Hasan, Md. A ik; Subo na, Shabikunnaha ; U bee, A ida Jinnu ain
A icle
In es iga ing he ole o o eign aid, FDI, and emi ance
on he public heal h o selec ed Sou h Asian coun ies
Resea ch in Globaliza ion
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Sugges ed Ci a ion: Hasan, Md. A ik; Subo na, Shabikunnaha ; U bee, A ida Jinnu ain (2025) :
In es iga ing he ole o o eign aid, FDI, and emi ance on he public heal h o selec ed Sou h
Asian coun ies, Resea ch in Globaliza ion, ISSN 2590-051X, Else ie , Ams e dam, Vol. 10, pp. 1-12,
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In es iga ing he ole o o eign aid, FDI, and emi ance on he public
heal h o selec ed Sou h Asian coun ies
Md. A ik Hasan
a,1,*
, Shabikunnaha Subo na
b
, A ida Jinnu ain U bee
a
a
Facul y o Depa men o Economics, Noakhali Science and Technology Uni e si y, Noakhali 3814, Bangladesh
b
Depa men o Economics, Noakhali Science and Technology Uni e si y, Noakhali 3814, Bangladesh
ARTICLE INFO
Keywo ds:
Heal h quali y index
Heal h expendi u es
Fo eign aid
Remi ances
Fo eign di ec in es men
Globaliza ion
Sou h Asia
ABSTRACT
Fo eign aid, emi ance, and o eign di ec in es men ha e a signi ican ole in shaping and p omo ing glob-
aliza ion and hese ac o s also play a i al ole in de e mining heal h quali y in de eloping coun ies. De eloping
coun ies, especially Sou h Asian coun ies s ill need esea ch and policies o e icien ly u ilize he con ibu ions
o hese ex e nal capi al sou ces in hei heal h sec o . Fo his eason, he p esen s udy examined he e ec s o
di e en globaliza ion- ela ed ac o s ( emi ances, o eign di ec in es men , o eign aid) and heal h spending
om 2000 o 2020 on he quali y o heal hca e in six Sou h Asian coun ies: Bangladesh, India, Nepal, Pakis an,
Maldi es, and S i Lanka. Mo eo e , his in es iga ion in oduces an unp eceden ed ace o he ealm o heal h
sec o esea ch by in oducing a no el heal h quali y index ha inco po a es li e expec ancy, newbo n mo ali y
a e, ma e nal mo ali y a e, and illness p e alence (speci ically ube culosis). This s udy used Augmen Mean
G oup (AMG) es ima ion o da a analysis. To ensu e he p ecision and dependabili y o he indings, his
esea ch u ilizes sophis ica ed s a is ical me hodologies, including he Common Co ela ed E ec o Mean G oup
(CCEMG), D iscoll-K aay Robus S anda d E o app oaches, and Dumi escu and Hu lin (D-H) causali y es ,
he eby es ablishing hei dependabili y. The indings o he s udy demons a e ha o eign aid and heal h
spending ha e a signi ican bene icial impac on he heal h quali y o Sou h Asia. In con as , emi ances end o
ha m heal h quali y. Fu he mo e, he in luence o FDI on he quali y o heal h in Sou h Asia is equi ocal. Sou h
Asian coun ies mus alloca e mo e o hei budge o he heal h sec o and ensu e ha o eign aid is p ope ly
u ilized o i s de elopmen . On he o he hand, hese coun ies a e equi ed o ake policy and c ea e an
en i onmen ha will help o imp o e heal h quali y h ough e ec i e use o emi ance and FDI.
1. In oduc ion
A na ion’s heal hca e sys em is c ucial o i s economic g ow h
(Islam e al., 2020) and social wel a e. A heal hy popula ion can ac i ely
pa icipa e in he economy and d i e g ow h, while poo heal h educes
p oduc i i y and s ains public esou ces. E en heal h spending i sel is
posi i ely associa ed wi h economic g ow h (Islam &Alhamad, 2022),
bu In Sou h Asia, he heal h sec o is one o he leas essen ial sec o s o
look a e . A e age spending on he heal h sec o in Sou h Asia is lowe
han 3 % o he coun y’s budge (Bidin, 2017). This low heal h spending
can be co e ed by wise use o he capi al in low om ex e nal ac o s.
Tha is why he ela ionship be ween economic ac o s like o eign aid,
FDI, emi ance, heal h expendi u e, and heal h ou comes has become a
c ucial a ea o s udy in de eloping na ions, pa icula ly in Sou h Asia.
Resea che s ha e been paying a en ion o he impac o o eign aid,
emi ance, and FDI on human de elopmen me ics, such as heal h
quali y and heal hca e se ice accessibili y. This issue has ga ne ed
a en ion om policymake s and academics alike in ecen imes.
Al hough he e ha e been e o s o imp o e public heal h in low and
middle-income coun ies h ough o eign aid, FDI, and emi ances om
mig an wo ke s, he impac o hese economic ac o s has been con-
es ed in exis ing li e a u e. I emains unclea whe he hese ac o s
alone can be c edi ed o socie al gains in public heal h o whe he o he
de e minan s o heal h also play a signi ican ole. Fu he esea ch is
needed o unde s and be e he speci ic impac o hese economic ele-
men s on ad ancing heal h sys ems in hese coun ies.
Fo eign di ec in es men (FDI) and emi ances a e wo ex e nal
inancial lows, which a e impo an in mi iga ing economic g ow h and
* Co esponding au ho a : Facul y o Depa men o Economics, Noakhali Science and Technology Uni e si y, Noakhali 3814, Bangladesh.
E-mail add esses: [email p o ec ed] (Md.A. Hasan), [email p o ec ed] (S. Subo na), [email p o ec ed] (A.J. U bee).
1
0009-0000-3919-6993.
Con en s lis s a ailable a ScienceDi ec
Resea ch in Globaliza ion
jou nal homepage: www.sciencedi ec .com/jou nal/ esea ch-in-globaliza ion
h ps://doi.o g/10.1016/j. esglo.2025.100268
Recei ed 28 Sep embe 2024; Recei ed in e ised o m 30 Decembe 2024; Accep ed 2 Janua y 2025
Resea ch in Globaliza ion 10 (2025) 100268
2
heal h ou comes’impo ance, pa icula ly in de eloping na ions (Islam,
2024). Bu like any o he hing, human capi al de elopmen is essen ial
o economic p og ess (Islam &Alam, 2023; Islam &Munee , 2018;
Islam &Shindaini, 2022), and pe sonal emi ances equen ly enhance
amily income, inc easing household access o heal hca e se ices
(Islam, 2022, 2020b, 2024; Islam &Alam, 2023). Fu he mo e, esea ch
shows ha emi ances help na ow he gap in ecei ing heal h ca e and
educa ion by educing inequali y and helping o posi i ely impac in-
come dis ibu ion (Islam &Azad, 2024; Islam &Ke ama , 2012). A s udy
o emi ance-sending coun ies shows ha e ec i e go e nance helps
maximize he emi ance bene i s by di ec ing hem owa d p oduc i e
sec o s such as heal hca e and sus ainable ene gy (Hasan e al., 2019;
Islam, 2020a; P adhan &Khan, 2015). FDI can acili a e echnology
ans e and in as uc u e de elopmen –which include heal h acil-
i ies. FDI has a ole in economic g ow h, income edis ibu ion, and
imp o ing heal hca e se ices (Nagel e al., 2015). FDI and emi ances
help ecipien na ions pa icipa e in he global ma ke and he capi al
lows in o he coun y (Shahid e al., 2021).
Imp o ing heal h ou comes is s ill a signi ican de elopmen conce n
in Sou h Asia due o he egion’s ongoing heal h sys em inadequacies
and une en p og ess owa d essen ial heal h goals. To make in o med
and e idence-based e o ms, i is c ucial o comp ehend he p ima y
de e minan s ha impac he unc ioning o he heal hca e sys em.
Sou h Asia’s inadequa e heal h sys ems and a iable p og ess owa d
SDG a ge a ainmen equi e p io i y a en ion o imp o e heal h
ou comes. The e o e, policymake s a e wo king owa ds unde s anding
and enhancing he heal h ou comes o he popula ion in Sou h Asia.
Signi ican heal h issues, no ably high a es o in ec ious illnesses,
malnu i ion, and ma e nal and in an mo ali y, exis in his egion.
Bloom e al. (2004) analyze how impo an economic ac o s impac he
quali y o heal h ac oss six majo economies in Sou h Asia. Rahman e al.
(2013) examine he ac o s ha con ibu e o high heal hca e cos s and
inancial disas e s associa ed wi h heal hca e in Bangladesh and make
u gen ecommenda ions o lowe ing he bu den o ou -o -pocke ex-
pendi u es o lowe le els o ca as ophic heal h spending. P og ess
ac oss he egion has been une en despi e imp o emen s in li e expec-
ancy and o he heal h indica o s (Bu ns e al., 2017). In addi ion,
heal hca e sys ems a e s ill acing inancial insu iciencies and di i-
cul ies in keeping up wi h he inc easing demand o hei se ices
(P inja e al., 2017). Sou h Asian go e nmen s, as lowe -middle-income
economies, ha e limi ed iscal capaci y o in es in heal hca e. In he
con ex o he heal h challenges aced by Sou h Asia, i is c ucial o use
all inancing sou ces e ec i ely o imp o e he pe o mance and quali y
o heal hca e sys ems. Ex e nal inancing plays an impo an ole.
A heal h quali y index is a me ic ha e alua es and quan i ies he
e ec i eness o heal hca e sys ems o he s a e o heal h in a communi y.
Tha e alua es mul iple ac o s, such as popula ion heal h ou comes,
access o ca e, and he e iciency o he heal h sys em. An e ec i e
heal hca e sys em can be measu ed by a highe sco e on he heal h
index, which ep esen s be e li e expec ancy, lowe equency o ill-
nesses, and ewe p e en able dea hs. This demons a es ha he pop-
ula ion’s heal h s a us imp o emen s a e pa ly due o b oade
socioeconomic p og ess. HQI is a be e measu emen o he heal h
s a us o a coun y han se e al o he single a iables like mo ali y a e,
in an mo ali y, li e expec ancy, e c., because his a iable shows a
single dimension o a coun y’s heal h sec o . In con as , HQI is he
me ics ha me ge all hese dimensions. Fig. 1 shows he imp o emen s
in he heal h quali y index in Sou h Asia.
Heal hca e expendi u es p o ide he necessa y unding o enhance
he accessibili y and quali y o heal hca e se ices (Bhalo a, 2007; Bein
e al., 2017; Mohapa a, 2022; Rahman e al., 2018). Enhancing heal h
esul s is a signi ican policy conce n, pa icula ly in en i onmen s wi h
limi ed esou ces. I is hough ha heal h spending a ec s how well he
heal h sys em unc ions. Empi ical e idence, howe e , has p oduced
con lic ing indings abou he connec ion be ween heal h ou comes and
medical cos s. One eason is ha co up ion and ine iciency may hinde
he pe o mance o u he in es men s. Second, poo die , hygiene,
educa ion, and economic de elopmen can hinde he p og ess o heal h.
Las ly, gains in ma ginal spending may be o se by he signi ican dis-
ease bu den om HIV/AIDS, mala ia, and o he in ec ious diseases.
Despi e his, he e is s ill a lo o deba e a ound hese undamen al
causes. As he e is a bidi ec ional ela ionship be ween economic g ow h
and heal h spending (Islam, 2020a,b,c), lowe GDP g ow h in Sou h
Asian coun ies means lowe heal h spending. This is why ex e nal
economic ac o s like o eign aid, FDI, and emi ance a e essen ial o
imp o e he heal h quali y o his egion.
The link be ween o eign di ec in es men (FDI) in lows and heal h
quali y has impo an implica ions o economic g ow h and de elop-
men . Resea ch on how globaliza ion a ec s heal h ou comes, pa icu-
la ly inc eased o eign in es men lows, has been i al. In bo h
indus ialized and de eloping na ions, Rega ding he connec ion be-
ween inwa d FDI s ocks and popula ion heal h quali y, he e a e s ill
Fig. 1. HQI o Sou h Asia o he selec ed coun ies ().
Sou ce: calcula ed by au ho s
Md.A. Hasan e al.
Resea ch in Globaliza ion 10 (2025) 100268
3
con adic o y indings. FDI g ow h can a ec heal h in se e al ways.
Public heal h expendi u es and access o high-quali y ea men may ise
as a esul o FDI- ela ed de elopmen and highe ea nings. Also, he
a ailabili y and deli e y in as uc u e o medical echnology a e
signi ican ly imp o ed by o eign di ec in es men (FDI) (Bu ns e al.,
2017). Howe e , o eign di ec in es men (FDI) may also con ibu e o
he sp ead o illness o ha e un a o able en i onmen al e ec s ha
could wo sen medical issues (Bake e al., 2014; Ba low e al., 2017;
Labon ´
e, 2019a).The e o e, he o e all consequences p obably ely on
he socioeconomic ci cums ances unique o each na ion.
Remi ances can inc ease an indi idual’s pu chasing powe o
heal hca e expenses (Rahman e al., 2013). Remi ances om mig an s
o hei home coun ies, pa icula ly de eloping na ions, ha e been
shown in se e al s udies o boos local popula ions’heal h esul s.
S udies ha e indica ed ha hese emi ances, pa icula ly in low- and
middle-income na ions, can conside ably lowe newbo n mo ali y a es
and enhance he heal h o child en. Imp o ing heal h ou comes and
hei quali y in de eloping egions is a signi ican consequence o
o eign aid ha is alloca ed owa d heal h p og ams. Remi ance can
a ec heal h no only in a di ec way bu also in indi ec ways. Fo
example, emi ance in low helps o aise GDP (Islam &Shindaini,
2022), and highe GDP may lead o imp o ed heal h quali y.
The impac o o eign aid on he heal h o de eloping na ions has
been an a ea o global deba e o e he pas se e al decades. The ques ion
is whe he addi ional unding and heal h- ela ed ini ia i es will esul in
be e heal hca e quali y and access. Aid can p o ide a boos o domes ic
heal h spending and esou ces, which can lead o highe alloca ions o
heal h sys ems and imp o ed access o high-quali y ca e (Bo ing e al.,
2010; Joh i e al., 2012). Assis ance can also enable he de elopmen o
enhanced heal h in as uc u e, ans e o medical echnology,
imp o ed su eillance p og ams, and a mo e capable heal h wo k o ce.
Also, o eign aid allows go e nmen s o und public heal h p og ams
hey canno a o d o he wise, and ecipien go e nmen s a e unable o
a o d i (Fa ag e al., 2013). Bu despi e ecei ing a lo o aid, he e
hasn’ been any no iceable imp o emen in e ms o heal h and o he
heal h- ela ed indica o s o many de eloping coun ies, especially om
A ica and Sou h Asia. Adhika i e al. (2018) sugges ha a he han
depending on middlemen, o eign unding should be di ec ed a
bols e ing and assis ing he domes ic heal hca e sys em. Many in-
di iduals hink ha o eign aid may help de eloping na ions wi h hei
heal h issues. On he o he hand, he e is disag eemen o e he
con ibu ion o aid o economic g ow h and i s abili y o imp o e heal h
ou comes. Fig. 2 shows he link be ween economic and globaliza ion
ac o s wi h good heal h.
This esea ch will enhance he discou se on s eng hening heal h
sys ems and popula ion heal h in Sou h Asia. The p e ious s udy by
Mohan y and Behe a (2020) in es iga ed he co ela ion be ween
heal hca e cos s and pa ien ou comes. Howe e , his s udy included
mo e economic a iables in i s analysis. I ’s essen ial o unde s and he
connec ion be ween ex e nal inances and heal h, as his can help wi h
deciding which a eas need unding he mos , p io i izing global de el-
opmen pa ne ships, and imp o ing in es men p omo ion s a egies.
Sou h Asia aces signi ican heal h challenges, so i ’s c ucial o make he
mos o all unding sou ces o imp o e he pe o mance and quali y o
heal hca e sys ems. This s udy p ima ily u ilizes he Heal h Quali y
Index (HQI) as he dependen a iable, e lec ing a holis ic measu e o
heal h sys em e ec i eness o e ime. Using a composi e me ic like
HQI, which consolida es mul i ace ed heal h domains in o a s anda d-
ized sco e, helps e alua e o e all pe o mance. This s udy makes use o
panel da a om he yea s 2000 o 2020, concen a ing on he six la ges
Sou h Asian na ions: Bangladesh, India, Pakis an, S i Lanka, he
Maldi es, and Nepal. These na ions we e chosen because hey accoun
o mo e han 95 % o Sou h Asia’s popula ion and GDP, as well as da a
a ailabili y.
The main objec i e o his s udy is o p o ide help ul in o ma ion o
heal h policy decisions in Sou h Asia. Abou he Sou h Asian economies,
he esea ch will speci ically examine how heal h spending, and
globaliza ion- ela ed ac o s ( o eign di ec in es men , emi ance in-
lows, and de elopmen aid o heal h) ha e a ec ed he heal h quali y
index be ween 2000 and 2020. By examining he ela ionship be ween
hese economic ac o s and heal h pe o mance measu es, he s udy
aims o p io i ize unding a eas ha ha e had he mos signi ican
impac in he pas . The de elopmen o a no el heal h quali y index o
ully cap u e he ac ual con ibu ion o dependen a iables on heal h
quali y is he second pu pose o his s udy. Because only li e expec ancy
o mo ali y is ine icien in cap u ing he ac ual heal h quali y o a e-
gion. The inclusion o policies ega ding he de elopmen o egional
and na ional heal h inance s a egies is he hi d goal. The s udy in ends
o suppo policymake s in imp o ing esou ce alloca ion o op imize
u u e heal h bene i s by quan i ying he his o ical co ela ions be ween
obse ed heal h quali y and ex e nal heal h spending. This s udy is ex-
pec ed o acili a e heal h policy and go e nance dialogues in Sou h Asia
by p o iding a clea unde s anding o he con ex o de elopmen
inancing.
The No el y o his s udy is embedded in ha , i in oduces a unique
heal h quali y index o cap u e he heal h quali y o Sou h Asian na ions.
Along wi h his, his s udy used obus app oaches ha e ec i ely
cap u e he complex dynamics and he e ogenei y o heal h quali y wi h
heal h spending, o eign di ec in es men , and emi ance in lows. We
use he augmen ed mean g oup (AMG) es ima o , he common co e-
la ed e ec o mean g oup (CCEMG), and he Disc oll and Ka y s an-
da d e o app oach. All o hese me hods can handle he c oss-sec ional
dependency and slope homogenei y p oblems o he da a. Wi h he help
o his me hodology, we can in es iga e he unde lying mechanisms as
well as he s a is ical ela ionships be ween he chosen a iables. Ou
goals a e o gi e policymake s help ul in o ma ion and a ho ough un-
de s anding o he ways ha o eign aid a ec s heal h ou comes.
The emaining pa o his s udy is o ganized as ollows: Sec ion 2
b ie ly discusses pas li e a u e ela ed o his s udy whe eas Sec ion 3
ep esen s he es ima ion s a egies o his s udy. Resul s om da a
analysis a e ep esen ed in Sec ion 4. Sec ion 5 s a es a b ie discussion
o es ima ed esul s. A causali y analysis is also illus a ed in sec ion 6.
The conclusion and policy ecommenda ion based on his s udy’s ind-
ings a e discussed in sec ion 7. Finally, Sec ion 8 demons a es he
limi a ions o his s udy and u u e esea ch guidelines on his opic.
2. Li e a u e e iew
Se e al s udies ha e been conduc ed o analyze how di e en eco-
nomic ac o s, such as heal h spending, o eign di ec in es men (FDI),
emi ances, and o eign aid, a ec he s anda d o heal h in de eloping
na ions. This sec ion will summa ize hose p e ious discussions.
Fig. 2. Link be ween he selec ed a iables.
Md.A. Hasan e al.
Resea ch in Globaliza ion 10 (2025) 100268
4
2.1. Heal h quali y and heal h expendi u e Nexus
A s udy by Mohapa a (2022) ound ha heal h expendi u e posi-
i ely a ec s heal h ou comes in he SAARC egion. In he SAARC-
ASEAN a ea, o e all heal h spending, s a e heal h spending, and p i-
a e heal h spending all g ea ly lowe ed newbo n mo ali y a es
(Rahman e al., 2018). Acco ding o he indings o Akba e al. (2021),
public heal h expendi u e helps o minimize he in an mo ali y a e.
Alziyani and Bein (2021) and Bein e al. (2017) disco e ed ha public
heal h ini ia i es a e essen ial, and mo e heal h spending is a signi ican
con ibu o o longe li e expec ancies. A e iew by Ju kowi z (2009)
disco e ed mixed indings, wi h some esea ch demons a ing a nega-
i e co ela ion be ween Medica e spending and ca e quali y and o he s
inding a posi i e co ela ion be ween o al heal hca e cos s and heal h
quali y. Ba be e al. (2017) e iew p e ious esea ch ha used
amenable mo ali y as a p oxy o access o and quali y o heal hca e.
Inc eased heal h spending should lead o imp o ed access o high-
quali y ca e, bu he empi ical e idence shows con lic ing esul s. Ac-
co ding o his e iew pape , p e ious c oss-na ional esea ch in he
OECD ound only weak co ela ions be ween heal h spending and
amenable mo ali y. In he mean ime, esea ch by Akinkugbe and
Mohanoe (2009) Dickson e al. (2021); Dieleman e al. (2020) demon-
s a ed ha inc eased public heal h in es men esul ed in lowe in an
mo ali y and longe li e expec ancies. Howe e , no signi ican causal
co ela ions we e disco e ed be ween a ious heal h spending a iables
and heal h ou comes in A ica by o he analyses. Among hese a e
esea ch wo ks by (Baldacci e al., 2003; Gyimah-B empong &Wilson,
2004; No ignon e al., 2012). All o he abo e s udies poin o he need
o ca e ul managemen and balancing heal h spending wi h o he is-
sues, e en hough i can con ibu e o be e heal h.
2.2. Heal h quali y and FDI Nexus
Many s udies ha e examined how o eign di ec in es men (FDI)
and heal h a e ela ed, u ilizing indica o s like li e expec ancy and
newbo n mo ali y a es. Resea ch on de eloping na ions e ealed ha
o eign di ec in es men (FDI) inc eased heal h spending and esul s,
bu some s udies also ound ha ad e se en i onmen al e ec s o se
hese ad an ages. Immu ana (2020) ind ou o eign di ec in es men
(FDI) has a a o able e ec on heal h ou comes, including li e expec-
ancy and dea h a es. They p opose ha o enhance heal h ou comes,
such as li e expec ancy and mo ali y a es, coun ies should concen a e
on lu ing mo e o eign di ec in es men (FDI). Bo h Immu ana (2020)
and Shahid e al. (2019) also disco e ed a a o able co ela ion be ween
o eign di ec in es men (FDI) and heal h since FDI aises li e expec-
ancy and lowe s he dea h a e. Howe e , a con lic ing esul was also
ound ega ding he impac o inc easing FDI on heal h quali y in-
dica o s and i s ou comes when his link was examined in de eloping
coun ies, especially hose in Sou h Asia (Shahid, 2021).
Resea ch om de eloped coun ies indica es ha because o
employmen unce ain y, mo e signi ican FDI may be ha m ul o public
heal h, economic inequali y, and psychosocial s ess (Chiappini e al.,
2022a). FDI appea s o ha e a a o able impac on heal h a lowe in-
come le els bu a de imen al impac a highe income le els, acco ding
o Nagel e al. (2015), who indica es ha his ela ionship is nonlinea .
Emphasizing he ole o popula ion heal h in lu ing o eign di ec in-
es men (FDI) and he co ela ion be ween imp o ed heal h and FDI
in lows in o low- and middle-income na ions (Mai i &Bidinge , 1981).
The connec ion be ween popula ion heal h and o eign di ec in es -
men (FDI) in low- and middle-income coun ies (LMICs) has spa ked a
lo o in e es in he li e a u e and con e sa ion. Despi e he widesp ead
pe cep ion ha economic expansion has posi i e long- e m e ec s on
heal h, he impac o sho - e m mac oeconomic adjus men s, pa icu-
la ly hose b ough on by o eign di ec in es men (FDI), on heal h is
no widely ecognized (Bu ns e al., 2017). Zhang e al., (2023) examine
he associa ion be ween o eign di ec in es men (FDI) in low and he
quali y o popula ion heal h in China. Acco ding o he indings, FDI
helps o imp o e heal h quali y when hey a e in es ed in ca bon-
minimizing p ojec s.
2.3. Heal h quali y and o eign aid Nexus
Acco ding o Benda id and Bha acha ya (2014), each 1 % inc ease
in heal h aid was associa ed wi h imp o emen s in li e expec ancy and
unde -5 mo ali y. And he associa ion be ween heal h aid and heal h
imp o emen s s eng hened o e ime. Heal h assis ance has imp o ed
li e expec ancy and child mo ali y a es, acco ding o c oss-coun y
assessmen s (Akinbode e al., 2021; Asiama &Qua ey, 2009; Rashed
e al., 2024). Heal h esul s a e signi ican ly and a o ably impac ed by
o eign aid, especially in na ions wi h solid ins i u ional quali y
(Zulaikha, 2016). I has been disco e ed ha assis ance lowe s he
p oduc i i y cos o illness, especially in egions adjacen o assis ance
ini ia i es (Odokonye o e al., 2018). In es men s in essen ial medical
echnology, disease su eillance, heal h wo ke aining, and in a-
s uc u e can enable de eloping coun ies o sho e up access o high-
quali y ca e (Bu ns e al., 2017; Lim e al., 2023).
Mish a and Newhouse (2009) looks a he connec ion be ween heal h
ou comes in de eloping coun ies and o eign help, speci ically heal h
aid. Fo eign aid had li le o no e ec on popula ion heal h o e all since
2000, wi h only a minimal imp o emen in li e expec ancy obse ed. 1
% inc ease in o eign aid, li e expec ancy goes up by 0.004 %. Findings
showed ha al hough he e isn’ enough e idence o d aw a de ini e
connec ion be ween help and economic g ow h, he s udy does show
ha o eign aid can imp o e heal h ou comes (Tosee e al., 2019).
None heless, he e is a complica ed ela ionship be ween globaliza ion,
heal h, and aid, wi h a nega i e co ela ion be ween he h ee a high
le els o globaliza ion o e all (Welande e al., 2012). Ins i u ional isks
also a ec he e ec i eness o aid in he heal h sec o (Ma u a e al.,
2020). Suppo e s o o eign assis ance asse ha i may imp o e he
deli e y o heal h ca e and sa e li es h ough p og ams like immuni-
za ion campaigns. A he same ime, opponen s con end ha i may ha e
un a o able e ec s like encou aging eliance o being dispe sed
ine icien ly.
2.4. Heal h quali y and emi ance Nexus
Recognizing he i al con ibu ion ha pe sonal emi ances make o
be e ing heal h ou comes is essen ial, especially in coun ies acing
economic ha dship. Sha iq and Gillani (2020) assessed how emi ances
a ec ed child heal h and concluded ha pe sonal emi ances ha e a
bene icial impac on child heal h in de eloping na ions. Te elonge,
(2014) shows ha he ise in emi ances migh be pa ly esponsible o
he dec ease in baby and child mo ali y a es. Be ween 1995 and 2009,
emi ances and public heal h spending in poo na ions inc eased mo e
han wo- old. Howe e , child and newbo n mo ali y in hese na ions
dec eased by 33.5 % and 30.9 % espec i ely du ing he same pe iod
(Te elonge, 2014). I has been disco e ed ha emi ances ha e a
a o able e ec on heal h ou comes, such as in he case o babies and
unde -5 mo ali y a es (Zulaikha, 2016). They also con ibu e o
lowe ing newbo n mo ali y, aising li e expec ancy, and aising
achie emen in elemen a y and seconda y (Zhunio e al., 2012). Re-
mi ances ha e been connec ed o highe heal h cos s in Ecuado , as well
as he cos o p esc ip ion d ugs du ing illness and p e en i e ea men s
like immuniza ions and dewo ming (Ponce e al., 2011).
Remi ances boos heal h ou comes in de eloping coun ies, wi h
go e nance and ma e nal educa ion iden i ied as c ucial ou es, ac-
co ding o a ecen s udy u ilizing a panel ec o au o eg essi e model
(Djeunankan &Tekam, 2022). Linds om and Ramí ez (2010) disco -
e ed ha emi ance- ecei ing households migh pu consump ion
ahead o in es men s in heal h and educa ion, which could ha e a
de imen al impac on heal h, especially o child en. A ecen s udy
conduc ed in Bangladesh by P adhan and Khan (2015) in es iga ed he
Md.A. Hasan e al.
Resea ch in Globaliza ion 10 (2025) 100268
5
co ela ion be ween emi ance ea nings and heal h quali y. The s udy’s
conclusions demons a ed a long- e m causal link be ween emi ances
and he Human De elopmen Index (HDI). This implies ha emi ances
e en ually esul in be e li ing condi ions. I is wo h no ing ha e-
mi ances a e a eliable p edic o o heal hy unc ioning and demon-
s a e a s ong and nonlinea ela ionship wi h heal hy unc ioning
(P˘
aunic˘
a e al., 2019). Table 1 ep esen s he summa y o he li e a u e
e iew.
2.6. Li e a u e gap
Nume ous s udies ha e al eady been conduc ed on he heal h sec o
ou come in Sou h Asia. Howe e , none o hose esea che s y o c ea e
a heal h quali y index. Somewha di e en , he li e a u e ies o
calcula e heal h ou comes by conside ing di e en p oxy a iables like
child mo ali y, ma e nal mo ali y, and li e expec ancy. Howe e , his
s udy, o he i s ime, ies o c ea e a unique heal h quali y index by
using child mo ali y, ma e nal mo ali y, li e expec ancy, and disease
p e alence. The exis ing li e a u e ails o adequa ely explain he link
be ween ex e nal capi al in low- ela ed a iables and heal h ou comes
in Sou h Asian coun ies. The e ec s o go e nmen heal h spending,
FDI, o eign aid, and emi ances on heal h ou comes ha e been exam-
ined in he pas , bu sepa a ely. To be e unde s and how ex e nal
economic ac o s, a ec public heal h in Sou h Asian coun ies, i is
c ucial o in es iga e how household-le el emi ance in lows, indus y-
le el FDI in low, and in e na ional aid in e ac wi h go e nmen policies
and heal hca e in es men s. By doing so, we can gain a mo e comp e-
hensi e unde s anding o he mechanisms ha impac popula ion heal h
in his egion.
3. Me hodology
3.1. Da a and sou ces
3.1.1. De elopmen o heal h quali y index
Se e al p e ious s udies ied o model heal h quali y wi h economic
aspec s. S ill, one o he signi ican gaps in he ea lie s udies was he
de e minan o heal h quali y ha hey used, which was a poo ep e-
sen a ion o a coun y’s heal h sec o quali y. Mos o he p e ious
s udies use dependen a iables like li e expec ancy, ma e nal mo ali y
a e, o disease p e alence. Howe e , one single a iable can’ exp ess
he eal heal h scena io o a coun y. Tha ’s why his s udy makes an
index by combining all o his. To do his s udy, I ollowed he ollowing
p ocedu e:
S ep
1:
A e collec ing da a on li e expec ancy, in an mo ali y, ma e nal
mo ali y, and ube culosis p e alence, we ake he in e se o hese o
ans e hem in o posi i e a ibu es. Now, he a iables become li e
expec ancy, ma e nal su i al a e, in an su i al a e, and ube culosis-
ee popula ion. All o hem show posi i e a ibu es.
(con inued on nex column)
(con inued)
S ep
2:
As he anges o all hese a iables we e di e en , his s udy applied a
widely used s anda diza ion me hod o con e all he a iables wi hin he
same ange.
S ep
3:
A e s anda diza ion, his s udy applied he p incipal componen analysis
(PCA) me hod o c ea e a unique heal h quali y index.
3.1.2. Da a de ini ion
Ou s udy’s econome ic es ima e was p edica ed on seconda y da a,
namely he Wo ld Bank’s WDI and Ou Wo ld in Da a sou ces. We
examined i al ac o s such as FDI in low, pe sonal emi ances
ecei ed, o eign aid, and heal h spending as independen a iables o
ind ou wha a ec s heal h ou comes. We con ined ou s udy and
examined da a o Sou h Asian na ions (Bangladesh, India, Maldi es,
Nepal, Pakis an, and S i Lanka) om 2000 o 2020, as da a o
A ghanis an and Bhu an we e no a ailable. The in o ma ion is yea ly
panel da a—a mo e ho ough analysis o he da a o Sou h Asian
economies om 2000 o 2020. Fou p ima y a iables we e selec ed o
measu e he inpu s o he heal hca e sys em, which a e independen o
each o he . These include Heal h expendi u e (HE), which is he amoun
spen on medical ca e by he public and p i a e sec o s. Fo eign aid (FA)
ep esen s he ne o icial de elopmen assis ance o heal h, which is
ex e nal inancing. Remi ances a e de ined as pe sonal paymen s made
by o eign wo ke s back o hei home na ions in Sou h Asia. This se es
as an addi ional sou ce o heal h inancing. Fo eign di ec in es men
(FDI) in lows a e capi al in es men s om ab oad ha a e linked o
heal hca e capaci y. A lis o he a iables and hei de ini ion a e gi en
in Table 2.
3.1.3. Summa y s a is ics
The a iable’s desc ip i e s a is ics om 2000 o 2020 a e shown in
Table 3. S anda d de ia ions, max, min, skewness, ku osis, sum, sum,
Table 1
Summa y o he li e a u e.
Li e a u e Coun y Pe iod Me hod Va iable Findings
(Immu ana, 2020) A ica 1997–2017 IVFE and GMM FDI and Heal h Ou come posi i e
(Zhang e al., 2023) China 1980–2020 VECM FDI and Heal h Ou come Posi i e
(Shahid e al., 2019) Sou h Asia 1990–2016 Fixed E ec (FE) FDI and Heal h Ou come Nega i e
(Chiappini e al., 2022a) 143 coun ies 1990–2016 Ins umen al Va iable (IV) FDI and Heal h Ou come Posi i e
(Sha iq &Gillani, 2020) 132 coun ies 1980–2015 Sys em GMM Remi ance and Child Heal h Posi i e
(Te elonge, 2014) 138 de eloping coun ies 1995–2009 OLS and 2SLS Remi ance and Heal h Ou come Posi i e
(P adhan &Khan, 2015) Bangladesh 1981–2011 VECM Remi ance and Heal h Ou come Posi i e
(Asiama &Qua ey, 2009) Sub-Saha an A ica OLS and GMM Aid and Heal h Ou come Posi i e
(Mish a &Newhouse, 2009) 118 coun ies 1973–2004 OLS and GMM Aid and Heal h Ou come Nega i e
(Benda id &Bha acha ya, 2014) 140 coun ies 1974–2010 OLS Fo eign Aid and Heal h Ou come Posi i e
(Anyanwu &E hijakpo , 2007) A ica 1999–2004 ROLS and R2SLS Heal h Expendi u e and Child Mo ali y Posi i e
(Akinkugbe &Mohanoe, 2009) Leso ho 1975–2007 VAR Heal h Expendi u e and Li e Expec ancy Posi i e
(Mohapa a, 2022) SAARC 1993–2012 GLS Heal h Expendi u e and Heal h Ou come Posi i e
Table 2
Lis o all a iables.
Va iable Indica o Measu emen Sou ce
HQI Heal h Quali y
Index
This index includes ou a iables:
Li e expec ancy a bi h, Mo ali y
a e (in an ), Ma e nal mo ali y
a io, and incidence o
ube culosis.
Wo ld Bank,
(2023)
HE Heal h
Expendi u e
Cu en heal h expendi u e pe
capi a (cu en US$)
Wo ld Bank,
(2023)
FDI Fo eign Di ec
In es men
Fo eign di ec in es men , ne
(Bop cu en US$)
Wo ld Bank,
(2023)
FA Fo eign Aid Fo eign aid (cu en US$) Ou Wo ld
in Da a,
(2023)
PRR Pe sonal
emi ance
ecei ed
Pe sonal emi ances ecei ed
(cu en US$)
Wo ld Bank,
(2023)
Md.A. Hasan e al.
Resea ch in Globaliza ion 10 (2025) 100268
6
sq., and means a e among hem. Fo e e y se ies, de elopmen s and
obse a ions a e a ailable. Ou lines some o he a iables’mos signi -
ican ea u es and gi es he esul s o he desc ip i e s a is ics. The
componen s ha e a ying a e age alues; emi ances ha e he lowes
mean alue, while heal h expenses ha e he g ea es mean alue. The
skewness o all he a iables is posi i e. While mos a iables ha e ew
ou lie s and display pla yku osis o nega i e ku osis, FDI displays
lep oku osis o posi i e excess ku osis.
3.2. Theo e ical model
This s udy explo es he impac o go e nmen heal h spending on
heal h ou comes in Sou h Asian coun ies, excluding A ghanis an and
Bhu an, using G ossman’s heal h p oduc ion model. Acco ding o
G ossman (2017), he cos o heal hca e and o he consume goods can
a ec people’s sa is ac ion wi h p oducing and consuming heal h. A lo
o o he esea ch also uses G ossman’s heal h p oduc ion unc ion as
hei heo e ical model, o example (Bala e al., 2022; Bolin &Capu o,
2017; Hwang &Sakong, 2019; Labon ´
e, 2019b; Liljas, 1998; Mhlanga,
2021; No ignon e al., 2012), e c. The G ossman model p o ides a o -
mula o measu ing heal h p oduc ion unc ion.
H= (x)(1)
The equa ion below shows how each pe son’s heal h ou pu is
measu ed. The le e H ep esen s a measu e o he heal h quali y index
(HQI). The le e X ep esen s a collec ion o di e en inpu s o he
heal h p oduc ion unc ion. These inpu s in ou s udy include go e n-
men heal h expendi u es (HE), o eign aid (FA), in lows o o eign
di ec in es men (FDI), and pe sonal emi ances ecei ed (PRR) in his
s udy as he main ocus o his s udy is o examine he ela ionship be-
ween ex e nal economic ac o s and heal h quali y. In p e ious s udies
like Immu ana (2020), Sha iq and Gillani (2020), Asiama and Qua ey
(2009), and Anyanwu and E hijakpo (2007), he e ec o hese a i-
ables was calcula ed sepa a ely on heal h ou comes. The H ec o ep-
esen s heal h ou come o quali y, and i may include any ac o ha can
show he scena io o heal h s a us. In ou s udy, we include ou com-
ponen s in he H ec o o ep esen heal h quali y: incidence o ube -
culosis, li e expec ancy, in an mo ali y a e, and ma e nal mo ali y
a io. Howe e , in p e ious s udies, such as (Chiappini e al., 2022b;
No ignon e al., 2012; P adhan and Khan (2015)), heal h ou comes we e
measu ed by only one o wo o hese a iables. I is possible o de ine
he empi ical links be ween heal h inpu s and heal h ou comes as
ollows.
HQIi =β0+β1HEi +β2FAi +β3FDIi +β4PRRi +
ε
i (2)
Equa ion (3) HQI is used o measu e he heal h quali y index in his
s udy. This index is de e mined by se e al ac o s such as he incidence
o ube culosis, ma e nal mo ali y a io, in an mo ali y a e, and li e
expec ancy a bi h. Fu he mo e, o eign aid (FA), o eign di ec in-
es men in lows (FDI), heal h expendi u e (HE), and pe sonal emi -
ance ecei ed (PRR) a e conside ed independen a iables. He e β0is
he in e cep and β1 o β4a e slope coe icien s o di e en independen
a iables and
ε
i is he e o e m o measu e de ia ions.
3.3. Econome ic es ima ion
3.3.1. Augmen ed mean g oup es
To ensu e ha c oss-sec ional dependence and pa ame e he e oge-
nei y a e aken in o conside a ion (Sence A asoy, 2017), he AMG
p oposed by (Ebe ha d e al., 2010; Ebe ha d &Bond, 2009) is used.
When analyzing panel da a, he Augmen ed Mean G oup (AMG) es i-
ma o has se e al bene i s. Fi s o , i e icien ly cap u es bo h c oss-
sec ional a ia ion and ime-se ies dynamics by pe mi ing he e oge-
neous pa ame e es ima es ac oss indi idual uni s while also pooling
in o ma ion ac oss uni s (Ebe ha d &Teal, 2010). Second, by including
lagged a iables and o he con ol a iables, he AMG es ima o mi i-
ga es possible endogenei y p oblems and imp o es he obus ness o he
es ima ion esul s (O hman e al., 2018). Thi dly, he AMG es ima o
minimizes bias and inc eases e iciency in p edic ing long- un co-
e icien s by adding lagged a iables o he g oup mean es ima o . This
is especially use ul when he e is a sho ime-se ies dimension
compa ed o he c oss-sec ional dimension (Pesa an &Smi h, 1995).
How hese es ima o s es ima e he unobse ed s anda d componen s is
he p ima y dis inc ion. The AMG es ima o pe mi s c oss-sec ional
dependence by es ima ing he unobse ed join dynamic impac while
accoun ing o he s anda d dynamic e ec pa ame e . A e adding ime
dummies o he o mula, he i s di e ence OLS is used o es ima e.
Δyi =
α
1i +βiΔXi +φi +∑
T
=2
τ
DUMMY +
ε
i (3)
We assign a uni coe icien o e e y g oup membe o build a
eg ession model ha is unique o ha g oup. The AMG es ima o is
sub ac ed om he dependen a iable o achie e his. The in e cep
cap u es he ime-in a ian ixed e ec s in each eg ession. We apply he
mean g oup es ima e o AMG.
AMG =N−1∑
N
i=1
βi(4)
He e
βiis he coe icien es ima o .
3.3.2. Robus ness check
This s udy u ilizes h ee ecen panel da a es ima o s o add ess he
c oss-sec ional dependency and slope he e ogenei y p oblems o he
da ase . To assess he consequences o AMG eg ession, we included he
D iscoll-K aay s anda d e o (D-K SE) me hod as a obus ness es ,
p oposed by (D iscoll &K aay, 1998). Unlike o he eg ession p oced-
u es, his echnique yields eliable and immacula e indings e en when
dealing wi h CSD. The me hod is capable o add essing missing alues as
well (Danish e al., 2019). The D-K s anda d e o is also a use ul me hod
o dealing wi h he e oscedas ici y o longi udinal and se ial depen-
dence wi hin he pa adigm o ixed e ec s (Danish e al., 2019). Mo e-
o e , i applies o bo h balanced and imbalanced panel da a se s,
allowing o a mo e ex ended pe iod and mo e lexibili y due o i s use o
Table 3
Summa y s a is ics.
HQI HE FDI FA PRR
Mean −7.94E-10 135.0841 5.41E +09 8.61E +08 2.76E +08
Median −0.526273 42.23648 7.12E +08 5.79E +08 7.593543
Maximum 3.538248 993.4720 6.44410 3.47709 3.066009
Minimum −3.16603 8.338082 −6647984 5170000. 0.077343
S d.De 1.671682 229.4762 1.250010 8.1000008 7.020008
Skewness 0.52974 2.339349 2.765608 1.158262 2.535668
Ku osis 2.426585 7.257731 9.774297 3.614196 8.281825
Sum −1.00E-07 17020.60 6.81E +11 1.08E +11 3.48E +10
Sum Sq.De 349.3152 6582418. 1.95E +22 8.20E +19 6.17E +19
Obse a ions 126 126 126 126 126
Md.A. Hasan e al.
Resea ch in Globaliza ion 10 (2025) 100268
7
a non-pa ame ic me hod. Equa ion (6) ep esen ing he eg ession o
D iscoll K aay’s s anda d e o is as ollows:
V(
α
) = (XʹX)−1
ST(XX)−1(6)
When slope he e ogenei y and c oss-sec ional dependence a e key
issues o add ess, he CCEMG es ima o is a obus choice in panel da a
models. E en in he ace o hose econome ic challenges, i deli e s
unbiased and consis en es ima es. To de e mine he mean g oup es i-
ma o o he CCE, compu e he a e age o e e y coe icien ac oss all
indi idual eg ession as desc ibed below:
CCEMG =N−1∑
N
i=1
βi(7)
whe e
βi ep esen s he coe icien es ima ions.
Finally, his s udy applied he Gene alized Me hod o Momen
(GMM) app oach o check whe he he e is any lagged e ec o he
dependen a iable exis s o no . Se e al no able ad an ages o he
GMM me hod a e a ailable. Fi s ly, i s , i does no need he assump ion
o no mali y. Second, he applied model is obus o he e oscedas ici y
wi hin he model. Thi d, GMM can p o ide es ima ion o pa ame e s
e en when he model canno be sol ed ully analy ically, and wi h some
lexibili y in how o choose he se o ins umen al a iables. GMM hen,
is pa icula ly good a dealing wi h endogenei y in he dependen a -
iable, he independen a iable, o he e o e m. This s udy applied he
ollowing GMM p oposed by (A ellano &Bond, 1991),
HQIi =β0+β1HQIi −1+β2HEi +β3FAi +β4FDIi +β5PRRi +
ε
i (8)
3.3.3. Causali y es
G ange (1969) c ea ed a es o de e mine whe he he a iables a e
causally ela ed. Howe e , i has se e al sho comings, such as he es ’s
inaccu acy when c oss-sec ional dependency (CSD) is p esen . Fo his
eason, his s udy employed a mo e ad anced e sion o he D-H cau-
sali y assessmen , de eloped by (Dumi escu &Hu lin, 2012). As a
esul , he D-H assessmen is applied, which is be e a aking CSD in o
accoun han he panel G ange causali y analysis. One app oach o
exp ess he D-H panel causali y would be as ollows:
Zin =δi+∑
k
k−1
Yk
iZi(n−k)+∑k
k−1θk
iXi(n−k)+
ε
in (9)
whe e X and z ep esen he obse ables, Yk
i ep esen s an au o eg essi e
pa ame e , and θk
ideno es he es ima ions o he eg ession coe icien .
Fig. 3 ep esen s he da a analysis p ocess and echnique o his s udy.
4. Resul s and discussion
4.1. Co ela ion me ics
The esul s o he co ela ion analysis will show i he a iables ha e
a posi i e o nega i e connec ion. Table 4 shows ha HE and HQI ha e a
posi i e connec ion (0.2340), whe eas FA and HE ha e he g ea es and
mos signi ican nega i e co ela ion (−0.4305). Highe emi ances a e
ypically linked o wo se heal h quali y, as shown by he s a is ically
signi ican nega i e associa ion be ween emi ance ecei ed and he
heal h quali y index (−0.2540). I is signi ican o no e ha he co e-
la ion coe icien s o all a iables a e less han 0.70, excep o FDI and
emi ance ecei ed. This sugges s he absence o mul icollinea i y.
4.2. Mul i-collinea i y es
The chosen a iables show no mul i-collinea i y, as suppo ed by a
a iance in la ion ac o o less han 10. The co ela ion esul s also
indica e no mul i-collinea i y, excep o o eign aid, which co ela es
wi h o he independen a iables g ea e han 0.5. The esul s o he
mul icollinea i y es a e s a ed in Table 5.
4.3. C oss-Sec ional dependency es
Table 6 ep esen s he c oss-sec ional dependency es sugges ed by
Pesa an. The e is s ong e idence ha con adic s he null hypo hesis o
c oss-sec ional independence o all a iables, as indica ed by he CD-
es s a is ics and co esponding p- alues. The a e age join T alue is
he same (21.0) ac oss all a iables. The mean
ρ
( ho) alues, which
ep esen he a e age pai -wise co ela ion coe icien s be ween c oss-
sec ional uni s, a y om 0.12 (PRR) o 0.94 (HE). Simila ly, he
mean abs(
ρ
) alues, which ep esen he a e age absolu e pai -wise
co ela ions, a y om 0.37 (PRR) o 0.95 (HQI). All o hese indings
sugges ha he e is a signi ican c oss-sec ional dependency in he da a,
wi h he a iables PRR and HQI showing he leas c oss-sec ional
dependence among hose conside ed and HE and HQI showing he mos .
4.4. Uni oo es
Due o ha ing CSD in he da ase , his s udy employs wo 2nd gen-
e a ion uni oo es s, CADF and CIPS. The 2nd gene a ion uni oo es
esul s o he a iables PRR, FDI, FA, HE, and HQI a e displayed in
Table 7. CADF es shows ha all he a iables excep HQI a e non-
s a iona y a he le el, bu hey become s a iona y a e aking he
i s di e ence. Bu HQI is s a iona y a le el. CIPS es shows ha wo
a iables (PRR and HQI) a e s a iona y a he le el, and he emaining
a iables a e s a iona y a he di e ence.
4.5. Slope homogenei y es
The esul s o he slope homogenei y es a e shown in Table 8. The e
a e signi ican di e ences in he slopes o he da a be ween g oups o
o e ime, as indica ed by he es s o slope homogenei y. he
Δand
Δ
adj es s ejec he null hypo hesis o slope homogenei y, as hei p-
alues a e e y low (0.000). I is c ucial o conside hese a ia ions
Fig. 3. Da a analysis echniques.
Table 4
Co ela ion es .
HQI HE FDI FA PRR
HQI 1.0000
HE 0.2340*** 1.0000
FDI 0.1059 −0.1524* 1.0000
FA 0.0175 −0.4305*** 0.5891*** 1.0000
PRR −0.2510** −0.1800** −0.1037 0.3149*** 1.0000
***p <0.1, **p <0.5, *p <0.10.
Md.A. Hasan e al.
Resea ch in Globaliza ion 10 (2025) 100268
8
while analyzing and in e p e ing he da a since hey imply di e en
co ela ions be ween he a iables ac oss g oups o pe iods.
4.6. Augmen ed mean g oup (AMG) es ima o es
The AMG es ima o esul s display he es ima ed coe icien s, s an-
da d e o s, and z- alues o he independen a iables HE, FDI, FA, and
PRR along wi h he cons an componen (_cons) in Table 9. The coe i-
cien o HE is −0.0004316 wi h a z- alue o −1.85, and i is s a is ically
insigni ican a a 5 % le el as he p- alue is 0.064. I e e s ha a ise in
heal h expendi u e will causes a small de e io a ion in heal quali y. This
may occu due o co up ion and mismanagemen in heal h sec o in
Sou h Asia. Simila ly, he coe icien o PRR is −0.0078775 wi h a z-
alue o −2.21, which is s a is ically signi ican a 5 % le el. This implies
ha a 1 % inc ease in PRR is associa ed wi h a 0.78775 % educ ion in
he dependen a iable, ce e is pa ibus. Acco ding o he AMG inding
emi ance con ibu e posi i ely o ise heal h s anda d o Sou h Asian
coun ies al hough i is e y small. In sou h Asian coun ies emi ance
usually no being di ec ed o he imp o emen o heal sec o as heal is
he leas p io i y sec o in hese coun ies. On he o he hand, he co-
e icien o FDI is 3.94e-12 wi h a z- alue o 1.80, which is s a is ically
signi ican a a 10 % le el wi h a p- alue o 0.071. I indica es ha FDI
ha e a small posi i e ole on heal h quali y o Sou h Asia. FDI helps o
ise income le el and li ing s anda d o he people which con ibu e
posi i ely o ise heal quali y in Sou h Asian coun ies. The FA coe i-
cien is 8.83e-11, and he z- alue o 3.03 indica es ha i is s a is ically
signi ican a a 1 % le el. This means ha a 1 % inc ease in FA is linked
o a 0.0000000883 % inc ease in he dependen a iable, gi en ha all
o he a iables emain cons an . I implies ha o eign aid has small bu
signi ican posi i e ole in de eloping heal h quali y o Sou h Asian
coun ies. Because o eign aid o en comes o hese coun ies as a o m o
medical assis ance. Fu he mo e, he cons an e m (_cons) has a coe -
icien o −1.965414, which is s a is ically signi ican a a 1 % le el wi h
a z- alue o −3.22. When all independen a iables a e ze o, his
cons an e m ep esen s he alue o he dependen a iable. In
conclusion, he esul s indica e ha while HE and FDI a e no s ong
p edic o s in his model, FA and PRR ha e a signi ican impac on he
dependen a iable.
4.7. Robus ness es
Table 10 p esen s h ee dis inc echniques o es ima ing he co-
e icien s o he gi en a iables −GMM, D iscoll-K aay, and CCEMG.
The a iables HE, PRR, and FA show s a is ical signi icance in all ech-
niques, wi h PRR ha ing a nega i e coe icien bu HE and FA ha ing a
posi i e coe icien . The a iables HE, FA, and PRR a e signi ican a he
1 % le els in bo h D iscoll-K aay and CCEMG app oaches bu he sig-
ni icance a ies in he GMM app oach. All app oaches indica e ha he
cons an e m (_cons) is s a is ically signi ican . Howe e , i is nega i e
in bo h D iscoll K aay and CCEMG es s bu posi i e acco ding o he
GMM me hod.
5. Discussion
This s udy in es iga es he impac o o eign aid, FDI in lows, e-
mi ances, and heal h expendi u es on he heal h quali y index o Sou h
Table 5
Va iance In la ion Fac o (VIF) o Inqui ing Mul i-collinea i y.
Va iable VIF 1/VIF
HE 1.25 0.798973
FDI 1.82 0.550867
FA 2.30 0.434493
PRR 1.29 0.772760
Mean VIF 1.67
Table 6
C oss-Sec ion Dependency Tes .
Va iable CD- es p- alue a e age join T mean
ρ
mean abs(
ρ
)
HQI 6.597*** 0.000 21.00 0.37 0.95
HE 16.613*** 0.000 21.00 0.94 0.94
FDI 8.913*** 0.000 21.00 0.50 0.51
FA 3.713*** 0.000 21.00 0.21 0.38
PRR 2.098*** 0.036 21.00 0.12 0.37
***p <0.1, **p <0.5, *p <0.10.
Table 7
CADF and CIPS uni oo es .
Va iables CADF CIPS
Le el A 1s Di e ence S a iona i y Le el A 1s Di e ence S a iona i y
HQI −0.610** I (0) −2.865*** I (0)
HE 0.722 −2.142*** I (1) −1.383 −3.966*** I (1)
FDI −0.446 −2.937*** I (1) −2.326 −4.488*** I (1)
FA 1.114 −1.293* I (1) −1.233 −3.892*** I (1)
PRR 1.144 −1.362* I (1) −1.481* I (0)
***p <0.1, **p <0.5, *p <0.10.
Table 8
Slope Homogenei y Tes s.
Δp- alue
Δ es 10.951*** 0.000
Δadj es 12.957*** 0.000
***p <0.1, **p <0.5, *p <0.10.
Table 9
AMG es ima o .
Va iable Coe icien S anda d e o Z- alue P alue
HE −0.0004316* 0.0028407 −1.85 0.064
FDI 3.94e-12* 2.36e-11 1.80 0.071
FA 8.83e-11*** 2.92e-11 3.03 0.002
PRR −0.0078775** 0.003566 −2.21 0.027
_cons −1.965414*** 0.6112609 −3.22 0.001
Wald chi2(2) =4.90
P ob >chi2 =0.0863
***p <0.1, **p <0.5, *p <0.10.
Table 10
GMM, D iscoll K aay, and CCEMG Tes .
Va iables GMM CCEMG D iscoll-K aay
HE 0.0013832** 0.0047595*** 0.0020681***
FDI −1.47e-12 −8.15e-12 −2.96e-12
FA 1.82e-11* 2.02e-11*** 4.98e-10***
PRR −1.11e-12** −0.0217629*** −6.69e-10***
_cons 0.1024126*** −0.1109265* −0.5076288*
***p <0.1, **p <0.5, *p <0.10.
Md.A. Hasan e al.
