Ang, Joshua Ping; Pa alinghug, Jason
A icle
Co up ion, na u al capi al and economic de elopmen : A
dynamic GMM analysis
Re iew o Economic Analysis (REA)
P o ided in Coope a ion wi h:
In e na ional Cen e o Economic Analysis (ICEA), Wa e loo, On a io
Sugges ed Ci a ion: Ang, Joshua Ping; Pa alinghug, Jason (2025) : Co up ion, na u al capi al and
economic de elopmen : A dynamic GMM analysis, Re iew o Economic Analysis (REA), ISSN
1973-3909, In e na ional Cen e o Economic Analysis (ICEA), Wa e loo (On a io), Vol. 17, Iss. 1, pp.
95-114,
h ps://doi.o g/10.15353/ ea. 17i1.5608
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Co up ion, Na u al Capi al and Economic De elopmen :
A Dynamic GMM Analysis
Emp y 15
JOSHUA P. ANG
No h Ca olina Ag icul u al and Technical S a e Uni e si y
Emp y 15
JASON C. PATALINGHUG
Sou he n Connec icu S a e Uni e si y†
Emp y 15
Using a dynamic panel da ase o 150 coun ies o he pe iod o 2006-2018 and a wo-
s ep sys em GMM es ima ion model, his pape shows ha na u al esou ces ha e a
posi i e e ec on economic de elopmen while holding co up ion cons an . Ou indings
suppo he no ion ha na u al esou ces ha e a posi i e e ec on he economy o a na ion.
When a coun y has less co up ion, i imp o es he app op ia ion o economic gains om
na u al esou ces which se es as na u al capi al ha would d i e u he capi al
accumula ion and u he de elopmen . We also ind ha physical capi al, human capi al,
and eedom om co up ion show s ong posi i e e ec s on economic de elopmen ,
con olling o o he economic and ins i u ional a iables.
Keywo ds: Co up ion; Economic De elopmen ; Dynamic Panel S udy; Na u al
Resou ces; Physical Capi al; Human Capi al
JEL Classi ica ions: O47; Q32
1 In oduc ion
Do na u al esou ces con ibu e mo e o he economic de elopmen o a coun y wi h low le els
o co up ion compa ed o one whe e co up ion is ampan ? Na u al esou ces can be de ined
as he wo ld's s ocks o na u al asse s which include mine als, soil, ai , wa e , and all li ing
o ganisms. These esou ces can be iewed as ei he a blessing o a cu se o economic
de elopmen . The e a e s udies (Sachs & Wa ne , 1999; To ik, 2001; K ugman, 1987) which
s a e ha ha ing na u al esou ces could ha e a nega i e spillo e e ec on a coun y’s u u e
economic g ow h compa ed o o he o ms o capi al. This is called he Du ch disease o
Ang: Depa men o Economics, pang@nca .edu Pa alinghug: Depa men o Economics,
pa alinghuj1@sou he nc .edu
© 2025 Joshua P. Ang and Jason C. Pa alinghug. Licensed unde he C ea i e Commons A ibu ion -
Noncomme cial 4.0 Licence (h p://c ea i ecommons.o g/licenses/by-nc/4.0/.
A ailable a h p:// o ea.o g.
Re iew o Economic Analysis 17 (2025) 95-114
96
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nega i e esou ce e ec o he gene al economy. While o he s (B unnschweile , 2006; Allco
& Kenis on, 2018) p oduce e idence agains his heo y, Mehlum e al. (2006) show mixed
esul s (see Venables (2016), Ha anek (2016) and an De Ploeg (2011) o mo e
in o ma ion).
I is impo an o accoun o he impac o co up ion on coun ies ha ha e an abundance
o na u al esou ces because he economic gains om hese esou ces become he na u al capi al
o u u e economic de elopmen . I is he e o e impe a i e ha hese coun ies ha e good
ins i u ions (Mehlum e al.,2006) o economic g ow h because an abundance o esou ces
could lead o mo e co up ion (Lei e and Weidmann, 1999; Bha acha yya and Hodle , 2009;
Gallego e . al, 2020).
Aside om ha ing human and physical capi al in ou g ow h model (Ba o, 1991; Ba en
and Vo, 2009; Fab o and Aixala, 2012; Iqbal and Daly, 2014), we also include a a iable o
na u al capi al (Sachs and Wa ne , 1999; England, 2000; B unnschweile , 2008) o cap u e he
coun y's s ock o na u al esou ces ha p o ides i he capabili y o g ow i s economy, as well
as a a iable ha measu es he p e alence (o lack he eo ) o co up ion. We add ess he
e ec s o na u al capi al and co up ion on economic de elopmen wi h a dynamic panel da a
model es ima ed by using a wo-s ep sys em GMM es ima ion me hod. This model is based on
he c oss-coun y ca ch-up equa ion by Ba o and Sala-i-Ma in (2003), which con ols o o he
a iables, such as ins i u ional ac o s ( ade eedom, labo eedom, democ acy, business
eedom, and p ope y igh s) and economic ac o s (in la ion, and go e nmen spending). Wi h
his es ima ion, we also accoun o he unobse able coun y-speci ic e ec , and i is e icien
and obus o he e oskedas ici y and au oco ela ion.
Ou indings o e suppo o he idea ha na u al esou ces ha e a posi i e e ec on
economic de elopmen assuming he ee om co up ion a iable emains cons an . We ind
ha physical capi al, human capi al and p ope y igh s also ha e posi i e e ec s on economic
de elopmen whe eas labo eedom has a nega i e e ec on de elopmen . Howe e , we could
no ind any e ec o democ acy on economic de elopmen when we con olled o he ee
om co up ion a iable.
This pape is s uc u ed as ollows: Sec ion 2 p o ides he e iew o ela ed li e a u e.
Sec ion 3 desc ibes he da a. Sec ion 4 discusses he empi ical amewo k. Sec ion 5 epo s
he esul s and Sec ion 6 gi es us he conclusion.
2 Li e a u e Re iew
The e ha e been se e al s udies on he ole ha ins i u ions play in economic g ow h and
de elopmen . Appendix 3 p o ides a lis o he s udies discussed in his sec ion o he pape as
well as hei a ious ea u es (sample size, es ima ion me hod, ime pe iod co e ed, dependen
and independen a iables). Dias and Tebaldi (2012) used a panel da ase o 61 coun ies om
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1965 o 2005 and a mic o- ounda ions model o examine he ela ionship be ween human
capi al, ins i u ions and economic g ow h. Using sys em GMM o es ima e hei model, hey
ound ha ins i u ions do play a ole in economic g ow h. They also disco e ed ha he g ow h
o physical and human capi al helps de e mine long- un economic g ow h.
Mankiw e al. (1992) a gued ha di e ences in pe capi a GDP among na ions can bes be
explained by using an augmen ed Solow model. Thei pape had se e al main indings. Fi s ,
hey ound no signi ican di e ence be ween he elas ici y o income wi h espec o he s ock
o physical capi al and he sha e o capi al o income. Second, unde he augmen ed Solow
model, bo h he accumula ion o physical capi al and popula ion g ow h ha e a la ge e ec on
income pe capi a compa ed o he o iginal Solow g ow h model. Las ly, he model in his
pape p edic s ha coun ies wi h simila echnologies and a es o accumula ion and popula ion
g ow h should con e ge in income pe capi a. The pape hus a gues ha di e ences in pe
capi a GDP a e due o di e ences in sa ing, popula ion g ow h and educa ion among coun ies.
Boikos e al. (2023) ies o ec ea e he wo k o Mankiw e al. (1992). They upda ed he
da ase using he pe iods 1960-2015, 1970-2015 and 1990-2015. While hei esul s a e no
ully consis en wi h he Solow and augmen ed Solow models, he augmen ed model was shown
o i hei da a be e . Thei esul s also show ha human capi al has a s onge impac on
g ow h compa ed o he esul s o he Mankiw e al. (1992) pape .
Gyl ason (2001) iden i ied ou ac o s ha cause na u al esou ces o s un economic
de elopmen . These a e (1) he Du ch disease, (2) en seeking, (3) o e con idence and (4)
neglec o educa ion. He s a es ha he e is an in e se ela ionship be ween educa ion spending
and he sha e o na u al esou ces in a coun y’s weal h which leads him o conclude ha na u al
esou ces c owds ou human capi al which leads o slowe economic de elopmen . Kim and
Lin (2017) used panel da a on 40 de eloping coun ies du ing he pe iod 1960 o 2012 as well
as he e ogeneous panel coin eg a ion echniques o examine he ela ionship be ween na u al
esou ces and economic de elopmen . They ound ha coun ies abundan in na u al esou ces
de elop slowe han hose wi h ewe esou ces hus gi ing mo e p oo o he cu se o na u al
esou ces.
Ca alcan i and No o (2005) in es iga ed how economic de elopmen is a ec ed by
ins i u ions. Using ou pu pe wo ke as a p oxy o de elopmen , hei esul s showed ha a
one pe cen imp o emen in ins i u ions leads o a i e pe cen inc ease in ou pu pe wo ke .
Thei esul s also show ha an imp o emen in ins i u ions leads o a bigge inc ease in ou pu
pe wo ke in lowe income coun ies as opposed o hose wi h highe incomes.
Hashim Osman e al. (2012) examined he ole ins i u ions played in he economic
de elopmen o 27 Sub-Saha an A ican coun ies. Using panel da a om he pe iod 1984 o
2003 and a ixed e ec s model, hey ound ha ha he quali y o ins i u ions and he s abili y
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o he go e nmen a e signi ican ac o s in he economic de elopmen o hese na ions.
Howe e , hey did no ind co up ion o be a signi ican o ce ha a ec s de elopmen .
Hall e al. (2010) de eloped a g ow h model whe e he p oduc i i y and alloca ion o capi al
depends on he quali y o a na ion’s ins i u ions. Using a da ase o 96 coun ies ha co e s he
pe iod o 1980 o 2000, hei esul s show ha inc eases in physical and human capi al can lead
o a coun y ha ing economic g ow h only i i has good ins i u ions.
Vedia-Je ez and Chasco (2015) used a da ase o 10 Sou h Ame ican coun ies o e he
pe iod o 1960 o 2008 o examine he long- un de e minan s o economic g ow h in he egion.
Using sys em GMM o es ima e hei model, hey disco e ed ha human and physical capi al
accumula ion a e i al condi ions o inc easing economic g ow h. Also, e icien poli ical
ins i u ions a e a key componen o g ow h as hey help s imula e p oduc i i y and a ac
capi al.
Nas een e al. (2015) used bo h o dina y leas squa es (OLS) and panel GMM o in es iga e
he long- e m impac o ins i u ions on in es men and economic g ow h. Using a da ase o 94
coun ies o he pe iod 1985-2009, hei esul s showed ha coun ies wi h mo e economic
eedom ha e highe economic g ow h pe uni o inpu as well as highe le els o spending on
physical and human capi al in es men . Thei s udy also poin s ou ha an independen and
unbiased judicial sys em ha p o ec s p ope y igh s is c ucial o economic g ow h.
Ta a es and Waczia g (2001) looked a he ole o democ acy in economic g ow h. They
used a di e se da ase o 65 de eloped and de eloping coun ies o e he pe iod o 1970-1989.
Using h ee-s age leas squa es (3SLS), hey ound ha democ acy has a nega i e bu mode a e
e ec on economic g ow h. This is because mo e democ acy inc eases human capi al
accumula ion and lowe s physical in es men a es. This means ha democ acy helps lowe -
income g oups by expanding access o educa ion, bu i comes a he expense o accumula ing
physical capi al. Democ acy also leads o lowe income inequali y which can lead o highe
g ow h. The au ho s o he s udy poin ou ha democ a ic ins i u ions p o ide a ade-o
be ween economic cos s and social bene i s.
Dawson (1998) analyzes he empi ical ela ionship be ween ins i u ions, in es men and
g ow h. Using a da ase o 85 coun ies o e he pe iod o 1975-1990 and ixed e ec s
es ima ion, he showed ha economic eedom has a signi ican and posi i e e ec on g ow h.
This is because economic eedom has a di ec e ec on g ow h h ough o al ac o p oduc i i y
and an indi ec e ec h ough in es men . Thus, p omo ing economic eedom is impo an in
achie ing g ow h. The s udy also shows ha ee-ma ke ins i u ions as well as poli ical and
ci il libe ies a e con ibu o s o g ow h.
Fa as and Miho ’s (2013) pape shows ha policy ola ili y has a s ong and nega i e
impac on g ow h. They can show his by c ea ing measu es o policy ola ili y ou o a da ase
o 93 coun ies o e he pe iod 1960-2007. Using pooled OLS and ixed e ec s models, hey
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disco e ha coun ies ha agg essi ely use disc e iona y iscal policy when i is unnecessa y
end o ha e lowe economic g ow h. One o hei main indings is ha ins i u ions a ec
economic g ow h h ough hei impac on policy a he han hei use as a cons ain on he chie
execu i e o a na ion.
Gwa ney e al. (2006) examine he ela ionship be ween ins i u ions and in es men and
how ins i u ional quali y a ec s g ow h h ough i s impac on he p oduc i i y and le el o
in es men . Using a da ase o 94 coun ies du ing he pe iod 1980-2000, hei indings show
ha coun ies wi h be e quali y ins i u ions ha e mo e g ow h pe uni o in es men and
a ac a highe le el o p i a e in es men as a sha e o GDP. The pape s a es ha ins i u ional
quali y has a sizeable indi ec impac on p i a e in es men . Thei analysis also shows ha
highe g ow h does no lead o be e ins i u ions. In ac , i goes he opposi e di ec ion as lowe
g ow h would lead o bigge imp o emen s in ins i u ional quali y.
Issahaku e al. (2018) ied o es o wo ela ed hypo heses. The i s one is he g ow h
impo a ion hypo hesis which s a es ha coun ies wi h weak ins i u ions will impo g ow h in
he o m o in e na ional emi ances. The second one is he u gency hypo hesis which s a es
ha he e is a high u gency o apply emi ances e icien ly in coun ies wi h weak ins i u ions
because o limi ed al e na i es. I hus implies ha he e is a high oppo uni y cos o
misalloca ing emi ance e enues. Using da a o 106 coun ies du ing he pe iod 1996-2013
and wo-s age leas squa es (2SLS) es ima ion, hey we e able o show s ong e idence o he
exis ence o hese wo hypo heses. They disco e ha emi ances os e g ow h in low income
and lowe middle-income coun ies bu no in high income o uppe middle-income coun ies.
The au ho s poin ou ha low income and lowe middle-income coun ies ha e no ye
bene i ed om he g ow h di idends o ins i u ions and ha ins i u ions and emi ances a e
subs i u es o one ano he .
Sidek and Asu ay (2021) analyze he impac o go e nmen expendi u es on economic
g ow h while con olling o ins i u ional ac o s using a da ase ha included 30 de eloped and
91 de eloping coun ies o e he pe iod 1984-2017. Using wo-s ep sys em GMM es ima ion,
hey disco e ed ha go e nmen expendi u es, whe he hey a e go e nmen de elopmen o
go e nmen consump ion expendi u es, ha e a posi i e e ec on economic g ow h i good
ins i u ions a e p esen . This implies ha good go e nance leads o he e icien use o public
unds.
3 Da a
We collec ed da a on 150 coun ies o 12 yea s (2006-2018) om di e en sou ces. We use
he eal pe capi a G oss Domes ic P oduc (GDP) (in cons an 2010 US$) wi h he da a
collec ed om The Wo ld Bank (WB) and smoo hened wi h a cen e ed mo ing a e age o a
yea . We also collec ed da a on he mean yea s o schooling om he Uni ed Na ions (UN) as
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a p oxy o human capi al. This ep esen s he a e age numbe o yea s o educa ion ecei ed
by people aged 25 and olde . We use g oss capi al o ma ion (% o GDP), which consis s o
ou lays on addi ions o he ixed asse s o he economy plus ne changes in he le el o
in en o ies, as a p oxy o physical capi al. We also use o al na u al esou ces en s (% o
GDP), whe e he o al na u al esou ces en s a e he sum o oil en s, na u al gas en s, coal
en s (ha d and so ), mine al en s, and o es en s, as a p oxy o na u al capi al. Da a on
g oss capi al o ma ion and o al na u al esou ces en s we e ob ained om The Wo ld Bank.
The Co up F ee a iable is he Co up ion Index collec ed om T anspa ency
In e na ional’s Co up ion Pe cep ions Index ha measu es he le el o co up ion in a na ion
wi h ze o as he mos co up and 100 as he leas co up . The Democ acy a iable comes om
he Economis In elligence Uni Democ acy Index which measu es he quali y o democ acies
based on ac o s such as elec o al plu alism, o m o go e nmen , poli ical pa icipa ion, ci il
libe y and poli ical cul u e, wi h ze o as he leas democ a ic and 100 as he mos democ a ic.
The da a on he annual in la ion a e (de i ed om he consume p ice index) is collec ed om
he In e na ional Mone a y Fund (IMF).
We also collec ed da a om The He i age Founda ion. This da a includes he Go e nmen
Spending Index ha measu es all le els o go e nmen expendi u es, he Labo F eedom Index
ha measu es egula ions conce ning labo employmen , he T ade F eedom Index ha
measu es he absence o a i and non- a i ba ie s ha a ec impo s and expo s o goods
and se ices, he Business F eedom Index ha measu es he abili y o ha e a business, he
o e all bu den o egula ion as well as he e iciency o go e nmen in he egula o y p ocess,
and P ope y Righ s ha measu es he deg ee o which a coun y’s laws p o ec p i a e p ope y
igh s and he deg ee o which i s go e nmen en o ces hose laws. All he indices a e measu ed
wi h ze o as ha ing he leas eedom and 100 as ha ing he mos eedom.
4 The Model
Ou baseline model is a wo-s ep sys em Gene alized Me hod o Momen s (GMM) es ima ion
model on dynamic panel da a. I can be e-w i en om he c oss-coun y ca ch-up equa ion o
Ba o and Sala-i-Ma in (2003) o assess he ins i u ional ac o s, wi h ou main ocus on
eedom om co up ion and na u al esou ces, as:
ln𝑌
𝑖𝑡 =
ln 𝑌
𝑖𝑡−1 +
1𝐻𝑢𝑚𝑎𝑛𝐶𝑎𝑝𝑖𝑡𝑎𝑙𝑖𝑡 +
2𝑃ℎ𝑦𝑠𝑖𝑐𝑎𝑙𝐶𝑎𝑝𝑖𝑡𝑎𝑙𝑖𝑡 +
3𝑁𝑎𝑡𝑢𝑟𝑎𝑙𝐶𝑎𝑝𝑖𝑡𝑎𝑙𝑖𝑡 +
4𝐶𝑜𝑟𝑟𝑢𝑝𝑡𝐹𝑟𝑒𝑒𝑖𝑡 +
5𝑇𝑟𝑎𝑑𝑒𝐹𝑟𝑒𝑒𝑑𝑜𝑚𝑖𝑡 +
6𝐼𝑛𝑓𝑙𝑎𝑡𝑖𝑜𝑛𝑖𝑡 +
7𝐿𝑎𝑏𝑜𝑟𝐹𝑟𝑒𝑒𝑑𝑜𝑚𝑖𝑡 +
8𝐷𝑒𝑚𝑜𝑐𝑟𝑎𝑐𝑦𝑖𝑡 +
𝑖+ 𝑑𝑡+
𝑖𝑡 (1)
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whe e
= 1 +
and
is he condi ional con e gence ac o , 𝑌
𝑖𝑡 is he eal GDP pe capi a,
𝑌
𝑖𝑡−1 is he p e ious yea eal GDP pe capi a,
𝑖 he unobse able coun y-speci ic e ec , 𝑑𝑡
is he yea ly ime dummy, εi is he e o e m, and
a e he coe icien s.
In Equa ion (1), 𝐻𝑢𝑚𝑎𝑛𝐶𝑎𝑝𝑖𝑡𝑎𝑙, 𝑃ℎ𝑦𝑠𝑖𝑐𝑎𝑙𝐶𝑎𝑝𝑖𝑡𝑎𝑙, and 𝑁𝑎𝑡𝑢𝑟𝑎𝑙𝐶𝑎𝑝𝑖𝑡𝑎𝑙 a e he capi al-
ela ed explana o y a iables o human capi al, physical capi al, and na u al capi al
espec i ely. Fo he baseline model, we ha e 𝑇𝑟𝑎𝑑𝑒𝐹𝑟𝑒𝑒𝑑𝑜𝑚, 𝐼𝑛𝑓𝑙𝑎𝑡𝑖𝑜𝑛, 𝐿𝑎𝑏𝑜𝑟𝐹𝑟𝑒𝑒𝑑𝑜𝑚,
and 𝐷𝑒𝑚𝑜𝑐𝑟𝑎𝑐𝑦 as con ol a iables o he T ade F eedom Index, he in la ion a e, he Labo
F eedom Index, and he Democ acy Index espec i ely. We also include 𝑃𝑟𝑜𝑝𝑒𝑟𝑡𝑦𝑅𝑖𝑔ℎ𝑡,
𝐵𝑢𝑠𝑖𝑛𝑒𝑠𝑠𝐹𝑟𝑒𝑒𝑑𝑜𝑚 , and 𝐺𝑜𝑣𝑒𝑟𝑛𝑚𝑒𝑛𝑡𝑆𝑝𝑒𝑛𝑑𝑖𝑛𝑔 as o he con ol a iables o p ope y
igh s, he Business F eedom Index, and go e nmen spending.
The e exis s unobse ed he e ogenei y in he c oss-sec ion o coun ies which is pe sis en
and has highe a iance han he e o e ms. We hus es ima e he dynamic panel da a using
ixed e ec s and GMM models o con ol o endogenei y and unobse ed he e ogenei y.
Howe e , we could possibly encoun e he p oblem o ha ing se e ely weak ins umen s i we
use he di e ence GMM model (A ellano and Bond, 1991). The e o e, we employ he sys em
GMM es ima o (A ellano and Bo e , 1995; Blundell and Bond, 1998).
Acco ding o Roodman (2009), ha ing a sample wi h he ime dimension being g ea e han
he numbe o coun ies can weaken he ins umen s which could lead o in alida ing some
asymp o ic esul s and speci ica ion es s (Teixei a and Quei os, 2016; Iqbal and Daly, 2014).
Hence, ou wo-s ep sys em GMM es ima ion is done wi h panel da a consis ing o 150
coun ies o e a pe iod o 12 yea s. We use wo-s ep, a he han one-s ep sys em GMM,
because i is mo e e icien and obus o he e oskedas ici y and au oco ela ion (Roodman,
2009). We use he collapsed ins umen ma ix o esol e he issue o o e i ing endogenous
a iables.
5 Resul s
In his sec ion, we p esen he esul s om he dynamic panel da a analysis in Table 1 ha
a e es ima ed by Blundell and Bond (1998)’s wo-s ep sys em GMM es ima ion me hod using
a collapsed ins umen ma ix ha includes ime dummy a iables and using obus s anda d
e o s co ec ed o ini e samples (Windmeije -co ec ed s anda d e o s).
Table 1 shows he es ima ion esul s o Equa ions 1 o 4 o he dependen a iable which
is eal GDP pe capi a (in na u al log). A ellano-Bond Tes s AR (1) show ha he speci ied
dynamic model is app op ia e when we ejec he null hypo hesis a he 1% signi icance le el
o all esul s. A ellano-Bond Tes s AR (2) show ha he GMM lag is a good ins umen when
we ail o ejec ha he e exis s second-o de se ial-co ela ion a he 10% signi icance le el
o all esul s. The Hansen es s show ha he esul s a e wi h alid ins umen s being speci ied
because we ail o ejec he null hypo hesis ha he ins umen s a e in alid a he 10%
Re iew o Economic Analysis 17 (2025) 95-114
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signi icance le el. All esul s ha e a ime pe iod o 12 yea s ha is less han he numbe o
g oups, and his ensu es alid asymp o ic esul s and speci ica ion es s, acco ding o Roodman
(2009).
The esul s show ha he accumula ion o bo h human and physical capi al ha e s ong
posi i e e ec s wi h s a is ical signi icance (a ei he he 1% o 5% le el) on economic
de elopmen o all equa ions, simila o he indings o Ba en and Vo (2009), Fab o and Aixala
(2012), and Iqbal and Daly (2014). Holding e e y hing else cons an , a one-uni inc ease in
physical capi al is associa ed wi h an app oxima ely 0.06% inc ease in eal GDP pe capi a in
Equa ions 1 o 4. Holding e e y hing else cons an , a one-uni inc ease in human capi al is
associa ed wi h a 2.17%, 2.12%, 1.62%, and 1.55% inc ease in eal GDP pe capi a in Equa ions
1 o 4, espec i ely. Wi h a popula ion ha has mo e educa ional a ainmen and mo e capi al
o ma ion o e ime, he highe le el o human capi al accumula ed has a g ea e e ec o
specializa ion in capi al-in ensi e indus ies ha would gi e ise o a g ea e gain on economic
de elopmen .
The na u al capi al a iable shows a posi i e e ec on g ow h (simila o B unnschweile ,
2006; Allco and Kenis on, 2018) wi h s a is ical signi icance a ei he he 5% o 10% le el.
Holding e e y hing else cons an , e e y one-pe cen age poin inc ease in na u al esou ces as a
pe cen o GDP is associa ed wi h a 0.26%, 0.28%, 0.3%, and 0.29% inc ease in he le el o
economic de elopmen in Equa ions 1 o 4, espec i ely. We also ind ha being less co up
has a s ong posi i e e ec , which is s a is ically signi ican a he 5% o 10% le el, on
economic de elopmen . Holding e e y hing else cons an , e e y one-uni inc ease in he ee
om co up ion a iable is associa ed wi h a 0.33%, 0.32%, 0.23%, and 0.24% inc ease in he
le el o economic de elopmen in Equa ions 1 o 4 espec i ely. This is consis en wi h
Mehlum e al. (2006), which inds a posi i e na u al esou ces e ec when a coun y endowed
wi h na u al esou ces has good ins i u ions. When a coun y has an abundance o na u al
esou ces, co up ion causes an une en app op ia ion on he gains om hese esou ces ha
would o he wise se e as he na u al capi al o allow mo e people o be be e o om
accumula ing o he o ms o capi al o achie e highe economic de elopmen . We did ind an
in e es ing no e on democ acy. We ailed o ind i s connec ion wi h economic de elopmen
when we con olled o eedom om co up ion. We also ound ha ade eedom has a
mode a e posi i e e ec on de elopmen in equa ion 4. Ou esul s ea i m he indings o
Lei e and Weidmann (1999) which said ha he es ablishmen o s ong, co up ion- ee
ins i u ions ha secu e p ope y igh s plays an impo an ole in p omo ing economic
de elopmen when a coun y is endowed wi h na u al esou ces.
AUTHOR(S) LAST NAME 4 spaces Abb e ia ed i le
109
www.Ro EA.o g
Hall e al.
(2010)
1980-
2000
96
coun ies
OLS
g ow h o
ou pu pe
wo ke
Human Capi al: a e age
yea s o schooling pe
wo ke om Baie ,
Dwye , and Tamu a
(2006)
Physical Capi al: pe pe ual
in en o y me hod used o
calcula e he physical
capi al s ock pe wo ke
using annual in es men
da a om Hes on e al.
(2000)
Ins i u ions: da a on " isk
o exp op ia ion" om he
In e na ional Coun y Risk
Guide (ICRG)
Dias and
Tebaldi
(2012)
1965-
2005
61
coun ies
one-s ep
sys em
GMM wi h
obus
co a iance
ma ix
GDP g ow h
a e pe
capi a
Human Capi al: a e o
e u n om educa ion
Psacha opoulos (1994)
Physical Capi al: pe pe ual
in en o y sys em (Eas e ly
and Le ine (2001)
Ins i u ions: a io o people
wi h pos -seconda y
educa ion o people wi h
no schooling, Poli y-IV
measu e o democ acy and
au oc acy
Hashim
Osman e al.
(2012)
1984-
2003
27
coun ies
Fixed e ec s
G ow h a e
o eal pe
capi a GDP
Ins i u ional quali y: (a)
socioeconomic condi ions,
(b) co up ion, (c)
go e nmen s abili y and
(d) e hnic ensions, da a
comes om In e na ional
Coun y Risk Guide
Fa as and
Miho (2013)
1960-
2007
93
coun ies
pooled OLS
and ixed
e ec s
g ow h a e
o ou pu pe
capi a
Human capi al: p ima y
school en ollmen
Physical capi al:
in es men p ice
Ins i u ions: poli ical
ola ili y
Re iew o Economic Analysis 17 (2025) 95-114
110
www.Ro EA.o g
Nas een e al.
(2015)
1985-
2009
94
coun ies
OLS and
panel GMM
g ow h a e
o eal GDP
pe capi a
Human capi al: adul
li e acy a e
Physical capi al:
in es men as sha e o
GDP
Ins i u ions: poli ical
libe y, ci il libe y and
economic eedom indices
aken o m F eedom
House
Vedia-Je ez
and Chasco
(2015)
1960-
2008
10
coun ies
sys em
GMM
G ow h:
in e -
quad ennial
g ow h o
log GDP pe
capi a, FDI:
log o eign
di ec
in es men
as a
pe cen age
o GDP
Human Capi al: A e age
pe cen age o he log o
wo king age popula ion
wi h seconda y educa ion
Physical capi al: Log g oss
ixed capi al o ma ion
Ins i u ions: ins i u ional
quali y index o m No is
(2009), ins i u ional
cons ain s on chie
execu i es index om
Poli y IV, con ac -
in ensi e money om IFS
Kim and Lin
(2017)
1990-
2012
40
coun ies
Mul i- ac o
eg ession
Log o eal
GDP pe
capi a
Na u al esou ces: (a)
sha e
o p ima y expo s in GDP
and (b) e enues om
na u al esou ces
(including ene gy,
mine als, and o es y) as a
sha e o GDP
Issahaku e al
(2018)
1996-
2013
106
coun ies
2SLS
g ow h in
pe capi a
GDP
Human capi al: labo o ce
pa icipa ion a e
Physical capi al: g oss
ixed capi al o ma ion
Ins i u ions: composi e
measu e o ins i u ional
quali y de i ed om he
six go e nance indica o s
de elopmen by
Kau mann, K aay and
Mas uzzi (2011)
AUTHOR(S) LAST NAME 4 spaces Abb e ia ed i le
111
www.Ro EA.o g
Sidek and
Asu ay
(2021)
1984-
2017
121
coun ies
sys em
GMM
GDP g ow h
a e
Human capi al: annual
change in popula ion,
Physical capi al:
in es men Ins i u ions: 12
a iables (go e nmen
s abili y, socio economic
condi ions, in es men
p o ile, in e nal con lic ,
ex e nal con lic ,
co up ion, mili a y in
poli ics, eligious ensions,
law and o de , e hnic
ensions, democ a ic
accoun abili y,
bu eauc acy) om ICRG
Boikos e al.
(2023)
1960-
2015
139
coun ies
OLS
ln GDP pe
wo king-age
pe son in
2015
Human capi al: (a) he
seconda y educa ional
a ainmen as a % o he
popula ion aged 15-64
( o al) om he Ba o-Lee
da ase (Ba o and Lee
2013) and (b) he human
capi al index, based on
yea s o schooling and
e u ns o educa ion om
he Penn Table
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