugging (9) in o (8) gi es he op imal labo inpu ,
𝐿∗= ( 𝑝α
𝑟+ϕ𝐶)α
1−α−β (𝑝β
𝑤+ϕ𝐶)1−α
1−α−β (10)
All hings equal, he op imal inpu le els ise i ϕ < 0, all i ϕ > 0, and a e unaffec ed by
co up ion i ϕ = 0. Plugging he op imal inpu s in o (1) gi es he op imal ou pu , Y
∗
, in he
p esence o co up ion.
Exp essing financial cons ain F, which is a a iable g ea e han o equal o ze o and
ze o i nega i e, as he diffe ence be ween p ofi s in he absence o co up ion and p ofi s in he
p esence o co up ion is as ollows:
F =
Π(
Y
ˆ
)
−
Π(Y
∗
, C)
(11)
F is posi i e when
Π(
Y
ˆ
)
> Π(Y
∗
, C) and ze o when
Π(
Y
ˆ
)
< Π(Y
∗
, C) o
Π(
Y
ˆ
)
= Π(Y
∗
, C),
sugges ing ha he e is no posi i e financial cons ain induced by co up ion. Taking he pa ial
de i a i e o (11) o unde s and he impac o co up ion on financial cons ain yields:
𝜕𝐹
𝜕𝐶 = 𝜙× 𝑝((𝛼+𝛽)𝜙𝐶+𝛼𝑤+𝛽𝑟)
(𝑟+𝜙𝐶)(𝑤+𝜙𝐶)(𝑟+𝜙𝐶
𝑝𝛼 )𝛼
1−𝛼−𝛽(𝑤+𝜙𝐶
𝑝𝛽 )𝛽
1−𝛼−𝛽
⏟
+
(12)
The model p edic s ha financial cons ain s become mo e s ingen when he effec o co up ion
is posi i e. This means ha he pa ial de i a i e o financial cons ain (F) wi h espec o
co up ion (C) is posi i e when ϕ is g ea e han ze o. Co up ion inc eases he cos o inpu s
o fi ms, which hinde s hei p ofi abili y and g ow h. Consequen ly, i becomes mo e difficul
o hem o aise he equi ed colla e al o access ex e nal finance. On he o he hand, financial
cons ain s weaken when he effec o co up ion is nega i e, ϕ < 0.
This implies ha ∂F
is
nega i e. Co up p ac ices educe inpu cos s by allowing hem o bypass compliance cos s o
ecei e p e e en ial ea men s, which encou ages fi m g ow h. This makes i easie o fi ms
o acqui e he colla e al necessa y o secu e ex e nal financing. When co up ion has no effec
(ϕ = 0),
∂F
becomes ze o, indica ing ha financial cons ain s a e no affec ed by co up ion.
This leads o he hypo hesis ha highe le els o co up ion inc ease financial cons ain s o
Nige ian fi ms, which I es ed in my empi ical esea ch. The heo e ical amewo k p o ides he
economic in e p e a ion o he es ima es o co up ion p o ided by he empi ical analysis.
3.
Me hodology
3.1.
Da a
To in es iga e he causal impac o co up ion on fi ms’ access o finance in Nige ia, I
analyze su ey da a om he 2014-2015 Wo ld Bank En e p ise Su ey (WBES) conduc ed in
Nige ia be ween Ap il 2014 and Feb ua y 2015. The WBES is a comp ehensi e and na ionally
ep esen a i e su ey o non-ag icul u al and non-financial p i a e en e p ises.
The sample o
7
Ezeibekwe: Bu eauc a ic Co up ion and Fi ms' Financial Cons ain sPublished by Peppe dine Digi al Commons, 2025
2003). Fo example, he absence o a anspa en and efficien ax adminis a ion and business
licensing c ea es oppo uni ies o co up p ac ices. Fi ms expe iencing hese impedimen s a e
mo e likely o seek assis ance om go e nmen agencies, exposing hem o co up officials who
may demand b ibes. The e o e, he ins umen s can p edic he ea men s a us, Co up ion,
once he o he exogenous co a ia es ha e been pa ialled ou . This condi ion can be assessed
empi ically using he weak ins umen es .
In addi ion, he ins umen s ha e no di ec ela ionship wi h fi ms’ financial access excep
h ough he fi s s age. Bo h ins umen s a e p ima ily influenced by ins i u ions, egula ions, and
adminis a i e p ocedu es, a he han financial cons ain s. Addi ionally, banks do no inqui e
abou whe he a fi m is acing obs acles wi h he ax adminis a ion ( his does no mean ha
he fi m does no pay axes) and ob aining licenses be o e deciding whe he o app o e o no
app o e a loan. The ins umen s a e no co ela ed wi h any omi ed ac o in ϵi and i, such as
he fi m’s p ofi abili y. The Sa gan es , wi h a null hypo hesis ha he sys em has a solu ion,
es s ha all es ic ions a e in e nally consis en .
4.
Resul s and Discussion
4.1.
Main Findings
The linea models a e es ima ed using he leas squa es me hod, while he non-linea mod-
els a e es ima ed using maximum likelihood. The IV is es ima ed using one ins umen and he
2SLS is es ima ed using wo ins umen s. The IV es ima o calcula es he a e age ea men e -
ec o complie s using a bina y ins umen (Imbens and Ang is , 1994; Ang is e al., 1996;
Ang is and Pischke, 2009). This examina ion u ilizes he o dina y leas squa e (OLS), IV es-
ima o , and 2SLS es ima o s o es ima e he linea model and adop s he p obi and bi a ia e
p obi o es ima e he non-linea models. The s anda d e o s o he OLS, IV, and 2SLS a e
he e oskedas ici y-consis en (HC3), as indica ed in Long and E in (2000). Fo he bi a ia e
p obi es ima o , he s anda d e o s we e calcula ed by boo s apping confidence in e als using
10,000 simula ed coefficien ec o s om he pos e io dis ibu ion o he es ima ed model pa-
ame e s. The es ima es o ρ a e significan in all cases. The a iance infla ion ac o (VIF) was
used o assess mul icollinea i y, and he esul is epo ed in Table A.1. All he alues a e close
o 1, he smalles possible alue o VIF, indica ing ha mul icollinea i y is no a p oblem.
The fi s -s age esul , epo ed in Table 5, indica es ha bo h Tax Admin and License
ha e posi i e, significan , and obus effec s on Co up ion. This holds whe he hey a e used
sepa a ely and oge he in eg ession and a e adjus ing o he e oskedas ici y. The signs o he
ins umen s om he fi s -s age eg essions a e posi i e and align wi h he hypo hesized sign. The
fi s -s age posi i e effec s o Tax Admin and License on he p obabili y o acing co up ion a e
abou 39 and 22 pe cen age poin s, espec i ely. The F-s a is ics om he h ee eg essions a e
significan a he 1 pe cen le el. The F-s a is ic inc eases om 3.7 by abou 527 pe cen , 300
pe cen , and 559 pe cen when Tax Admin, License, and Tax Admin and License combined a e
included in he eg essions, espec i ely.
14The Jou nal o En ep eneu ial Finance, Vol. 27, Iss. 1 [2025], A . 1
h ps://digi alcommons.peppe dine.edu/je / ol27/iss1/1
DOI: 10.57229/2373-1761.1505
Table 5: Fi s -S age Resul s
Dependen a iable:
Co up ion
O dina y Leas Squa e (OLS)
(1)
(2)
(3)
(4)
Tax Admin
License
0.338
∗∗∗
(0.031)
0.218
∗∗∗
0.275
∗∗∗
(0.033)
0.116
∗∗∗
Capi al Ci y
−
0.029
−
0.009
(0.023)
−
0.025
(0.023)
−
0.010
Business Ci y
Sou h
(0.019)
0.094
∗∗∗
(0.017)
−
0.047
∗∗
(0.020)
(0.018)
0.074
∗∗∗
(0.016)
−
0.018
(0.019)
(0.018)
0.075
∗∗∗
(0.016)
−
0.038
∗∗
(0.019)
(0.018)
0.068
∗∗∗
(0.016)
−
0.019
(0.019)
Manu ac u ing
−
0.001
0.004
0.001
0.004
(0.020)
(0.018)
(0.019)
(0.018)
Re ail
0.005
0.009
0.007
0.010
(0.024)
(0.022)
(0.023)
(0.022)
Fi m Age
−
0.0001
−
0.0002
0.001
0.0002
Re enue
Inno a ion
Sole P op ie o
(0.001)
−
0.004
(0.004)
−
0.0003
(0.017)
−
0.009
(0.020)
(0.001)
−
0.002
(0.004)
−
0.022
(0.015)
−
0.006
(0.020)
(0.001)
−
0.004
(0.004)
−
0.004
(0.016)
−
0.002
(0.020)
(0.001)
−
0.002
(0.004)
−
0.020
(0.015)
−
0.003
(0.020)
Manage Educa ion
0.006
∗∗
0.005
0.005
∗
0.004
(0.003)
(0.003)
(0.003)
(0.003)
Female Owne
0.009
0.005
−
0.003
−
0.001
(0.022)
(0.021)
(0.021)
(0.021)
Subsidia y Fi m
0.038
∗
0.028
0.033
∗
0.027
Cons an
(0.020)
0.799
∗∗∗
(0.080)
(0.019)
0.518
∗∗∗
(0.079)
(0.020)
0.650
∗∗∗
(0.080)
(0.019)
0.492
∗∗∗
(0.079)
Obse a ions
1,696
1,696
1,696
1,696
R2
0.026
0.152
0.103
0.169
Adjus ed R2
0.019
0.145
0.096
0.162
Residual S d. E o
0.340
0.317
0.326
0.314
F S a is ic
3.706
∗∗∗
23.169
∗∗∗
14.802
∗∗∗
24.449
∗∗∗
No e:
∗
p
<
0.1;
∗∗
p
<
0.05;
∗∗∗
p
<
0.01
The numbe s in ound b acke s () a e s anda d e o s. S anda d e o s a e he e oskedas ici y-consis en (HC3)
15
Ezeibekwe: Bu eauc a ic Co up ion and Fi ms' Financial Cons ain sPublished by Peppe dine Digi al Commons, 2025
4.1.1.
Effec s o Bu eauc a ic Co up ion on MSMEs’ Financial Cons ain s
The effec s o bu eauc a ic co up ion on MSMEs’ financial cons ain s using OLS, IV,
2SLS, p obi , and bi a ia e p obi me hods a e epo ed he e. Acco ding o he OLS es ima o
ha assumes ha Co up ion is exogenous, MSMEs (used in e changeably wi h small fi ms) ha
iden ified co up ion as an obs acle a e, on a e age, app oxima ely 0.318 mo e likely o be finan-
cially cons ained han hose ha did no iden i y co up ion as an obs acle. B ibe y inc eases
inpu cos s and inhibi s fi m g ow h, he eby making i mo e difficul o fi ms o ob ain he
colla e al equi ed o accessing ex e nal finance. The es ima e o he non-linea es ima o ha
assumes exogenei y is only 0.3 pe cen la ge bu hey a e he same o wo decimal places. The
p obi es ima o is also mo e efficien .
Acco ding o Table 6, he effec o Co up ion nea ly iples when ei he o bo h ins u-
men s a e used. Al hough he IV and 2SLS es ima es a e simila , he IV using Tax Admin as an
ins umen has he la ges es ima e. The 2SLS es ima e is close o he IV es ima e using Tax
Admin because he IV es ima o has a s onge fi s s age. U ilizing Tax Admin as an ins umen ,
co up ion is es ima ed o aise he likelihood o acing financial cons ain s o an MSME expe-
iencing ax adminis a ion hind ances by 91 pe cen age poin s. Using he same ins umen , he
bi a ia e p obi sugges s ha co up ion inc eases he p obabili y o a ep esen a i e MSME be-
ing financially cons ained by oughly 62 pe cen age poin s. The es ima e de i ed om he linea
IV es ima o is app oxima ely 47 pe cen highe han he non-linea es ima e. Fo models using
License as an ins umen , i an MSME is g appling wi h ob aining business licenses and pe mi s,
i is abou 90 pe cen age poin s mo e likely o be financially cons ained due o co up ion. The
co esponding bi a ia e p obi es ima e indica es a 64 pe cen age poin ise in he p obabili y o
becoming cons ained financially. The IV es ima e is 40 pe cen highe han he bi a ia e p obi
es ima e. The heo e ical amewo k p o ides he economic in e p e a ion o he effec . The
posi i e es ima es imply ha co up ion inc eases fi m cos s, as a esul , educing hei g ow h
and abili y o aise colla e al o bo owing.
As expec ed, IVs and 2SLS es ima o s a e less efficien han he OLS, bu he 2SLS is
mo e efficien han he IV es ima o s. The bi a ia e p obi es ima o s a e mo e efficien han
hei linea coun e pa s, whe he one o wo ins umen s a e u ilized. Also, he p obi me hod
has a supe io explana o y powe han he OLS. The Wu-Hausman es s sugges ha Co up ion
is indeed endogenous, and he weak ins umen es s confi m he ele ance o he ins umen s
used in all models. The 2SLS is used o compu e he Sa gan es , which sugges s ha he sys em
has a solu ion. The s a is ically significan
ρ
ˆ
es ima es sugges he exis ence o omi ed a iable
bias in he sys em o equa ions. The e o e, he OLS and p obi es ima o s a e inconsis en .
In Table 6, six co a ia es p oduce s a is ically significan es ima es ac oss he linea and
non-linea me hods: Capi al Ci y, Business Ci y, Sou h, Re ail, Fi m Age, and Manage Educa ion.
The analysis shows ha he e is geog aphical a ia ion in financial cons ain s, wi h MSMEs lo-
ca ed in he capi al ci y expe iencing highe le els o financial cons ain s. This could be due o
hei p oximi y o public officials, which inc eases he likelihood o paying b ibes and becoming
bank up . Addi ionally, highe ope a ional cos s and compe i ion con ibu e o his p oblem.
Fi ms in he capi al ci ies end o ace highe en s, labo cos s, and ope a ional expenses, which
equi e mo e capi al o co e . Capi al ci ies a ac a la ge numbe o businesses, leading o
inc eased compe i ion and highe financial p essu e o in es in ma ke ing, esea ch and de elop-
men , and employee benefi s o emain compe i i e. In addi ion, in ense compe i ion o unding
16The Jou nal o En ep eneu ial Finance, Vol. 27, Iss. 1 [2025], A . 1
h ps://digi alcommons.peppe dine.edu/je / ol27/iss1/1
DOI: 10.57229/2373-1761.1505
Table 6: Effec s o Bu eauc a ic Co up ion on MSMEs’ Financial Cons ain s
Dependen a iable:
Financial Cons ain s
OLS
(1)
IV
(2)
IV
(3)
2SLS
(4)
P obi
(5)
(6)
Bi a ia e P obi
(7)
(8)
Co up ion
0.318
∗∗∗
0.907
∗∗∗
0.896
∗∗∗
0.903
∗∗∗
0.319
∗∗∗
0.617
∗∗∗
0.637
∗∗∗
0.623
∗∗∗
(0.035)
(0.113)
(0.126)
(0.102)
(0.034)
(0.043)
(0.050)
(0.041)
Capi al Ci y
0.101
∗∗∗
0.118
∗∗∗
0.117
∗∗∗
0.118
∗∗∗
0.099
∗∗∗
0.092
∗∗∗
0.090
∗∗∗
0.092
∗∗∗
(0.023)
(0.026)
(0.026)
(0.026)
(0.022)
(0.019)
(0.026)
(0.019)
Business Ci y
−
0.077
∗∗∗
−
0.133
∗∗∗
−
0.132
∗∗∗
−
0.132
∗∗∗
−
0.075
∗∗∗
−
0.083
∗∗∗
−
0.083
∗∗∗
−
0.083
∗∗∗
(0.022)
(0.027)
(0.027)
(0.026)
(0.022)
(0.019)
(0.019)
(0.019)
Sou h
−
0.079
∗∗∗
−
0.051
∗
−
0.052
∗
−
0.051
∗
−
0.078
∗∗∗
−
0.055
∗∗∗
−
0.053
∗∗∗
−
0.053
∗∗∗
(0.024)
(0.027)
(0.027)
(0.027)
(0.022)
(0.019)
(0.020)
(0.020)
Manu ac u ing
0.036
0.036
0.036
0.036
0.036
0.031
0.030
0.030
(0.023)
(0.027)
(0.026)
(0.027)
(0.022)
(0.019)
(0.019)
(0.019)
Re ail
0.076
∗∗∗
0.074
∗∗
0.074
∗∗
0.074
∗∗
0.075
∗∗∗
0.065
∗∗∗
0.062
∗∗∗
0.064
∗∗∗
(0.028)
(0.031)
(0.031)
(0.031)
(0.025)
(0.023)
(0.022)
(0.023)
Fi m Age
0.004
∗∗∗
0.005
∗∗∗
0.005
∗∗∗
0.005
∗∗∗
0.004
∗∗∗
0.004
∗∗∗
0.004
∗∗∗
0.004
∗∗∗
(0.001)
(0.001)
(0.001)
(0.001)
(0.001)
(0.001)
(0.001)
(0.001)
Re enue
0.005
0.008
0.008
0.008
0.006
0.007
0.007
0.007
(0.005)
(0.005)
(0.005)
(0.005)
(0.005)
(0.005)
(0.005)
(0.005)
Inno a ion
0.006
0.006
0.006
0.006
0.006
0.002
0.003
0.002
(0.020)
(0.022)
(0.022)
(0.022)
(0.019)
(0.017)
(0.017)
(0.017)
Sole P op ie o
−
0.025
−
0.019
−
0.019
−
0.019
−
0.020
−
0.015
−
0.014
−
0.014
(0.025)
(0.028)
(0.028)
(0.028)
(0.024)
(0.021)
(0.021)
(0.021)
Manage Educa ion
−
0.005
∗
−
0.009
∗∗
−
0.009
∗∗
−
0.009
∗∗
−
0.005
−
0.004
∗∗∗
−
0.004
∗∗∗
−
0.004
∗∗∗
(0.003)
(0.004)
(0.004)
(0.004)
(0.003)
(0.001)
(0.001)
(0.001)
Female Owne
0.032
0.027
0.027
0.027
0.029
0.024
0.023
0.027
(0.026)
(0.029)
(0.029)
(0.029)
(0.025)
(0.022)
(0.021)
(0.024)
Subsidia y Fi m
0.004
−
0.018
−
0.018
−
0.018
0.004
−
0.006
−
0.007
−
0.007
(0.025)
(0.027)
(0.027)
(0.027)
(0.024)
(0.021)
(0.021)
(0.021)
Cons an
0.459
∗∗∗
−
0.012
−
0.003
−
0.009
(0.095)
(0.133)
(0.142)
(0.127)
Obse a ions
1,696
1,696
1,696
1,696
1,696
1,696
1,696
1,696
(Pseudo) R2
0.102
(0.104)
Weak IV (p)
2
×
10
−
16
2
×
10
−
16
2
×
10
−
16
Wu-Hausman (p)
5
×
10
−
16
2
×
10
−
9
2
×
10
−
16
Sa gan (p)
0.918
ρ
ˆ (S d. E .)
-0.6(0.1)
-0.6(0.1)
-0.6(0.1)
No e:
∗
p
<
0.1;
∗∗
p
<
0.05;
∗∗∗
p
<
0.01
The ins umen o (2) and (6) is Tax Admin, he ins umen o (3) and (7) is License, and he ins umen s o (4) and (8) a e
Tax Admin and License. S anda d e o s o (1), (2), (3), and (4) a e he e oskedas ici y-consis en (HC3). S anda d e o s o
he bi a ia e p obi we e calcula ed om confidence in e als boo s apped using 10,000 simula ed coefficien ec o s om he
pos e io dis ibu ion o he es ima ed model pa ame e s. (5)-(8) a e ma ginal effec s. The numbe s in ound b acke s () a e
s anda d e o s and p means p- alue. All equa ions we e es ima ed wi h an in e cep .
17
Ezeibekwe: Bu eauc a ic Co up ion and Fi ms' Financial Cons ain sPublished by Peppe dine Digi al Commons, 2025
can make i ha de o indi idual fi ms o secu e he necessa y capi al, leading o g ea e financial
cons ain s.
MSMEs loca ed in business ci ies ypically ha e be e access o financing. This is because
such ci ies ha e a la ge concen a ion o financial ins i u ions, such as banks and in es men fi ms,
which makes i easie o businesses o access financial p oduc s and se ices. Being loca ed in a
business ci y can also a ac mo e in es o s and cus ome s, leading o mo e unding and e enue
o fi ms o mee hei financial needs and g ow. As expec ed, MSMEs in sou he n Nige ia ha e
be e access o finance due o hei p oximi y o capi al ma ke s and he willingness o in es o s
o in es in mo e p ospe ous egions wi h pe cei ed s abili y and po en ial o highe e u ns.
The supe io consume spending in sou he n Nige ia could enhance he e enue and p ofi abili y
o hese fi ms, making i easie o hem o ob ain loans.
Financial cons ain s a e mo e p e alen in he e ail sub-sec o han in he manu ac u ing
o o he se ices sub-sec o s. This is p obably due o he in ense compe i ion ha exis s in he
e ail indus y, which esul s in businesses ha ing lowe p ofi s and limi ed financial powe . As
a esul , hey may s uggle o co e expenses, leading o lowe p ofi abili y. Addi ionally, olde
fi ms ace challenges in ob aining finance as hey a e mo e likely o ha e accumula ed deb o e
he yea s due o expansions o acquisi ions. Se icing deb s may limi hei abili y o ake on
addi ional deb , and he paymen o di idends o sha eholde s may u he limi he unds a ail-
able o expansion. On he o he hand, fi ms wi h mo e educa ed manage s ha e lowe financial
cons ain s. This can be a ibu ed o hei supe io financial li e acy, which leads o be e fi-
nancial decision-making. This con ibu es o he financial s abili y o he fi ms hey manage and
educes he chances o being financially cons ained. Fu he mo e, mo e educa ed manage s may
also ha e a b oade p o essional ne wo k and be e knowledge o financial ins i u ions, making
i easie o hem o secu e ex e nal unding when needed.
4.1.2.
Effec s o Bu eauc a ic Co up ion on Fi ms’ Financial Cons ain s
He e, I add he 110 la ge fi ms wi h comple e da a o he 1,696 MSMEs and analyze he
da a o all fi ms o unde s and he o e a ching pa e ns ac oss en e p ises. I include a bina y
a iable, MSME, which equals one i he es ablishmen iden ifies as an MSME and ze o o he wise.
The esul s o all fi ms a e in Table 7. The esul s p o ide he ea men effec s using
linea and non-linea me hods. Based on he IV es ima es, co up ion inc eases he p obabili y
o being financially cons ained o a ypical Nige ian fi m acing impedimen s ela ed o ax ad-
minis a ion and ob aining business licenses and pe mi s by app oxima ely 92 pe cen age poin s.
Using Tax Admin and License as ins umen s, he bi a ia e p obi es ima es imply ha co up ion
inc eases he p obabili y o being financially cons ained by 61 o 63 pe cen age poin s, espec-
i ely.
A e including la ge en e p ises wi h 100 o mo e employees, he es ima es om he
linea me hod a e app oxima ely wo pe cen la ge han he MSME IV es ima es, using Tax Ad-
min and License as ins umen s sepa a ely in eg essions. In con as , he bi a ia e p obi es ima e
declines by one pe cen o Tax Admin and wo pe cen o License. The economic in e p e a-
ions o hese es ima es a e based on he p edic ions o he heo e ical amewo k. Including la ge
en e p ises wi h 100 o mo e employees did no subs an ially change he es ima es. Howe e ,
his could be due o he limi ed ep esen a ion o hese fi ms in he sample. Ano he eason could
be ha he effec o co up ion is homogeneous ac oss fi m sizes. Fu he mo e, he diagnos ic
esul emains s able a e including la ge fi ms.
18The Jou nal o En ep eneu ial Finance, Vol. 27, Iss. 1 [2025], A . 1
h ps://digi alcommons.peppe dine.edu/je / ol27/iss1/1
DOI: 10.57229/2373-1761.1505
Table 7: Effec s o Bu eauc a ic Co up ion on Fi ms’ Financial Cons ain s
Dependen a iable:
Financial Cons ain s
OLS
(1)
IV
(2)
IV
(3)
2SLS
(4)
P obi
(5)
Bi a ia e P obi
(6)
(7)
(8)
Co up ion
0.311
∗∗∗
0.921
∗∗∗
0.915
∗∗∗
0.919
∗∗∗
0.312
∗∗∗
0.611
∗∗∗
0.626
∗∗∗
0.616
∗∗∗
(0.034)
(0.111)
(0.125)
(0.101)
(0.034)
(0.041)
(0.047)
(0.038)
MSME
0.212
∗∗∗
0.193
∗∗∗
0.193
∗∗∗
0.193
∗∗∗
0.211
∗∗∗
0.169
∗∗∗
0.166
∗∗∗
0.166
∗∗∗
(0.050)
(0.055)
(0.055)
(0.055)
(0.052)
(0.046)
(0.045)
(0.045)
Capi al Ci y
0.102
∗∗∗
0.122
∗∗∗
0.122
∗∗∗
0.122
∗∗∗
0.100
∗∗∗
0.094
∗∗∗
0.093
∗∗∗
0.094
∗∗∗
(0.022)
(0.025)
(0.025)
(0.025)
(0.021)
(0.019)
(0.019)
(0.019)
Business Ci y
−
0.073
∗∗∗
−
0.124
∗∗∗
−
0.124
∗∗∗
−
0.124
∗∗∗
−
0.070
∗∗∗
−
0.077
∗∗∗
−
0.077
∗∗∗
−
0.078
∗∗∗
(0.022)
(0.025)
(0.026)
(0.025)
(0.022)
(0.019)
(0.019)
(0.019)
Sou h
−
0.085
∗∗∗
−
0.051
∗∗
−
0.051
∗∗
−
0.051
∗∗
−
0.083
∗∗∗
−
0.057
∗∗∗
−
0.056
∗∗∗
−
0.056
∗∗∗
(0.023)
(0.026)
(0.026)
(0.026)
(0.022)
(0.019)
(0.019)
(0.019)
Manu ac u ing
0.035
0.036
0.036
0.036
0.035
∗
0.030
0.030
0.030
(0.023)
(0.026)
(0.026)
(0.026)
(0.021)
(0.019)
(0.019)
(0.019)
Re ail
0.081
∗∗∗
0.078
∗∗
0.078
∗∗
0.078
∗∗
0.080
∗∗∗
0.069
∗∗
0.066
∗∗
0.068
∗∗
(0.028)
(0.031)
(0.031)
(0.031)
(0.025)
(0.022)
(0.022)
(0.022)
Fi m Age
0.005
∗∗∗
0.005
∗∗∗
0.005
∗∗∗
0.005
∗∗∗
0.005
∗∗∗
0.004
∗∗∗
0.005
∗∗∗
0.004
∗∗∗
(0.001)
(0.001)
(0.001)
(0.001)
(0.001)
(0.001)
(0.001)
(0.001)
Re enue
0.002
0.004
0.004
0.004
0.002
0.003
0.003
0.003
(0.004)
(0.005)
(0.005)
(0.005)
(0.004)
(0.004)
(0.004)
(0.004)
Inno a ion
0.005
0.008
0.008
0.008
0.005
0.002
0.004
0.002
(0.019)
(0.022)
(0.022)
(0.022)
(0.019)
(0.017)
(0.017)
(0.016)
Sole
P op ie o
−
0.029
−
0.015
−
0.015
−
0.015
−
0.024
−
0.015
−
0.015
−
0.015
(0.024)
(0.027)
(0.027)
(0.027)
(0.023)
(0.021)
(0.020)
(0.020)
Manage Educa ion
−
0.005
−
0.009
∗∗
−
0.009
∗∗
−
0.009
∗∗
−
0.004
−
0.004
∗∗∗
−
0.004
∗∗∗
−
0.004
∗∗∗
(0.003)
(0.004)
(0.004)
(0.004)
(0.003)
(0.001)
(0.001)
(0.001)
Female
Owne
0.036
0.034
0.034
0.034
0.031
0.027
0.026
0.026
(0.026)
(0.029)
(0.029)
(0.029)
(0.024)
(0.021)
(0.021)
(0.021)
Subsidia y Fi m
−
0.005
−
0.028
−
0.028
−
0.028
−
0.005
−
0.014
−
0.014
−
0.014
(0.024)
(0.026)
(0.027)
(0.026)
(0.023)
(0.020)
(0.020)
(0.021)
Cons an
0.292
∗∗∗
−
0.191
−
0.186
−
0.190
(0.109)
(0.143)
(0.152)
(0.139)
Obse a ions
1,806
1,806
1,806
1,806
1,806
1,806
1,806
1,806
R2 (Pseudo R2)
0.113
(0.114)
Weak IV (p)
2
×
10
−
16
2
×
10
−
16
2
×
10
−
16
Wu-Hausman (p)
2
×
10
−
16
2
×
10
−
10
2
×
10
−
16
Sa gan (p)
0.956
ρ
ˆ (S d. E .)
-0.6(0.1)
-0.6(0.1)
-0.6(0.1)
No e:
∗
p
<
0.1;
∗∗
p
<
0.05;
∗∗∗
p
<
0.01
The ins umen o (2) and (6) is Tax Admin, he ins umen o (3) and (7) is License, and he ins umen s o (4) and (8)
a e Tax Admin and License. S anda d e o s o (1), (2), (3), and (4) a e he e oskedas ici y-consis en (HC3). The numbe s
in ound b acke s () a e s anda d e o s. S anda d e o s o he bi a ia e p obi we e calcula ed om confidence in e als
boo s apped using 10,000 simula ed coefficien ec o s om he pos e io dis ibu ion o he es ima ed model pa ame e s.
(5)-(8) a e ma ginal effec s. The numbe s in ound b acke s () a e s anda d e o s and p means p- alue. All equa ions we e
es ima ed wi h an in e cep .
19
Ezeibekwe: Bu eauc a ic Co up ion and Fi ms' Financial Cons ain sPublished by Peppe dine Digi al Commons, 2025
Fu he mo e, Nige ian MSMEs a e abou 17 o 19 pe cen age poin s mo e likely o be
financially cons ained han la ge fi ms. One way o explain his effec is ha small businesses
ha e lowe o al e enue han la ge fi ms, indica ing ha smalle businesses a e mo e likely o
s uggle o aise he colla e al needed o ob ain bank loans.
4.1.3.
Analyzing Fi m Size and Indus y He e ogenei y and he Deg ees o Co up ion
Ha ing obse ed he changes in he effec o Co up ion a e including la ge fi ms, I em-
ploy an in e ac ion e m o assess i he diffe ence in financial cons ain s be ween MSMEs and
la ge fi ms due o co up ion is s a is ically significan . Table 8 shows he esul o he in e ac-
ion e m be ween Co up ion and MSME. The effec o he in e ac ion e m is no s a is ically
significan , sugges ing ha he impac o co up ion on financial cons ain s aced by Nige ian
fi ms does no depend on fi m size. Simila ly, he e is no e idence ha he impac o co up ion
diffe s ac oss indus ies (Table 9). Howe e , he main conclusion ha co up ion es ic s fi ms’
access o finance emains unchanged.
Addi ionally, I employ he IV es ima o o es ima e he effec s o he deg ees o co up-
ion on fi ms’ access o finance. I e ained Financial Cons ain s as a bina y a iable. The o dinal
a iables Co up ion, Tax Admin, and License we e di ided in o fi e bina y a iables, and he su -
ey classifica ions a e used o ca ego ize he deg ee o co up ion, ax adminis a ion challenges,
and issues wi h ob aining licenses whe e 0 signifies no obs acle, 1 ep esen s a mino obs acle,
2 indica es a mode a e obs acle, 3 sugges s a majo obs acle, and 4 shows a e y se e e obs acle.
The summa y s a is ics o he new a iables a e p esen ed in Table A.2. Gi en he endogenei y
o Co up ion, I u ilize Tax Admin (Mino ) and License (Mino ) as ins umen s o Co up ion
(Mino ) and so on. The esul s o he analysis, as p esen ed in Table 10, indica e ha fi ms ha
epo ed co up ion as a “mino ” ba ie expe ience he highes le el o financial cons ain s o
bo h ins umen s. One would expec en e p ises ha pe cei e co up ion as a “ e y se e e” hin-
d ance o hei ope a ion o ha e he la ges es ima ed effec . This esul may suppo he no ion
s a ed ea lie ha while o dinal a iables allow he measu emen o diffe en le els o in ensi y,
he in e p e a ion o he diffe en ca ego ies may be mo e subjec i e han ha o a bina y a iable.
O e all, hese findings unde sco e he pe asi e and de e io a ing impac o bu eauc a ic
co up ion on Nige ian fi ms and highligh he need o effec i e measu es o comba co up ion
and educe i s ad e se effec s on fi ms and, consequen ly, economic g ow h and de elopmen .
20The Jou nal o En ep eneu ial Finance, Vol. 27, Iss. 1 [2025], A . 1
h ps://digi alcommons.peppe dine.edu/je / ol27/iss1/1
DOI: 10.57229/2373-1761.1505
Table 8: Effec s o Co up ion on Fi ms’ Financial Cons ain s By Fi m Size
Dependen a iable:
Financial Cons ain s
OLS
IV
IV
(1)
(2)
(3)
Co up ion
0.241
∗
(0.132)
1.146
∗∗
(0.500)
1.326
∗
(0.770)
MSME
0.147
0.402
0.567
(0.129)
(0.456)
(0.687)
Co up ion
×
MSME
0.075
−
0.243
−
0.436
Capi al Ci y
Business Ci y
Sou h
(0.137)
0.101
∗∗∗
(0.022)
−
0.074
∗∗∗
(0.022)
−
0.086
∗∗∗
(0.023)
(0.511)
0.123
∗∗∗
(0.025)
−
0.121
∗∗∗
(0.026)
−
0.049
∗
(0.027)
(0.780)
0.124
∗∗∗
(0.026)
−
0.119
∗∗∗
(0.027)
−
0.048
∗
(0.028)
Manu ac u ing
0.035
0.036
0.036
Re ail
Fi m Age
(0.023)
0.081
∗∗∗
(0.028)
0.005
∗∗∗
(0.001)
(0.026)
0.078
∗∗
(0.031)
0.005
∗∗∗
(0.001)
(0.026)
0.077
∗∗
(0.031)
0.005
∗∗∗
(0.001)
Re enue
0.002
0.004
0.004
(0.004)
(0.005)
(0.005)
Inno a ion
0.005
0.009
0.010
Sole P op ie o
Manage Educa ion
(0.019)
−
0.030
(0.024)
−
0.005
(0.003)
(0.022)
−
0.012
(0.029)
−
0.009
∗∗
(0.004)
(0.023)
−
0.009
(0.030)
−
0.009
∗∗
(0.004)
Female Owne
0.035
0.035
0.036
Subsidia y Fi m
Cons an
(0.025)
−
0.004
(0.024)
0.354
∗∗
(0.157)
(0.030)
−
0.028
(0.027)
−
0.391
(0.464)
(0.030)
−
0.028
(0.027)
−
0.550
(0.691)
Obse a ions
1,806
1,806
1,806
R2
0.113
Weak IV (p)
2
×
10
−
16
2
×
10
−
16
Weak IV (p)
2
×
10
−
16
2
×
10
−
16
Wu-Hausman (p)
2
×
10
−
16
1
×
10
−
9
No e:
∗
p<0.1;
∗∗
p<0.05;
∗∗∗
p<0.01
The ins umen o (2) is Tax Admin and he ins umen o (3) is License. S anda d e o s a e
he e oskedas ici y-consis en (HC3). The numbe s in ound b acke s () a e s anda d e o s and p means
p- alue. All equa ions we e es ima ed wi h an in e cep .
21
Ezeibekwe: Bu eauc a ic Co up ion and Fi ms' Financial Cons ain sPublished by Peppe dine Digi al Commons, 2025
Table 9: Effec s o Co up ion on Fi ms’ Financial Cons ain s by Indus y
Dependen a iable:
Financial Obs acle
LPM
IV
IV
(1)
(2)
(3)
Co up ion
MSME
0.234
∗∗∗
(0.062)
0.209
∗∗∗
(0.050)
0.781
∗∗∗
(0.211)
0.190
∗∗∗
(0.055)
0.893
∗∗∗
(0.234)
0.192
∗∗∗
(0.056)
Co up ion
×
Manu ac u ing
0.083
0.124
−
0.041
(0.077)
(0.260)
(0.280)
Co up ion
×
Re ail
0.199
∗
0.374
0.245
Capi al Ci y
Business Ci y
Sou h
(0.103)
0.103
∗∗∗
(0.022)
−
0.075
∗∗∗
(0.022)
−
0.084
∗∗∗
(0.023)
(0.295)
0.124
∗∗∗
(0.025)
−
0.126
∗∗∗
(0.025)
−
0.049
∗
(0.026)
(0.365)
0.122
∗∗∗
(0.025)
−
0.124
∗∗∗
(0.026)
−
0.049
∗
(0.027)
Manu ac u ing
−
0.037
−
0.071
0.071
Re ail
Fi m Age
(0.074)
−
0.092
(0.100)
0.004
∗∗∗
(0.001)
(0.233)
−
0.248
(0.268)
0.005
∗∗∗
(0.001)
(0.249)
−
0.135
(0.328)
0.005
∗∗∗
(0.001)
Re enue
0.002
0.005
0.005
(0.004)
(0.005)
(0.005)
Inno a ion
0.007
0.012
0.010
Sole P op ie o
Manage Educa ion
(0.019)
−
0.030
(0.024)
−
0.005
(0.003)
(0.022)
−
0.017
(0.028)
−
0.009
∗∗
(0.004)
(0.022)
−
0.014
(0.028)
−
0.009
∗∗
(0.004)
Female Owne
0.034
0.031
0.032
Subsidia y Fi m
Cons an
(0.026)
−
0.006
(0.024)
0.366
∗∗∗
(0.121)
(0.029)
−
0.030
(0.026)
−
0.062
(0.226)
(0.029)
−
0.029
(0.027)
−
0.169
(0.245)
Obse a ions
1,806
1,806
1,806
R2
0.116
Weak IV (p)
2
×
10
−
16
2
×
10
−
16
Weak IV (p)
2
×
10
−
16
2
×
10
−
16
Weak IV (p)
2
×
10
−
16
2
×
10
−
16
Wu-Hausman (p)
2
×
10
−
16
5
×
10
−
9
No e:
∗
p<0.1;
∗∗
p<0.05;
∗∗∗
p<0.01
The ins umen o (2) is Tax Admin and he ins umen o (3) is License. S anda d e o s a e
he e oskedas ici y-consis en (HC3). The numbe s in ound b acke s () a e s anda d e o s and p means p-
alue.
22The Jou nal o En ep eneu ial Finance, Vol. 27, Iss. 1 [2025], A . 1
h ps://digi alcommons.peppe dine.edu/je / ol27/iss1/1
DOI: 10.57229/2373-1761.1505
Table 10: Effec s o Deg ees o Co up ion on Financial Cons ain s (All Fi ms)
Dependen a iable:
Financial Cons ain s
IV
IV
(1)
(2)
Co up ion (Mino )
1.376
∗∗∗
1.711
∗
(0.350)
(0.889)
Co up ion (Mode a e)
1.100
∗∗∗
0.616
(0.408)
(0.387)
Co up ion (Majo )
0.880
∗∗
1.539
∗∗
(0.405)
(0.629)
Co up ion (Ve y Se e e)
1.157
∗∗∗
1.262
∗∗∗
(0.254)
(0.444)
MSME
0.213
∗∗∗
0.219
∗∗∗
(0.065)
(0.081)
Capi al
Ci y
0.152
∗∗∗
0.184
∗∗
(0.039)
(0.075)
Business Ci y
−
0.141
∗∗∗
−
0.168
∗∗∗
(0.032)
(0.058)
Sou h
−
0.056
0.018
(0.053)
(0.078)
Manu ac u ing
0.025
0.021
(0.032)
(0.042)
Re ail
0.058
0.058
(0.039)
(0.052)
Fi m Age
0.004
∗∗∗
0.005
∗∗
(0.001)
(0.002)
Re enue
0.001
0.002
(0.006)
(0.008)
Inno a ion
0.033
0.034
(0.031)
(0.045)
Sole P op ie o
−
0.021
0.008
(0.037)
(0.047)
Manage Educa ion
−
0.011
∗∗
−
0.013
∗
(0.005)
(0.007)
Female Owne
0.042
0.003
(0.043)
(0.053)
Subsidia y Fi m
−
0.026
−
0.028
(0.031)
(0.040)
Cons an
−
0.256
−
0.515
(0.202)
(0.394)
Obse a ions
1,806
1,806
Weak IV (Mino ) (p)
4
×
10
−
10
4
×
10
−
8
Weak IV (Mode a e) (p)
6
×
10
−
9
6
×
10
−
7
Weak IV (Majo ) (p)
7
×
10
−
11
5
×
10
−
7
Weak IV (Ve y Se e e) (p)
2
×
10
−
16
2
×
10
−
16
Wu-Hausman (p)
1
×
10
−
14
3
×
10
−
7
No e:
∗
p<0.1;
∗∗
p<0.05;
∗∗∗
p<0.01
The ins umen o (1) is Tax Admin and he ins umen o (2) is License. Co up ion (Mino ) was es ima ed using
Tax Admin (Mino ) and License (Mino ) as ins umen s and so on. The numbe s in ound b acke s () a e s anda d
e o s and p means p- alue. S anda d e o s a e he e oskedas ici y-consis en (HC3).
23
Ezeibekwe: Bu eauc a ic Co up ion and Fi ms' Financial Cons ain sPublished by Peppe dine Digi al Commons, 2025
Table A.1: VIF o OLS Resul
VIF
Co up ion
1.026
Capi al Ci y
1.354
Business Ci y
1.310
Sou h
1.196
Manu ac u ing
1.401
Re ail
1.378
Fi m Age
1.085
Re enue
1.079
Inno a ion
1.044
Sole P op ie o
1.048
Manage Educa ion
1.106
Female Owne
1.054
Subsidia y Fi m 1.164
Table A.2: Summa y S a is ics o All Fi ms
S a is ic
Mean
S . De .
Min
Max
N
Co up ion (Mino )
0.215
0.411
0
1
1,806
Co up ion (Mode a e)
0.184
0.387
0
1
1,806
Co up ion (Majo )
0.337
0.473
0
1
1,806
Co up ion (Ve y Se e e)
0.127
0.333
0
1
1,806
Co up ion (No Obs acle)
0.137
0.344
0
1
1,806
Tax Admin (Mino )
0.375
0.484
0
1
1,806
Tax Admin (Mode a e)
0.267
0.443
0
1
1,806
Tax Admin (Majo )
0.162
0.368
0
1
1,806
Tax Admin (Ve y Se e e)
0.029
0.169
0
1
1,806
Tax Admin (No Obs acle)
0.167
0.373
0
1
1,806
License (Mino )
0.378
0.485
0
1
1,806
License (Mode a e)
0.237
0.425
0
1
1,806
License (Majo )
0.095
0.293
0
1
1,806
License (Ve y Se e e)
0.015
0.121
0
1
1,806
License (No Obs acle)
0.275
0.447
0
1
1,806
Table A.3: Summa y S a is ics o Recoded Va iables
S a is ic
Mean
S . De .
Min
Max
N
Financial Cons ain s1
0.485
0.500
0
1
1,696
Co up ion1
0.654
0.476
0
1
1,696
Tax Admin1
0.461
0.499
0
1
1,696
License1
0.349
0.477
0
1
1,696
Financial Cons ain s2
0.076
0.265
0
1
1,696
Co up ion2
0.127
0.333
0
1
1,696
Tax Admin2
0.031
0.172
0
1
1,696
License2
0.016
0.125
0
1
1,696
30The Jou nal o En ep eneu ial Finance, Vol. 27, Iss. 1 [2025], A . 1
h ps://digi alcommons.peppe dine.edu/je / ol27/iss1/1
DOI: 10.57229/2373-1761.1505
