Uddin, Muhammad Raihan; Sadik, Na is; Rahman, Md. Mominu
A icle
Globaliza ion, physical capi al, and human capi al nexus
wi h economic g ow h: E idence om BIMSTEC
Resea ch in Globaliza ion
P o ided in Coope a ion wi h:
Else ie
Sugges ed Ci a ion: Uddin, Muhammad Raihan; Sadik, Na is; Rahman, Md. Mominu (2025) :
Globaliza ion, physical capi al, and human capi al nexus wi h economic g ow h: E idence om
BIMSTEC, Resea ch in Globaliza ion, ISSN 2590-051X, Else ie , Ams e dam, Vol. 10, pp. 1-11,
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Globaliza ion, physical capi al, and human capi al nexus wi h economic
g ow h: e idence om BIMSTEC
Muhammad Raihan Uddin, Na is Sadik , Md. Mominu Rahman
*
Bangladesh Ins i u e o Go e nance and Managemen (BIGM), Dhaka, Bangladesh
ARTICLE INFO
Keywo ds:
Globaliza ion
Economic g ow h
Human capi al
Physical capi al
BIMSTEC
ABSTRACT
Policymake s’ main ocus is economic g ow h, pa icula ly in a eas like BIMSTEC whe e s uc u al p oblems and
globaliza ion’s in luences g ea ly a ec pa hs o de elopmen . Wi h special ocus on he mode a ing unc ion o
globaliza ion, his s udy examines he link be ween physical capi al, human capi al, and economic g ow h. The
pape analyzes he ela ionships using ad anced econome ic me hods including c oss-sec ional dependency,
s a iona i y, coin eg a ion, and ully modi ied o dina y leas squa es using panel da a om 1990 o 2019. The
esul s show a complica ed link: while physical and human capi al ha e posi i e di ec e ec s on g ow h,
globaliza ion nega i ely mode a es hese ela ionships in BIMSTEC due o he egion’s di e se economic s uc-
u es and di e en deg ees o in eg a ion wi h global ma ke s, so ans o ming hem in o s onge g ow h d i e s
in he long un. Dynamic o dina y leas squa es and ARDL models’ obus ness es ing help o alida e he esul s.
Especially, al hough he associa ions main ain in he long- un, he sho un shows no app eciable in luence.
These indings ha e signi ican consequences o policy since hey encou age BIMSTEC na ion o icials o ma ch
globaliza ion wi h capi al accumula ion policies in o de o suppo sus ainable economic de elopmen . This
pape p o ides a ou e o c ea ing long- e m de elopmen p og ams ha include wo ldwide possibili ies in o
egional economic s a egy.
1. In oduc ion
Physical and human capi al play pi o al oles in p omo ing economic
g ow h by enhancing p oduc i i y, e iciency, os e ing inno a ion, and
building a skilled wo k o ce ha suppo s sus ainable de elopmen
(Pomi e al., 2021; Rahman e al., 2024b; Saleh e al., 2020). Global-
iza ion boos s economic g ow h by enhancing physical capi al h ough
he ans e o ad anced echnologies, esou ces, and in es men s ha
imp o e p oduc i i y in a eas like machine y and in as uc u e
(Coulibaly e al., 2018; Zaidi e al., 2019). I also s eng hens human
capi al by enabling knowledge exchange, skill de elopmen , and access
o global ma ke s, which inc eases labo p oduc i i y and wo k o ce
capabili ies (Asongu & Tchamyou, 2020; S o ko a & Sukalo a, 2020).
Se e al economic heo ies discuss he oles o physical and human
capi al in economic g ow h. Solow (1996) unde sco ed he impo ance
o physical capi al and echnological p og ess in economic g ow h.
Rome (1989) ocused on human capi al and inno a ion as impo an
de e minan s o sus ained g ow h. Mankiw e al. (1995) ex ended he
Solow model by inco po a ing bo h physical and human capi al o
explain a ia ions in economic pe o mance. In his con ex ,
in es men s in human capi al, such as educa ion and heal hca e, and
physical capi al like in as uc u e, machine y, and echnology, signi i-
can ly d i e economic g ow h (Bawono, 2021; Kei a, 2016; Wu & Wu,
2022).
Çepni e al. (2019) unde sco e a nonlinea co ela ion be ween
inequali y and economic g ow h, accen ua ing he impo ance o he
human capi al o physical capi al a io. None heless, hei app oach ails
o examine how globaliza ion migh a ec his ela ionship, c ea ing a
signi ican oid in comp ehending he wide en i onmen in which
hese p ocesses unc ion. Likewise, al hough Liu & Agbola (2014)
illus a e a posi i e co ela ion be ween human capi al and economic
g ow h in China’s elec onics sec o , hei esea ch ails o accoun o
he po en ial impac o globaliza ion on his connec ion wi hin he
BIMSTEC amewo k. This o e sigh is no ably impo an , as global-
iza ion b ings mul iple elemen s—such as in e na ional ade, in es -
men lows, and echnology ans e — ha can ei he augmen o
impede he e icacy o capi al accumula ion (Wang e al., 2023).
Mo eo e , he p e ailing esea ch p edominan ly emphasizes a na ow
ange o economic indica o s o assess globaliza ion, neglec ing i s wide
economic, social, and poli ical aspec s. Rao e al. (2011) con end ha
p io esea ch has o e looked he ex ensi e ami ica ions o
* Co esponding au ho .
E-mail add ess: [email p o ec ed] (Md.M. Rahman).
Con en s lis s a ailable a ScienceDi ec
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h ps://doi.o g/10.1016/j. esglo.2025.100284
Recei ed 26 No embe 2024; Recei ed in e ised o m 14 Ap il 2025; Accep ed 15 Ap il 2025
Resea ch in Globaliza ion 10 (2025) 100284
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2590-051X/© 2025 The Au ho (s). Published by Else ie L d. This is an open access a icle unde he CC BY license ( h p://c ea i ecommons.o g/licenses/by/4.0/ ).
globaliza ion, especially on i s mul i ace ed e ec s. This limi ed
pe spec i e cons ains he comp ehension o how globaliza ion engages
wi h human and physical capi al in a ec ing economic g ow h, pa ic-
ula ly in a eas wi h he e ogeneous economic amewo ks and di e ing
de elopmen al phases. Ou s udy in es iga es he mode a ing in luence
o globaliza ion on he link be ween physical and human capi al and
economic g ow h in BIMSTEC na ions. We o e a ho ough analysis o
how globaliza ion a ec s capi al accumula ion and economic g ow h in
a egion ma ked by conside able economic di e si y, by examining he
mul i ace ed dimensions o globaliza ion h ough he amewo k o bo h
ypes o capi al. This me hod add esses a signi ican de iciency in he
li e a u e and p o ides inno a i e pe spec i es on he in e ac ion be-
ween globaliza ion, capi al, and economic g ow h in eme ging
economies.
The BIMSTEC na ions—Bangladesh, India, Myanma , S i Lanka,
Thailand, Bhu an, and Nepal— o m a s a egically signi ican egional
bloc, loca ed a he in e sec ion o Sou h and Sou heas Asia. Wi h hei
di e se economic s uc u es, abundan esou ces, and g owing eco-
nomic po en ial, hese coun ies hold immense p omise o egional and
global economic in eg a ion. In his con ex , he ole o globaliza ion
becomes c ucial, as i in luences he dynamics be ween physical capi al,
human capi al, and economic g ow h. BIMSTEC is a egion wi h com-
mon challenges like weak in as uc u e, and di e ences in educa ion
and skills. They also ade, in es , and sha e esou ces, implying ha
hei g ow h is in e connec ed. Exis ing s udies ha e explo ed he eco-
nomic g ow h dynamics o BIMSTEC na ions, ocusing on a ious
con ibu ing ac o s o he han physical and human capi al. Towhid &
Kiyo o (2019) examined he e ec o ade openness on economic
g ow h wi hin BIMSTEC coun ies, while Kuma e al. (2023) analyzed
he ela ionship be ween o eign di ec in es men and economic
g ow h in he egion. Howe e , his esea ch akes a no el app oach by
in es iga ing he impac o physical and human capi al on he egion’s
economic g ow h, wi h globaliza ion se ing as a mode a ing in luence.
I explo es how globaliza ion changes he impac o physical and human
capi al on g ow h in a way ha pas s udies ha e no in es iga ed. Wi h
his app oach, his s udy seeks o explain how BIMSTEC coun ies,
expe iencing c oss-bo de spillo e e ec s, can wo k oge he o g ow
as e and bene i om hei egional connec ions.
This esea ch aims o in es iga e he ela ionship be ween physical
capi al, human capi al, and economic g ow h, ocusing on he mode -
a ing e ec s o globaliza ion in BIMSTEC coun ies. The speci ic objec-
i es a e:
1. To ind he ela ionship be ween physical capi al and economic
g ow h,
2. To examine how human capi al a ec s economic g ow h, and.
3. To in es iga e whe he globaliza ion s eng hens o weakens
capi al (physical and human) and economic g ow h ela ionships.
This esea ch signi ican ly con ibu es o he li e a u e on BIMSTEC
coun ies by examining he in ica e linkages among physical capi al,
human capi al, and economic g ow h, especially wi hin he amewo k
o globaliza ion. This a icle speci ically in es iga es he mode a ing
in luence o globaliza ion on economic g ow h, an a ea ha has been
insu icien ly examined in he BIMSTEC se ing, in con as o p io
s udies ha p edominan ly concen a ed on he di ec impac s o
physical and human capi al (Iqbal e al., 2022). This inno a i e me hod
enhances comp ehension o globaliza ion’s impac on he e icacy o
bo h capi al ypes in s imula ing economic g ow h, deli e ing essen ial
insigh s o policymake s in de eloping economies. Mo eo e , he e-
sul s o his pape possess signi ican policy ami ica ions. By demon-
s a ing ha globaliza ion diminishes he connec ion be ween physical
and human capi al and economic g ow h, we unde sco e he necessi y
o BIMSTEC na ions o implemen policies ha enhance he syne gies
be ween globaliza ion and capi al accumula ion. These measu es a e
c ucial o p omo ing sus ainable economic de elopmen in a egion
cha ac e ized by di e en economic s uc u es and di e ing de elop-
men al s ages, whe e localized policies can p o oundly in luence g ow h
ajec o ies (Juknys e al., 2016; Wang e al., 2023).
The es o he pape includes ‘Li e a u e e iew’ in sec ion 2,
‘Me hodology’ in sec ion 3, ‘Resul s and Discussions’ in sec ion 4,
‘Conclusion’ in sec ion 5.
2. Li e a u e e iew
2.1. Physical capi al and economic g ow h
The accumula ion o physical capi al is widely acknowledged as a
c i ical d i e o economic g ow h due o i s abili y o enhance p o-
duc i e capaci y and s eng hen economic in as uc u e (Sen, 2013).
The ounda ional Solow-Swan model posi s ha economic g ow h is
p ima ily d i en by capi al and labo accumula ion, alongside echno-
logical ad ancemen s (Dykas e al., 2023). In his model, physical cap-
i al—encompassing machine y, in as uc u e, and equipmen —ac s as
a undamen al inpu in he p oduc ion p ocess, acili a ing e iciency
and inc eased ou pu (Solow, 1956).
Physical capi al os e s economic g ow h h ough mul iple mecha-
nisms ha enhance p oduc i i y, e iciency, and echnological adop ion
ac oss an economy (Gong e al., 2012; Li e al., 2015). A i s co e,
physical capi al di ec ly impac s p oduc ion p ocesses by allowing i ms
o p oduce mo e ou pu wi h he same amoun o labo , hus inc easing
p oduc i i y (Solow, 1956). In es men s in ad anced machine y o
echnology educe labo equi emen s pe uni o ou pu , eeing up
labo esou ces o o he p oduc i e ac i i ies. This imp o es e iciency
and p oduc i i y, inc easing o e all economic ou pu and GDP g ow h
(Ga dine e al., 2012).
Mo eo e , physical capi al suppo s he de elopmen o a conduci e
en i onmen o bo h domes ic and o eign in es men s (Casi &
Nomencla u e
Ac onyms
DOLS Dynamic o dina y leas squa e
ARDL Au o eg essi e Dis ibu ed Lag
ECGR Economic g ow h
PCAP Physical capi al
HCAP Human capi al
GLBN Globaliza ion
INFL In la ion
FDIN Fo eign di ec in es men
GFDV Global inancial de elopmen
PCD Pesa an CD
BP-LM B eusch-Pagan LM
PS-LM Pesa an Scaled LM
GDP G oss domes ic p oduc
WDI Wo ld de elopmen indica o
PPP Pu chasing powe pa i ies
BoP Balance o paymen
SD S anda d de ia ion
VIF Va iance In la ion Fac o
CSD C oss-sec ional dependence
CIPS C oss-Sec ionally Augmen ed IPS
BIMSTEC Bangladesh, India, Myanma , S i Lanka, Thailand,
Bhu an, and Nepal
CADF C oss-Sec ionally Augmen ed Dickey-Fulle
FMOLS Fully Modi ied O dina y Leas Squa es
BCS-LM Bias-Co ec ed Scaled LM
M.R. Uddin e al.
Resea ch in Globaliza ion 10 (2025) 100284
2
Resmini, 2017). Imp o ed in as uc u e acili a es ade by connec ing
ma ke s domes ically and in e na ionally, which allows o economies o
scale and be e esou ce alloca ion (Be gs and & Egge , 2007).
Ano he c ucial way physical capi al d i es economic g ow h is by
enabling echnology adop ion and di usion, especially in de eloping
economies. When coun ies in es in mode n equipmen , hey can mo e
e ec i ely implemen new echnologies ha enhance p oduc i i y and
os e inno a ion (C espi & Zuniga, 2012).
Fo he BIMSTEC egion, physical capi al in es men holds s a egic
impo ance in p omo ing economic in eg a ion and g ow h, as hese
na ions wo k o build in as uc u e ha enhances connec i i y and
ade lows ac oss bo de s (Hossain, 2023). Regional s udies ocusing on
Sou h and Sou heas Asia unde sco e ha exis ing in as uc u e gaps
limi g ow h po en ial; howe e , a ge ed in es men s in physical cap-
i al yield subs an ial mul iplie e ec s on p oduc i i y and ade wi hin
he egion (Wigna aja & Ga i, 2024).
Li e al. (2015) analyzed China’s economic g ow h om 1981 o
2010 and ound ha physical and human capi al played a key ole,
mainly due o capi al accumula ion and highe labo p oduc i i y.
Loayza & So o (2002) examined he g ow h expe iences o de eloping
coun ies and asse ha s a egic in es men in in as uc u e and
p oduc i e asse s can signi ican ly bols e economic esilience and
g ow h ou comes. Ano he empi ical esea ch by Ghu a & Hadjimichael
(1996) on A ican economies inds a posi i e co ela ion be ween capi al
o ma ion in p oduc i e sec o s and GDP g ow h a es, unde sco ing he
impac o a ge ed physical capi al in es men s on economic
pe o mance.
Thus, physical capi al is essen ial o economic g ow h, as i boos s
p oduc i i y and suppo s long- e m de elopmen . Wi hin he BIMSTEC
con ex , whe e in as uc u e and p oduc i e in es men a e p io i ized
o acili a e egional economic in eg a ion and coope a ion, in es men
in physical capi al ep esen s a c i ical ac o o os e ing sus ainable
g ow h and enhancing economic s abili y ac oss membe na ions. Gi en
he exis ing s udies, he ollowing hypo hesis he e o e can be
pos ula ed:
H1. Physical capi al posi i ely and signi ican ly in luences economic
g ow h in BIMSTEC egions.
2.2. Human capi al and economic g ow h
Human capi al d i es economic g ow h, pa icula ly h ough i s ole
in enhancing p oduc i i y, inno a ion, and economic esilience (Ahmed
e al., 2020). The heo y o endogenous g ow h, as de eloped by Rome
(1990) and Lucas (1988), posi s ha in es men s in human capi al-
—such as educa ion, heal h, and skill de elopmen —can lead o sus-
ained economic g ow h by inc easing he p oduc i i y o he wo k o ce.
Human capi al en iches he capaci y o indi iduals o gene a e new
ideas and adap o echnological ad ancemen s, he eby os e ing a sel -
ein o cing cycle o g ow h (Da id, 2000).
Ba o (1991) and Mankiw e al. (1992) ind ha coun ies wi h
highe le els o educa ion and skill de elopmen end o expe ience
as e economic g ow h. These s udies show ha educa ion boos s in-
di idual p oduc i i y and sp eads knowledge ac oss indus ies, which
imp o es o e all economic pe o mance. The heal h componen o
human capi al is also i al o economic g ow h, pa icula ly in de el-
oping egions (G a Zi in & Neidell, 2013). In a panel analysis, Pel-
inescu (2015) examined he ole o human capi al in d i ing economic
g ow h, measu ed as g oss domes ic p oduc (GDP) pe capi a. The
model demons a ed a s a is ically signi ican and posi i e ela ionship
be ween GDP pe capi a and key indica o s o human capi al: inno a i e
capaci y, as indica ed by pa en coun s, and wo k o ce quali ica ions,
ep esen ed by seconda y educa ion le els. Meh a a & Musai (2013)
explo es he link be ween economic g ow h and human capi al in
de eloping coun ies, speci ically looking a how educa ion a ec s GDP
om 1970 o 2010. Using panel da a me hods, including uni oo and
coin eg a ion es s, he indings show ha in es men and economic
g ow h signi ican ly in luence educa ion, bu educa ion does no ha e a
no able impac on GDP o in es men in he sho o long e m. This
implies ha in hese na ions, economic expansion and capi al in es -
men d i e educa ional p og ess a he han educa ion d i ing economic
g ow h.
Mo eo e , human capi al plays a key ole in sp eading echnological
inno a ion, helping de eloping economies mode nize indus ies and
imp o e compe i i eness (Das & D ine, 2020). I se es as a b idge,
helping coun ies u ilize global knowledge and d i e egional economic
g ow h (Asongu & Tchamyou, 2020). In ligh o his, BIMSTEC na ions
mus make s a egic in es men s in educa ion, heal h, and skill de el-
opmen o ensu e long- e m g ow h and economic esilience. Gi en he
exis ing s udies, he ollowing hypo hesis can be pos ula ed:
H2. Human capi al posi i ely and signi ican ly in luences economic
g ow h in BIMSTEC egions.
2.3. Mode a ing e ec s o globaliza ion
Globaliza ion can s eng hen he ela ionship be ween physical
capi al and economic g ow h by acili a ing he low o esou ces,
echnology, and in es men s ac oss bo de s (Coulibaly e al., 2018;
G ossman & Helpman, 2015). Th ough globaliza ion, coun ies gain
access o ad anced echnologies and capi al goods ha can imp o e he
p oduc i i y o physical capi al, such as machine y, in as uc u e, and
equipmen (Sachs, 2000). This inc eased e iciency leads o highe
ou pu and s imula es economic g ow h.
Mo eo e , globaliza ion opens up la ge ma ke s o goods and se -
ices and allows economies o achie e economies o scale and inc ease
e u ns on physical capi al (Mukhe jee, 2018). Fo eign di ec in es -
men (FDI), a key aspec o globaliza ion, p o ides essen ial capi al and
knowledge ans e , pa icula ly in de eloping coun ies. I leads o
u he enhancemen s in he p oduc i i y o physical capi al (La i e al.,
2018). By in eg a ing wi h he global economy, coun ies can accele a e
inno a ion, a ac in es men s ha mode nize hei in as uc u e, and
imp o e he o e all economic e iciency o physical capi al, he eby
os e ing sus ainable g ow h (Shabi , 2024).
Simila ly, globaliza ion can enhance he ela ionship be ween
human capi al and economic g ow h by acili a ing knowledge ans e ,
echnological ad ancemen s, and access o global ma ke s (Jahange
e al., 2022). Th ough globaliza ion, coun ies gain g ea e exposu e o
ad anced echnologies and inno a i e p ac ices. I leads o he de el-
opmen o mo e p oduc i e and skilled wo k o ces (Beliz e al., 2019).
This exposu e helps imp o e labo p oduc i i y, as seen in de eloping
na ions whe e wo ke s adap o he echnology and skills o ad anced
economies, os e ing p oduc i i y gains (Ra e al., 2019).
Globaliza ion also causes inc eased mobili y o labo and he di u-
sion o educa ion and aining s anda ds ac oss bo de s (Bound e al.,
2021). This mobili y leads indi iduals o acqui e skills om mo e
de eloped coun ies and b ing his expe ise back home, which c ea es a
eedback loop ha s eng hens local human capi al. Addi ionally, in-
e na ional ade and o eign di ec in es men (FDI) con ibu e o
economic g ow h by c ea ing mo e jobs and imp o ing he demand o
skilled labo (Nguyen, 2020). As human capi al expands and adap s
h ough global in eg a ion, i os e s a mo e compe i i e economy and
highe GDP g ow h (Osiobe, 2019). Thus, he ollowing hypo hesis can
be pos ula ed:
H3. Globaliza ion s eng hens he ela ionship be ween physical
capi al and economic g ow h in BIMSTEC egions.
H4. Globaliza ion s eng hens he ela ionship be ween human
capi al and economic g ow h in BIMSTEC egions.
Based on he e iew o ela ed s udies, his s udy de elops Fig. 1 as a
concep ual model.
M.R. Uddin e al.
Resea ch in Globaliza ion 10 (2025) 100284
3
3. Me hods
3.1. Da a and a iables
This s udy analyzes he syne gy be ween globaliza ion, physical
capi al, and human capi al, and hei collec i e in luence on economic
g ow h in BIMSTEC coun ies o e he pe iod 1990–2019. The da ase
comp ises annual panel da a sou ced om epu able da abases, ensu ing
consis ency and eliabili y. The key a iables include economic g ow h,
physical capi al, human capi al, and globaliza ion, supplemen ed by
ele an con ol a iables such as in la ion, o eign di ec in es men ,
and global inancial de elopmen .
Economic g ow h (ECGR) is he dependen a iable and is measu ed
as annual GDP in cons an 2015 US dolla s, ex ac ed om he Wo ld
De elopmen Indica o s (WDI) da abase. I se es as he p oxy o
assessing economic pe o mance ac oss he BIMSTEC na ions. Physical
capi al (PCAP), a c i ical de e minan o economic ou pu , is ep esen ed
by he sha e o g oss capi al o ma ion a cu en pu chasing powe
pa i ies (PPPs). Da a o physical capi al a e sou ced om he Penn
Wo ld Table (PWT 10.01). Human capi al (HCAP) e lec s he ole o
educa ion in os e ing economic g ow h. This a iable is measu ed using
he g oss en ollmen a io in seconda y educa ion (%) and is ob ained
om he WDI da abase. GLBN cap u es he mul idimensional impac o
globaliza ion. The KOF Globaliza ion Index, which inco po a es eco-
nomic, social, and poli ical dimensions, is used o measu e his a iable.
Da a a e accessed om he WDI da abase.
In addi ion o he key a iables, he s udy inco po a es he ollowing
con ol a iables o add ess po en ial con ounding ac o s: INFL is
measu ed by he annual pe cen age change in consume p ices, in la ion
da a is sou ced om he WDI da abase. This a iable accoun s o
mac oeconomic s abili y in he analysis. FDIN is ep esen ing he in low
o FDI, his a iable is measu ed in ne balance o paymen s (BoP) e ms
a cu en US dolla s, sou ced om he WDI. GFDV a iable, measu ed
by liquid liabili ies in millions o cons an 2010 US dolla s, se es as a
p oxy o inancial ma ke ma u i y. Da a o his a iable a e ex ac ed
om he WDI. Table 1 p o ides a de ailed o e iew o he a iables,
hei de ini ions, measu emen app oaches, and da a sou ces, ensu ing
anspa ency in he da a collec ion p ocess.
3.2. Theo y and model speci ica ion
This s udy is based on he neoclassical g ow h model de eloped by
Mankiw which includes human capi al as a de e minan o economic
g ow h. I s a s om a Cobb–Douglas p oduc ion unc ion:
Yi =Ki
α
Hi β(Ai Li )1−
α
−β,(1)
This unc ion conside s ou ac o s o p oduc ion: physical capi al (K),
human capi al (H), labo (L), and le el o echnology (A).
▪ Basic model:
ECGR = (PCAP,HCAP,GLBN,INFL,FDIN,GFDV)(2)
Speci ic models
▪ Model-1:
ECGRi =Ci +β1PCAPi +β2GLBNi +β3INFLi +β4FDINi +β5GFDVi +
ε
i
(3)
▪ Model-2:
ECGRi =Ci +β1HCAPi +β2GLBNi +β3INFLi +β4FDINi +β5GFDVi +
ε
i
(4)
▪ Model-3:
Fig. 1. Concep ual model o he s udy.
Table 1
Sign, measu emen , and sou ces o a iables.
Sign Va iables Measu emen Sou ces
Key a iables
ECGR Economic g ow h Annual GDP (cons an 2015 US$) WDI
PCAP Physical capi al Sha e o g oss capi al o ma ion a
cu en PPPs
PWT
10.01
HCAP Human capi al School en ollmen , seconda y (% g oss) WDI
GLBN Globaliza ion The KOF Globalisa ion Index measu es
he economic, social, and poli ical
dimensions o globaliza ion.
WDI
Con ol a iables
INFL In la ion In la ion, consume p ices (annual %) WDI
FDIN Fo eign di ec
in es men
Fo eign di ec in es men , ne (BoP,
cu en US$)
WDI
GFDV Global inancial
de elopmen
Liquid liabili ies in millions (cons an
2010 US$)
WDI
M.R. Uddin e al.
Resea ch in Globaliza ion 10 (2025) 100284
4
ECGRi =Ci +β1PCAPi +β2PCAPi ×GLBNi +β3GLBNi +β4INFLi
+β5FDINi +β6GFDVi +
ε
i
(5)
▪ Model-4:
ECGRi =Ci +β1HCAPi +β2HCAPi
×GLBNi +β3GLBNi +β4INFLi +β5FDINi +β6GFDVi +
ε
i
(6)
▪ Model-5 ( inal combined model):
ECGRi =Ci +β1PCAPi +β2HCAPi +β3PCAPi ×GLBNi +β4HCAPi
×GLBNi +β5GLBNi +β6INFLi +β7FDINi +β8GFDVi +
ε
i
(7)
He e, he subsc ip s i and ep esen he c oss-sec ional uni s (coun ies)
and ime pe iods (yea s), espec i ely. Economic g ow h se es as he
dependen a iable ac oss equa ions (2) h ough (7). The key indepen-
den a iables a e physical capi al (PCAP), human capi al (HCAP), and
Globaliza ion (GLBN). Fo eign di ec in es men (FDIN), in la ion
(INFL), and global inancial de elopmen (GFDV) a e he con ol a i-
ables. Finally, c is he cons an , β deno es he coe icien s o he
explana o y a iables, ‘ ×’ indica es in e ac ion e m, and
ε
is he e o
e m.
4. Resul s and Discussions
4.1. Desc ip i e s a is ics and co ela ions
Table 2 delinea es he summa y s a is ics o he examined ac o s o
BIMSTEC na ions om 1990 o 2019. The a e age alues e lec modes
le els o economic g ow h (24.47), physical capi al (24.68), and glob-
aliza ion (43.86), whe eas human capi al (59.04) exhibi s g ea e a i-
abili y. In la ion demons a es he g ea es ola ili y (SD =7.69), wi h a
peak o 57.07 and a ough o −0.90, indica ing economic ins abili y a
some in e als. The skewness and ku osis da a demons a e ha ECGR
and INFL exhibi signi ican skewness and lep oku osis, indica ing
p onounced a ia ions. Con e sely, o he a iables display app oxi-
ma ely no mal dis ibu ions, cha ac e ized by modes skewness and
signi ican ku osis. These igu es unde sco e he a ied economic e-
ali ies ac oss he BIMSTEC a ea.
4.2. Co ela ion analysis
Table 3 displays he co ela ion analysis o he examined a iables,
indica ing he s eng h and di ec ion o hei linea co ela ions. The
indings demons a e ha all co ela ion coe icien s a e below 0.90,
indica ing a lack o mul icollinea i y among he a iables. ECGR ex-
hibi s a signi ican posi i e co ela ion wi h globaliza ion (0.57), o eign
di ec in es men (0.68), and global inancial de elopmen (0.770),
al hough i s co ela ion wi h physical capi al (-0.24) and human capi al
(0.28) is compa a i ely less. The co ela ions among he emaining
a iables a e likewise low o mode a e, wi h no e idence o high
collinea i y. Mo eo e , he Va iance In la ion Fac o (VIF) alues
emain below 3, subs an ia ing he asse ion ha mul icollinea i y is no
an issue. The esul s alida e he app op ia eness o he a iables o
eg ession analysis, as hey exhibi minimal in e dependence (see Fig. 2
o sca e plo ma ix).
4.3. C oss-sec ional dependency, s a iona i y, and coin eg a ion
Table 4 displays he ou comes o he c oss-sec ional dependence
(CSD) es s o he examined a iables, e alua ing he p esence o un-
obse ed common componen s o in e dependencies wi hin he panel
da a. The assessmen s comp ise he B eusch-Pagan LM (BP-LM), Pesa an
Scaled LM (PS-LM), Bias-Co ec ed Scaled LM (BCS-LM), and Pesa an
CD (PCD) exams.
The B eusch-Pagan LM es assesses c oss-sec ional dependence by
agg ega ing he squa ed pai wise co ela ion coe icien s o esiduals
o e all c oss-sec ional uni s. The o mula is:
LM =∑
N−1
i=1∑
N
j=i+1
T
ρ
2
ij
Whe e,
ρ
ij pai wise co ela ion coe icien o esiduals be ween uni s
i and j. N is he numbe o c oss-sec ional uni s, and T is he ime pe iods.
The Pesa an Scaled LM es adjus s he BP-LM es by scaling i o
add ess challenges in ex ensi e panels. The o mula is:
LMPS =1
N(N−1)∑
N−1
i=1∑
N
j=i+1
T
√
ρ
2
ij
The Bias-Co ec ed The Scaled LM es modi ies he PS-LM es o
accoun o bias in ini e samples, pa icula ly when bo h T and N a e
subs an ial. The equa ion is as ollows:
LMBCS =1
N(N−1)∑
N−1
i=1∑
N
j=i+1
T
√(
ρ
2
ij −1
T)
The Pesa an CD es di ec ly assesses he mean co ela ion o e-
siduals, pa icula ly use ul o panels whe e T is minimal in compa ison
o N. The o mula is:
CD =
2T
N(N−1)
√∑
N−1
i=1∑
N
j=i+1
ρ
ij
All a iables—ECGR, PCAP, HCAP, GLBN, INFL, FDIN, and
GFDV—exhibi e y signi ican es s a is ics (p- alue =0.000), signi-
ying obus c oss-sec ional dependence. This highligh s he impo ance
o u ilizing a s a iona i y es o subsequen econome ic models.
Table 5 displays he s a iona i y esul s de i ed om second-
gene a ion uni oo es s, speci ically he C oss-Sec ionally
Augmen ed IPS (CIPS) and C oss-Sec ionally Augmen ed Dickey-Fulle
(CADF) es s, which conside c oss-sec ional dependence in panel
da a. The CADF es u ilizes c oss-sec ional a e ages o he a iable and
i s lagged alues o mi iga e c oss-sec ional dependence. The o mula o
he examina ion is:
Δyi, =
α
i+βiyi, −1+γiy −1+∑
φ
j=1
∅i,jΔyi, −1+∈i,
Whe e, yi, is he a iable o in e es o c oss-sec ional uni i a ime ,
y −1 is he c oss-sec ional a e age o yi, −1, Δ is he i s di e ence
ope a o , φ is he op imal lag leng h, and ∈i, is he e o e m. The null
hypo hesis (H0) is ha yi, has a uni oo (βi=0), while he al e na i e
hypo hesis (Ha) is ha yi, is s a iona y (βi<0).
The CIPS es b oadens he CADF me hodology o panel da a by
a e aging he CADF es s a is ics o e all c oss-sec ional uni s. The CIPS
s a is ic is calcula ed as ollows:
Table 2
Summa y s a is ics o he in es iga ed a iables.
ECGR PCAP HCAP GLBN INFL FDIN GFDV
Mean 24.47 24.68 59.04 43.86 8.27 19.44 10.26
Maximum 28.58 51.83 130.93 73.43 57.07 24.65 14.57
Minimum 1.90 5.65 0.05 21.46 −0.90 10.82 4.45
SD 2.63 9.06 24.87 13.75 7.69 2.90 2.48
Skewness −3.14 0.58 0.27 0.22 3.10 −0.36 −0.37
Ku osis 27.20 3.66 2.84 2.03 16.11 2.50 2.44
M.R. Uddin e al.
Resea ch in Globaliza ion 10 (2025) 100284
5
CIPS =1
N∑
N
i=1
CADFi
Whe e, N is he numbe o c oss-sec ional uni s, and CADFi is he es
s a is ic om he CADF es o uni i. The null hypo hesis (H0) is ha all
se ies ha e a uni oo , while he al e na i e hypo hesis (Ha) is ha a
Table 3
Analysis o co ela ion be ween he in es iga ed a iables.
ECGR PCAP HCAP GLBN INFL FDIN GFDV VIF
ECGR 1.00 −0.24*** 0.28*** 0.57*** −0.16** 0.68*** 0.70*** 1.112
PCAP 1.00 0.08 0.11 −0.38*** −0.10 −0.29*** 1.215
HCAP 1.000 0.79*** −0.29*** 0.48*** 0.31*** 1.267
GLBN 1.00 −0.38*** 0.75*** 0.61*** 2.124
INFL 1.00 −0.11 0.00 1.563
FDIN 1.00 0.87*** 2.334
GFDV 1.00 1.549
No e: ***=p <0.01, **=p <0.05, *=0 <0.1.
Fig. 2. Sca e ma ix.
Table 4
CSD es o he in es iga ed a iables.
Va iables BP-LM PS-LM BCS-LM PCD
ECGR S a . 333.708 48.252 48.131 13.001
p- alue 0.000 0.000 0.000 0.000
PCAP S a . 233.319 32.762 32.641 6.189
p- alue 0.000 0.000 0.000 0.000
HCAP S a . 529.106 78.402 78.282 22.977
p- alue 0.000 0.000 0.000 0.000
GLBN S a . 528.872 78.366 78.246 22.957
p- alue 0.000 0.000 0.000 0.000
INFL S a . 114.087 14.364 14.243 8.515
p- alue 0.000 0.000 0.000 0.000
FDIN S a . 248.910 35.167 35.047 14.679
p- alue 0.000 0.000 0.000 0.000
GFDV S a . 425.076 62.350 62.230 17.873
p- alue 0.000 0.000 0.000 0.000
No e: BP =B eusch Pagan LM, PS=Pesa an Scaled LM, BCS =Bias Co ec ed
Scaled LM, PCD=Pesa an CD.
Table 5
S a iona i y es using CIPS and CADF.
Va iables CIPS CADF
- alue p- alue - alue p- alue
ECGR −1.982 >=0.10 −3.672 <=0.05
PCAP −2.647 <=0.01 −3.692 <=0.05
HCAP −0.150 >=0.10 −2.859 >=0.10
GLBN −2.107 >=0.10 −3.439 <=0.05
INFL −2.311 <=0.10 −4.938 <=0.01
FDIN −2.351 <=0.10 −4.731 <=0.01
GFDV −2.573 >=0.10 −3.959 <=0.05
M.R. Uddin e al.
Resea ch in Globaliza ion 10 (2025) 100284
6
leas some se ies a e s a iona y.
Table 5 demons a es ha all a iables a e s a iona y a le el ac-
co ding o bo h es s. Bo h es s asce ain ha ECGR, PCAP, HCAP,
GLBN, INFL, FDIN, and GFDV lack uni oo s. The indings indica e ha
he da ase is app op ia e o econome ic analysis wi hou necessi a ing
di e encing o manipula ion o a ain s a iona i y.
Table 6 p esen s he indings o he Ped oni and Wes e lund coin-
eg a ion es s, which assess he exis ence o a long- e m link among he
a iables. The Ped oni es , a i s -gene a ion coin eg a ion assessmen ,
yields signi ican ou comes o bo h he Panel -S a is ic (18.095, p =
0.000) and he Panel ADF-S a is ic (−2.299, p =0.012), demons a ing
e idence o coin eg a ion. Likewise, he Wes e lund es , a second-
gene a ion coin eg a ion es ha conside s c oss-sec ional depen-
dence, p oduces a signi ican es s a is ic (4.129, p =0.000), so ein-
o cing he p esence o a long- un link. The consis en esul s om bo h
ounds o coin eg a ion es s con i m he exis ence o coin eg a ion,
hence legi imizing he applica ion o coin eg a ed eg ession models
such as FMOLS o DOLS o subsequen s udy.
4.4. Long- un es ima ions
The Fully Modi ied O dina y Leas Squa es (FMOLS) app oach is
employed o long- e m es ima ions as i e icien ly mi iga es endoge-
nei y and se ial co ela ion in coin eg a ed panel da a, hence yielding
eliable and unbiased coe icien es ima es (Rahman e al., 2024a).
Gi en he long- un coin eg a ion e idenced in Table 6, FMOLS is an
app op ia e echnique o examining he ela ionships among a iables.
FMOLS does his by inco po a ing non-pa ame ic modi ica ions o
mi iga e any eedback e ec s be ween independen a iables and he
e o e m, while also ec i ying se ial co ela ion wi hin he esiduals.
All models exhibi R-squa ed alues exceeding 50%, indica ing mode -
a e o s ong explana o y powe .
The empi ical esul s demons a e ha bo h physical and human
capi al posi i ely a ec economic g ow h ac oss all model speci ica ions
(Model A–E), unde sco ing he essen ial ole o capi al accumula ion
and human esou ce de elopmen in os e ing economic p ospe i y in
he BIMSTEC a ea. The subs an ial posi i e in luence o globaliza ion on
ECGR indica es ha mo e in eg a ion in o global ma ke s p omo es
economic g ow h, likely ia imp o ed ade, echnology ans e , and
o eign in es men s. The in e ac ion e ms PCAP ×GLBN and HCAP ×
GLBN demons a e nega i e impac s on ECGR, sugges ing ha global-
iza ion diminishes he g ow h-p omo ing unc ion o bo h physical and
human capi al. This may be asc ibed o ac o s including heigh ened
o eign i al y, capi al ou lows, o a dispa i y be ween indigenous ca-
pabili ies and global ma ke equi emen s. Globaliza ion may con ibu e
o b ain d ain, weakening he domes ic pool o skilled labo . Likewise,
o eign di ec in es men s and ex e nal economic dependencies may
cons ain he domes ic use o physical capi al, diminishing i s impac on
long- e m g ow h. These indings unde sco e he in ica e ela ionship
be ween globaliza ion and economic de elopmen , indica ing ha
al hough globaliza ion p omo es g ow h, i may simul aneously impose
s uc u al limi a ions ha hinde he e icacy o domes ic capi al and
labo esou ces.
4.5. Robus ness check
4.5.1. DOLS
Robus ness checks a e c ucial in empi ical analysis o con i m he
dependabili y and consis ency o esul s ac oss a ious es ima ing
me hods, ensu ing ha he conclusions a e no con ingen upon he
selec ed app oach (Huang e al., 2024). To alida e he obus ness o he
indings de i ed om FMOLS in Table 7, we u ilize he Dynamic O di-
na y Leas Squa es (DOLS) app oach in Table 8, which accoun s o
endogenei y and se ial co ela ion by inco po a ing leads and lags o he
independen a iables. The DOLS esul s co obo a e he FMOLS ind-
ings, indica ing pe sis en bene icial impac s o GLBN on ECGR and
analogous mode a ing e ec s o GLBN on he in e ac ions be ween
PCAP, HCAP, and ECGR. The consis ency among me hodologies en-
hances he alidi y o he analysis, ins illing highe con idence in he
conclusions on he dynamics o economic g ow h in he examined
se ing.
4.5.2. ARDL
The u iliza ion o he Au o eg essi e Dis ibu ed Lag (ARDL) model
acili a es a comp ehensi e analysis o he sho - un and long- un in-
e ac ions among he a iables ( e e o Table 9). The indings demon-
s a e ha whe eas physical capi al, human capi al, and globaliza ion
a o ably a ec long- e m economic g ow h, he in e ac ion e ms
(PCAP ×GLBN and HCAP ×GLBN) show nega i e impac s, aligning
wi h p io es ima es. In he sho e m, no signi ican connec ions we e
de ec ed, indica ing ha he g ow h consequences o capi al accumu-
la ion, human capi al, and globaliza ion mani es o e ime a he han
p oducing ins an e ec s. This disco e y highligh s he necessi y o
con inuous in es men s in capi al and wo k o ce de elopmen , along-
side s a egic globaliza ion policies, o a ain endu ing economic success
in he BIMSTEC egion.
4.6. G ange causali y es
The G ange causali y es ou comes p esen ed in Table 10 indica e
subs an ial causal linkages be ween c i ical a iables and economic
g ow h in he BIMSTEC egion. A bi-di ec ional causa ion (↔) exis s
Table 6
Coin eg a ion es o Ped oni and Wes e lund.
Tes s S a is ic P ob.
Ped oni
Panel -S a is ic 18.095 0
Panel ADF- a is ic −2.299 0.012
Wes e lund
Tes s a is ic 4.129 0.000
Table 7
Long- un es ima ions using FMOLS.
Va iables Model-A Model-B Model-C Model-D Model-E
PCAP 0.084*** 0.035 0.038
[0.022] [0.035] [0.035]
HCAP 0.052*** 0.010 0.022*
[0.011] [0.016] [0.012]
PCAP ×
GLBN
−0.001* −0.002***
[0.001] [0.001]
HCAP ×
GLBN
0.000 −0.001***
[0.000] [0.000]
GLBN 0.011 −0.012 0.084*** 0.075*** 0.170***
[0.018] [0.019] [0.024] [0.033] [0.037]
INFL −0.101*** −0.068 −0.012 −0.013 −0.012
[0.040] [0.053] [0.012] [0.015] [0.012]
FDIN −0.093 0.029 −0.026 −0.066 −0.020
[0.057] [0.034] [0.072] [0.092] [0.071]
GFDV −0.021* −0.031*** −0.080 −0.102 −0.089
[0.013] [0.013] [0.098] [0.130] [0.098]
Diagnos ic
es s
R-squa ed 0.542 0.532 0.642 0.641 0.647
Adjus ed R-
squa ed
0.515 0.505 0.620 0.618 0.621
Long- un
a iance
2.236 2.214 0.925 1.552 0.868
Coun ies 7 7 7 7 7
No e: ***=p <0.01, **=p <0.05, *=0 <0.1. S anda d e o s in he pa en hesis.
M.R. Uddin e al.
Resea ch in Globaliza ion 10 (2025) 100284
7
be ween physical capi al and economic g ow h, sugges ing ha capi al
accumula ion and economic expansion mu ually suppo one ano he .
Global inancial de elopmen and ECGR demons a e bi-di ec ional
causali y, indica ing ha he expansion o he inancial sec o bo h
p opels and is a ec ed by economic g ow h. A unidi ec ional causali y
(→) exis s om globaliza ion o ECGR, indica ing ha globaliza ion
subs an ially in luences economic g ow h, bu no he o he way a ound.
Fu he mo e, ECGR G ange -causes human capi al, in la ion, and
o eign di ec in es men ; howe e , hese a iables do no signi ican ly
in luence ECGR, indica ing ha economic g ow h is pi o al in de e -
mining in es men , human capi al ad ancemen , and mac oeconomic
s abili y. These indings unde sco e he in e ela edness o capi al,
inance, and globaliza ion in in luencing long- e m g ow h dynamics in
he egion.
4.7. Discussions
Table 11 p o ides a de ailed discussion o he hypo hesized e-
la ionships be ween ECGR and key a iables, including hei di ec e -
ec s and in e ac ion e ms. The esul s e eal mixed suppo o he
hypo heses, highligh ing nuanced dynamics wi hin he s udied
ela ionships.
Ou esea ch subs an ia es ha physical capi al (PCAP) exe s a
posi i e in luence on economic g ow h (ECGR) in BIMSTEC na ions,
consis en wi h he ex ensi e li e a u e highligh ing capi al accumula-
ion as a c ucial ca alys o economic ad ancemen . Kuma e al. (2023)
es ablish a obus co ela ion be ween o eign di ec in es men (FDI)
and economic g ow h in BIMSTEC na ions, indica ing ha augmen ed
capi al in lows, pa icula ly physical capi al, s imula e GDP g ow h.
Mo eo e , Uneze (2013) endo ses he concep o a bi-di ec ional causal
Table 8
Robus ness check using DOLS.
Va iables Model-1 Model-2 Model-3 Model-4 Model-5
PCAP 0.008 0.023 0.039
[0.007] [0.028] [0.055]
HCAP 0.002 0.013*** 0.021
[0.003] [0.007] [0.019]
PCAP ×GLBN 0.000 −0.002
[0.001] [0.001]
HCAP ×GLBN 0.000* −0.001
[0.000] [0.000]
GLBN 0.034*** 0.023*** 0.046*** 0.046*** 0.150***
[0.010] [0.010] [0.018] [0.017] [0.059]
INFL −0.016 −0.014* −0.015* −0.015* −0.014
[0.010] [0.009] [0.009] [0.009] [0.020]
FDIN 0.018 0.049 0.012 0.022 −0.019
[0.049] [0.042] [0.055] [0.046] [0.116]
GFDV 0.169** 0.184*** 0.111 0.089 −0.072
[0.085] [0.074] 0.077 [0.076] [0.162]
Diagnos ic es s
R-squa ed 0.637 0.639 0.638 0.641 0.655
Adjus ed R-
squa ed
0.617 0.619 0.616 0.619 0.630
Long- un a iance 2.511 2.508 2.496 2.485 2.428
Coun ies 7 7 7 7 7
No e: ***=p <0.01, **=p <0.05, *=0 <0.1. S anda d e o s in he pa en hesis.
Table 9
Robus ness check using ARDL.
Va iables Model-1 Model-2 Model-3 Model-4 Model-5
Long- un coe icien s
PCAP 0.006*** 0.036* 0.064***
[0.002] [0.020] [0.029]
HCAP 0.000 −0.004 −0.008
[0.001] [0.005] [0.007]
PCAP ×GLBN −0.001** −0.002***
[0.001] [0.001]
HCAP ×GLBN 0.000 0.000
[0.000] [0.000]
GLBN 0.026*** 0.017*** 0.023*** 0.015** −0.005
[0.004] [0.003] [0.010] [0.007] [0.020]
INFL −0.027*** −0.023*** −0.010 −0.022*** 0.011
[0.004] [0.004] [0.006] [0.006] [0.012]
FDIN −0.007 0.007 −0.016 −0.003 0.002
[0.009] [0.006] [0.020] [0.021] [0.031]
GFDV 0.306*** 0.364*** 0.522*** 0.579*** 1.191***
[0.036] [0.024] [0.062] [0.042] [0.108]
Cons an 21.087*** 20.651*** 18.845*** 18.580*** 14.438***
[0.254] [0.152] [0.646] [0.322] [0.922]
Sho - un coe icien s
D(PCAP) 0.021* −0.111* 0.037
[0.012] [0.065] [0.034]
D(HCAP) 0.061 −0.631 −0.310
[0.048] [0.552] [0.237]
D(PCAP) ×D(GLBN) 0.003* 0.000
[0.001] [0.001]
D(HCAP) ×D(GLBN) 0.019 0.010
[0.017] [0.008]
D(GLBN) 0.257 0.274 0.177 −0.548 −0.113
[0.195] [0.214] [0.145] [0.541] [0.094]
D(INFL) −0.011 −0.017 −0.018 −0.033 0.001
[0.008] [0.014] [0.013] [0.030] [0.002]
D(FDIN) −0.126 −0.160 −0.070 −0.122 −0.097
[0.104] [0.132] [0.055] [0.100] [0.089]
D(GFDV) 0.006 0.490 −0.769 1.396 0.657
[0.201] [0.481] [0.772] [1.470] [1.057]
ECT 0.194 0.311 0.434 2.107 0.710
[0.286] [0.455] [0.467] [2.257] [0.686]
Log-Likelihood 263.750 241.665 278.117 235.846 285.564
No e: ***=p <0.01, **=p <0.05, *=0 <0.1. S anda d e o s in he pa en hesis.
M.R. Uddin e al.
Resea ch in Globaliza ion 10 (2025) 100284
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