Umai , Muhammad e al.
A icle
Empowe ing Pakis an's economy: The ole o heal h
and educa ion in shaping labo o ce pa icipa ion and
economic g ow h
Economies
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Ci a ion: Umai , Muhammad, Waqa
Ahmad, Baba Hussain, Cos inela
Fo ea, Monica Lau a Zla i, and
Valen in Ma ian An ohi. 2024.
Empowe ing Pakis an’s Economy:
The Role o Heal h and Educa ion in
Shaping Labo Fo ce Pa icipa ion
and Economic G ow h. Economies 12:
113. h ps://doi.o g/10.3390/
economies12050113
Academic Edi o : B uce Mo ley
Recei ed: 31 Ma ch 2024
Re ised: 26 Ap il 2024
Accep ed: 30 Ap il 2024
Published: 9 May 2024
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4.0/).
economies
A icle
Empowe ing Pakis an’s Economy: The Role o Heal h and
Educa ion in Shaping Labo Fo ce Pa icipa ion and
Economic G ow h
Muhammad Umai 1, Waqa Ahmad 2,* , Baba Hussain 2, Cos inela Fo ea 3, Monica Lau a Zla i 3and
Valen in Ma ian An ohi 3
1Depa men o Economics, Eme son Uni e si y Mul an, Mul an 60000, Pakis an; [email p o ec ed]
2School o Economics, IIIE, In e na ional Islamic Uni e si y Islamabad, Islamabad 44000, Pakis an;
baba [email p o ec ed]
3Depa men o Business Adminis a ion, Duna ea de Jos Uni e si y o Gala i, 800008 Gala i, Romania;
[email p o ec ed] (C.F.); [email p o ec ed] (M.L.Z.); [email p o ec ed]o (V.M.A.)
*Co espondence: [email p o ec ed]
Abs ac : The labo o ce is a c ucial ac o in conduc ing economic ac i i ies, especially in labo -
su plus coun ies like Pakis an. In his s udy, we explo e he impac o labo o ce pa icipa ion (LF)
on economic g ow h (EG), wi h an emphasis on how his impac depends on he le els o heal h
and educa ion expendi u es. We analyze ime se ies da a om Pakis an spanning om 1980 o
2022, using ARDL (Au o eg essi e Dis ibu ed Lag), ECM (E o Co ec ion Model) and G ange
causali y echniques o empi ical analysis. The ARDL esul s indica e ha LF signi ican ly boos s
EG, bo h in he sho and long un. Fu he mo e, he es ima ions e eal ha be e acili ies o
heal h and educa ion s eng hen he posi i e e ec s o LF on EG. This sugges s a complemen a y
ela ionship be ween heal h, educa ion, and LF in d i ing EG. Mo eo e , ou indings highligh he
empo al signi icance o heal h and educa ion: Heal h plays a mo e c ucial ole in he sho un,
while educa ion’s impac is mo e subs an ial in he long un. Fu he mo e, he G ange causali y
esul s indica e ha LF, heal h, and educa ion signi ican ly con ibu e o EG. I is ad isable o he
go e nmen o p io i ize in es men s in he heal h and educa ion sec o s. This app oach can empowe
indi iduals o ac i ely and e ec i ely pa icipa e in economic ac i i ies, e en ually con ibu ing o
he o e all economic ou pu o he na ion.
Keywo ds: labo o ce pa icipa ion; economic g ow h; heal h; educa ion; ARDL
JEL Classi ica ion: J21; O40; I12; I22; C22
1. In oduc ion
Human capi al, encompassing educa ion and heal h, s ands as a key asse shaping a
coun y’s economic p og ess, pa icula ly in de eloping economies (Huay and Bani 2018).
In es ing in human capi al o ma ion is o u mos impo ance. This in es men is aimed
a ensu ing ha a coun y’s wo k o ce is well in o med, skilled, p oduc i e, and in good
heal h. Such a wo k o ce is essen ial o e ec i ely binding and u ilizing he na ion’s
esou ces o os e g ow h and de elopmen (Kanayo 2013).
In he 1980s, a signi ican shi occu ed in he unde s anding o ac o s d i ing
economic g ow h. This e a ma ked a pi o al momen whe e economis s began o ee alua e
he adi ional d i e s o g ow h, conside ing a wide a ay o elemen s such as educa ion,
heal h, esea ch and de elopmen , echnological ad ancemen s, e ol ing go e nmen oles,
in o ma ion accumula ion, inancial inno a ions, economies o scale, income dis ibu ion,
and o he p oduc ion ac o s (Bedi 2016).
In he 1990s, economis s shi ed hei ocus owa d unde s anding he pi o al ole
o human capi al in d i ing p oduc i i y and os e ing g ow h. Economis s inc easingly
Economies 2024,12, 113. h ps://doi.o g/10.3390/economies12050113 h ps://www.mdpi.com/jou nal/economies
Economies 2024,12, 113 2 o 21
began o ecognize ha human capi al in es men , pa icula ly h ough heal h and educa-
ion, signi ican ly in luences a na ion’s abili y o inno a e, p oduce e icien ly, and sus ain
long- e m g ow h. Pionee ing s udies by economis s like Ba o (1991), Mankiw e al. (1992),
Ba o and Lee (1994), Galo and Tsiddon (1997), and Ba o (2003) p o ided seminal insigh s
in o he linkage be ween human capi al in es men and economic g ow h. These wo ks
no only unde sco ed he impo ance o nu u ing human po en ial bu also illumina ed
he pa hways h ough which in es men s in educa ion, heal hca e, and skill de elopmen
ansla e in o angible economic gains. This e ol ing na a i e no only eshaped economic
heo ies bu also esona ed wi h eal-wo ld policies, highligh ing he impe a i e o na-
ions o p io i ize human de elopmen as a s a egic impe a i e o sus ainable g ow h
and p ospe i y.
The labo o ce con ibu es o os e ing economic g ow h. This con ibu ion occu s
bo h di ec ly, as hey se e as he p ima y p o ide s o he essen ial inpu o p oduc ion,
and indi ec ly, gi en hei subs an ial impac on he o e all human en i onmen . The
cha ac e is ics o he labo o ce and he quali ies o he wo k hey p o ide a e in insically
linked (Du and 2015). Ne e heless, sus ained economic g ow h has emained elusi e
o any na ion ha has no made subs an ial in es men s in human capi al de elopmen .
Among highly educa ed segmen s o he popula ion, scien is s and echnicians s and ou as
ha ing a compa a i e ad an age in g asping and in eg a ing new o exis ing ideas in o
p oduc ion p ocesses. Human capi al de elopmen is iewed as bo h an end goal and a
means o achie e de elopmen . I se es as a means o unlocking people’s ull po en ial,
enhancing hei capabili ies, and, c ucially, empowe ing hem o ac i ely pa icipa e in
hei own de elopmen al jou ney (Xia e al. 2022).
The ag icul u e sec o is a majo con ibu o o Pakis an’s GDP (g oss domes ic p od-
uc ), and skilled ag icul u is s can enhance i s yield by u ilizing mode n and e ec i e
s a egies. Educa ed ag icul u is s and a me s can inco po a e he la es esea ch in hei
ield, such as pes icides, nu ien s, e ilize s, and a ious cul i a ion and ha es ing
echniques (Iqbal e al. 2001). I can be a gued ha skilled indi iduals a e supe io o
unskilled indi iduals; o ins ance, educa ed a me s, ca pen e s, eache s, accoun an s,
skilled labo e s, and specialis s can deli e be e esul s (Rais e al. 2015).
In es men s in educa ion by go e nmen s a e c ucial o add essing majo economic
challenges like ecessions, po e y, and unemploymen . Such spending is c ucial o expand-
ing he pool o skilled wo ke s and mee ing he e ol ing demands o a ious economic
sec o s (Mehme aj and Xhindi 2022). As highligh ed by Villela and Pa edes (2022), spending
on educa ion yields bo h sho - e m and long- e m bene i s by enhancing he employabili y
o wo ke s and bols e ing hei con ibu ions o he labo ma ke . The e o e, p io i izing
educa ion unding is essen ial o os e ing sus ainable economic g ow h and ensu ing a
skilled wo k o ce capable o mee ing he demands o he mode n economy.
Pakis an has adi ionally concen a ed i s e o s on planning and accumula ing
physical capi al o uel apid g ow h and de elopmen , equen ly igno ing he signi icance
o human capi al in he de elopmen p ocess. I is c ucial o unde s and ha acili a ing
g ow h is no solely achie able h ough p omo ing physical in es men s like in as uc u e,
communica ion, and ene gy gene a ion and dis ibu ion. Equally essen ial a e in es men s
in human capi al, which encompass a eas such as heal hca e, educa ion, and aising
li ing s anda ds (Islam and Alam 2023). Resea che s widely ag ee ha making physical
in es men s alone would no be enough o e ec i ely add ess Pakis an’s p oblems wi h
po e y and inequali y. Fac o s like inadequa e educa ional oppo uni ies, limi ed access o
heal hca e, and high unemploymen a es signi ican ly impede economic g ow h. Thus,
i is impe a i e o acknowledge he pa amoun impo ance o human capi al o ma ion
in d i ing economic g ow h and o inc ease in es men s in he ields o heal hca e and
educa ion (Zhao and Zhou 2021).
Human capi al o ma ion is o u mos impo ance o na ions wi h an excess o labo .
In such coun ies, whe e he labo o ce exceeds he demand, ha ing an e icien and skilled
wo k o ce becomes c ucial o boos ing economic ac i i ies (Mankiw e al. 1992). The
Economies 2024,12, 113 3 o 21
majo i y o de eloping na ions a e ac i ely pu suing indus ializa ion, and he p esence
o a well- ained labo o ce is a equi emen o he accu a e unc ioning o indus ies. A
skilled and educa ed wo k o ce is be e equipped o ope a e mode n machine y, plan s,
and a ious elec onic and mechanical de ices. Hence, human capi al o ma ion is essen ial
o add ess hese challenges and enable a mo e e icien con ibu ion o skilled labo o
p oduc ion ac i i ies (Baha in e al. 2020). In con as , indi iduals who a e in poo heal h o
lack educa ion ind i challenging o compe e wi h he inno a ions o he es o he wo ld.
To ackle his issue, many de eloping na ions ely on o eign esou ces, such as aid, loans,
and echnical assis ance. A case in poin is Pakis an, whe e he go e nmen has s uggled
o alloca e o eign assis ance anspa en ly o he de elopmen o human capi al, esul ing
in nega i e economic consequences (Ali e al. 2012).
As discussed abo e, be e educa ion and heal hca e a e i al in enhancing he p o-
duc i i y o he labo o ce. Pakis an’s economy is p ima ily dependen on ag icul u e,
and educa ion se es as a ca alys o a me s o e ine hei a ming p ac ices (Qad i
and Waheed 2011). Educa ion enables a me s o inco po a e mode n echnology and he
la es esea ch indings in o hei cul i a ion and ha es ing echniques. Fu he mo e, an
educa ed and heal hy labo o ce p o es o be mo e e icien in he indus ial sec o as
well (Islam 2020). Many s udies in he exis ing li e a u e ha e empi ically examined he
e ec o he labo o ce, educa ion, and heal h on Pakis an’s economic g ow h (e.g., Ak am
e al. 2008;Hassan and Ra az 2017;Ha eez and Rahim 2019;Ja ed 2021). Howe e , o he
bes o ou knowledge, no s udy has ye examined he in e media y ole o heal h and
educa ion on he labo o ce–economic g ow h nexus in Pakis an. The e o e, ou s udy
del es in o an explo a ion o how he labo o ce a ec s economic g ow h in Pakis an and
how his e ec depends on he le els o heal h and educa ion. Pakis an se es as a ocal
poin o his discussion because o i s labo -in ensi e economy. This s udy holds pa icula
signi icance as i encompasses bo h heal hca e and educa ional dimensions wi hin he labo
o ce pa icipa ion–economic g ow h nexus.
The s udy is o de ed as ollows: Sec ion 2discusses he ela ed li e a u e. In Sec ion 3,
he heo e ical unde pinnings a e explo ed. Sec ion 4highligh s he da a and me hodol-
ogy u ilized. Sec ion 5p esen s he s udy’s indings and hei in e p e a ions. Sec ion 6
summa izes he s udy and o e s policy ecommenda ions.
2. Li e a u e Re iew
The signi icance o labo o ce pa icipa ion, heal h, and educa ion in a coun y’s
economic g ow h is widely acknowledged. Nume ous s udies in he exis ing li e a u e
ha e iden i ied hese componen s as impo an ac o s in he g ow h p ocess. Fo ins ance,
Ha eez and Rahim (2019) del ed in o how di e en elemen s o building human capi al,
such as ac i e pa icipa ion in he wo k o ce, in es men s in heal hca e, and educa ional
ad ancemen s, con ibu e o Pakis an’s economic p og ess. Thei indings highligh ed a
s ong and bene icial ela ionship be ween hese aspec s o human capi al de elopmen
and he coun y’s economic g ow h. This sugges s ha nu u ing human esou ces h ough
inc eased pa icipa ion, imp o ed heal h p o isions, and enhanced educa ion no only
en iches indi iduals bu also uels b oade economic p ospe i y in Pakis an. Simila ly,
Hassan and Ra az (2017) ound ha inc eased emale labo o ce pa icipa ion posi i ely
con ibu es o Pakis an’s GDP, wi h emale educa ion exhibi ing a a o able associa ion
wi h he emale labo o ce pa icipa ion a e. In a ecen s udy by Hamdan e al. (2020),
i was ound ha he link be ween spending on educa ion and economic ad ancemen in
Saudi A abia is no as s aigh o wa d as p e iously assumed. Thei esea ch sugges s
ha while in es ing in educa ion is c ucial, i may no di ec ly ansla e in o subs an ial
economic g ow h in he Saudi con ex . This inding challenges he adi ional no ion
ha highe educa ion expendi u e au oma ically leads o signi ican economic bene i s. I
unde sco es he complexi y o ac o s in luencing economic de elopmen , highligh ing
he need o a mo e nuanced unde s anding o how educa ional in es men s in e ac wi h
b oade economic dynamics in Saudi A abia.
Economies 2024,12, 113 4 o 21
Fu he mo e, Qi e al. (2022) explo ed he ela ionship be ween highe educa ion and
economic g ow h in China. They no ed a signi ican connec ion be ween hese wo ac o s.
Howe e , hey ound ha simply inc easing he use o highe educa ion did no lead o
posi i e impac s on economic g ow h. Ins ead, hei indings highligh ed he impo ance o
a ge ed go e nmen spending on skilled educa ion and a ocus on high- ech indus ies,
which we e associa ed wi h highe le els o economic g ow h. In addi ion, Tu han e al.
(2023) shed ligh on an in e es ing aspec o economic sus ainabili y. They ound ha
he p og ess o BRICS (B azil, Russia, India, China and Sou h A ica) economies owa d
economic sus ainabili y was no ably in luenced by wo key ac o s: he de elopmen o
he inancial sec o and ad ancemen s in educa ion. Thei esea ch showed a clea and
posi i e connec ion be ween hese ac o s and he o e all sus ainabili y le els o hese
economies. This sugges s ha a well-de eloped inancial sec o , coupled wi h s ong
educa ional achie emen s, plays a i al ole in os e ing economic sus ainabili y wi hin he
BRICS na ions. Mo eo e , he indings iden i y ha educa ional a ainmen has a s onge
impac compa ed o inancial sec o de elopmen . Consequen ly, bo h a e ecognized as
aluable ools o p omo ing economic sus ainabili y.
Halıcı-Tuluce e al. (2016) ound an in e es ing ela ionship be ween public heal h
spending and economic g ow h. Thei s udy sugges s ha when go e nmen s in es mo e
in public heal h, i ends o boos economic g ow h. On he o he hand, hey no ed ha
p i a e heal h expendi u es ha e he opposi e e ec , po en ially dampening economic
g ow h. This highligh s he complex in e play be ween heal hca e inancing sou ces and
hei impac s on b oade economic ou comes. In hei ecen s udy ocusing on Tu key,
Esen and Kecili (2021) del ed in o he in ica e dynamics be ween heal hca e spending and
economic ou pu . Thei esea ch shed ligh on how inc eased in es men s in heal hca e
can bols e he o e all ou pu and pe o mance o he economy. By dedica ing mo e
esou ces o heal hca e, Tu key no only enhances i s ci izens’ well-being bu also lays a
s onge ounda ion o sus ained economic g ow h. This unde sco es he i al link be ween
heal hca e policies and economic p ospe i y, emphasizing he impo ance o s a egic
in es men s in heal hca e in as uc u e and se ices. In a s udy by Eggoh e al. (2015), hey
es ima ed a no ewo hy co ela ion be ween educa ion, heal hca e, and economic g ow h
in a ious A ican coun ies. Thei indings shed ligh on he impac o public in es men s
in heal hca e and educa ion, showing ha hese in es men s in luence economic g ow h
posi i ely. Howe e , hey also no ed ha he manne in which hese in es men s a e
managed can ei he enhance o impede hei e ec i eness. Thei esea ch highligh ed a
syne gis ic connec ion be ween spending on educa ion and heal hca e, emphasizing he
impo ance o simul aneously inc easing in es men s in bo h sec o s. Fu he mo e, hei
s udy s essed he need o enhance he e iciency o hese in es men s o maximize hei
impac on human capi al de elopmen and subsequen ly on economic g ow h.
Fu he mo e, Singh e al. (2022) examined he con ibu ion o educa ion and aining
o ob ain he Sus ainable De elopmen Goals (SDGs) in alignmen wi h Saudi Vision
2030, a ision ha highligh s he impo ance o he knowledge economy. The indings
show a a o able con ibu ion o educa ion and aining o GDP g ow h. The e o e, i is
ecommended ha he go e nmen inc ease i s in es men s in educa ion as well as aining
o op imize he alignmen be ween he SDGs, he eby acili a ing sus ainable job c ea ion,
enhancing human capi al, ad ancing socioeconomic empowe men ia echnology, and
os e ing GDP g ow h. Siddique e al. (2018) explo ed he educa ion, heal h, and GDP
g ow h nexus in 76 de eloping economies. Thei empi ical indings e ealed ha heal h
expendi u es s imula e GDP g ow h. Addi ionally, he esul s indica ed ha highe le els
o seconda y and e ia y educa ion had a a o able e ec on he g ow h le el, while labo
had an ad e se e ec on i . Thei s udy sugges ed ha coun ies, especially lowe -income
na ions, should p io i ize in es men s in educa ion and imp o ed heal hca e acili ies o
o e all imp o emen .
In he same ein, Ak am e al. (2008) examined how a ious indica o s o heal h a ec
economic p og ess in Pakis an. The indings indica ed ha in he long un, heal h indica-
Economies 2024,12, 113 5 o 21
o s con ibu e o he ise in economic p og ess; howe e , hey do no exe a signi ican
in luence in he sho un. Fu he mo e, Ja ed (2021) explo ed he ela ionship be ween
educa ion and heal h s anda ds on economic p og ess in Pakis an. The esul s s ongly
suppo he no ion ha bo h heal h and educa ion s anda ds con ibu e posi i ely o he
coun y’s g ow h le el. Mush aq e al. (2013) highligh ed he in ica e dynamics a ec ing
Pakis an’s labo o ce, emphasizing he signi ican oles played by in an mo ali y and
seconda y school en ollmen . Thei indings unde sco ed a nega i e co ela ion be ween
hese ac o s and labo o ce pa icipa ion, indica ing po en ial challenges in wo k o ce
de elopmen s emming om hese ac o s. Mo eo e , hei s udy shed ligh on he nuanced
ela ionship be ween heal h expendi u es and labo o ce dynamics. I no ed a posi i e
sho - e m impac o heal h expendi u e on he labo o ce, sugges ing immedia e bene-
i s such as imp o ed wo k o ce heal h and p oduc i i y. Howe e , his posi i e e ec
appea ed o ape o o e he long e m, hin ing a he need o sus ained in es men s and
comp ehensi e s a egies o main ain he posi i e in luence o heal h expendi u es on he
labo o ce.
In a ecen s udy, Khan e al. (2021) shed ligh on an in e es ing aspec o Pakis an’s
g ow h dynamics, highligh ing he in e wined ela ionship be ween educa ion, heal h,
and economic p ospe i y. Thei esea ch del ed in o how in es men s in educa ion and
heal hca e con ibu e signi ican ly o os e ing economic g ow h wi hin he coun y. The
indings sugges ed ha when indi iduals a e well educa ed and in good heal h, hey a e
mo e p oduc i e con ibu o s o he economy. Simila ly, a heal hie popula ion ends o be
mo e engaged in wo k, esul ing in enhanced p oduc i i y le els ac oss a ious sec o s.
Amin e al. (2012) del ed in o how human capi al de elopmen in luences Pakis an’s
economic g ow h. They looked a ac o s like highe educa ion, p ima y educa ion, and li e
expec ancy as indica o s o human capi al o ma ion. Thei indings highligh ed a posi i e
impac o li e expec ancy and p ima y educa ion on Pakis an’s economic pe o mance.
Howe e , in e es ingly, hey no ed a nega i e co ela ion be ween seconda y educa ion
and economic g ow h in he Pakis ani con ex . Thei s udy sheds ligh on he nuanced
dynamics o human capi al’s ole in economic de elopmen , emphasizing he need o
a comp ehensi e unde s anding o educa ion and heal h me ics in shaping a coun y’s
economic ajec o y. These insigh s can guide policymake s in c a ing a ge ed s a egies
o op imize human capi al in es men s o sus ainable economic p og ess.
3. Theo e ical F amewo k
In de eloping coun ies, a la ge po ion o he labo o ce pa icipa es in ag icul u al
ac i i ies o ea n hei li ing. In he e a o globaliza ion, local indus ies impo new ma-
chine y, equi ing skilled and educa ed people o ope a e i . The skilled and educa ed labo
o ce can easily adap o new me hods and echnicali ies o he machine y, con ibu ing
o ac i e and e icien oles in p oduc ion ac i i ies. In he indus ial sec o , educa ed
and skilled manpowe a e capable o making inno a ions and cap u ing ma ke s. On he
o he hand, ine icien and uneduca ed manpowe can dis up he smoo h and e icien
p oduc ion p ocess (Eggoh e al. 2015). The heo e ical ep esen a ion ela ed o he s udy
is p o ided below.
Solow G ow h Theo y
This heo y is cen e ed on he no ion o economic g ow h and iden i ies h ee unda-
men al componen s ha a e essen ial o os e ing such g ow h, namely physical capi al,
labo o ce, and echnological ad ancemen . The heo y sugges s ha he g ow h o he
economy is achie able h ough physical capi al accumula ion, e ec i ely coupled wi h a
skilled labo o ce and echnology. Fu he mo e, he heo y unde sco es ha he cons uc-
ion o physical capi al is a ainable h ough in es men s and sa ings sou ced domes ically
as well as in e na ionally (Solow 1956;Mankiw e al. 1992). This pe spec i e ex ends
beyond he ea lie Ha od–Doma g ow h model, which ocused p ima ily on he ole o
physical capi al. The Solow g ow h heo y builds upon his ounda ion by emphasizing
Economies 2024,12, 113 6 o 21
he impo ance o human capi al o ma ion, assigning equal signi icance o bo h he labo
o ce and he gene a ion o new ideas (inno a ions) wi hin he p oduc ion unc ion. This
app oach is summa ized in he model h ough a ma hema ical equa ion.
Y = K( ),A( )L( )(1)
He e, Yshows he ou pu le el, Kindica es he capi al, Adeno es he p oduc i i y
o labo , and Lp esen s he labo engaged in he p oduc ion sec o , whe e ep esen s
he ime. In he model, A( )*L( ) ep esen s e ec i e labo . I is impo an o no e ha
echnological p og ess occu s when he le el o knowledge (A) inc eases. The e o e, an
illus a i e ins ance o a p oduc ion unc ion is he Cobb–Douglas unc ion.
Y = (K( ),A( )L( ))
Y =K( )β,A( )L( )1−β
0≺β≺1
Y/AL = (K/AL)β,(AL/AL)1−β
∴y=Y/AL
∴k=K/AL
Though,
y=kβ
y = (k )
(2)
We will adap his p oduc ion unc ion o inco po a e he a iables. Now, we p esen
he dynamic mo emen o capi al, labo , and knowledge o e ime.
K•=K −K( −1)
∂K/K= capi al g ow h a e; capi al is g owing a a e δ.
L•=L −L( −1)
∂L/L= labo g ow h a e; labo is g owing a a e n.
A•=A −L( −1)
∂A/A= knowledge g ow h a e; knowledge is g owing a a e g.
Hence, kequals K( )/A( )L( ).
Applying he quo ien ule, we de i e he equa ion o he ounda ional Solow model
om Equa ion (2).
K•( )= [K•( )(A( )L( ))−(A•( )L( ))K( )−(A( )L•( ))K( )]/(A( )L( ))2
∂K( )= [∂K( )(A( )L( ))−(∂A( )L( ))K( )−(A( )∂L( ))K( )]/(A( )L( ))2
K•( )= [K•( )(A•( )L( ))/(A( )L( ))2−(A•( )L( ))K( )/(A( )L( ))2
−(A( )L•( ))K( )]/(A( )L( ))2
K•
( )=K•
( )/(A( )L( ))−A•
( )K( )/A( )(A( )L( ))−L•
( )K( )/L( )(A( )L( ))
∴K•
( )=sY( )−δK( )
K•( )=sY( )/(A( )L( ))−δK( )/(A( )L( ))−A•( )K( )/A( )(A( )L( ))
−L•( )K( )/L( )(A( )L( ))
∴A•
( )/A( )=g
Economies 2024,12, 113 7 o 21
∴k=K/AL
∴y = (k )
∴L•( )/L( )=n
∴y=Y/AL
Hence,
K•
( )=s (k )−(n+g+δ)k Solow equa ion (3)
whe e (k( )) ep esen s ou pu pe uni o e ec i e labo , while s (k( )) deno es ac ual
in es men pe uni o e ec i e labo . The e m
(n+g+δ)k( )
s ands o b eake en
in es men . The Solow g ow h model suppo s an open ma ke sys em as i encou ages
ade, which boos s domes ic esou ces and sa ings. An open ma ke also a ac s o eign
in es men , leading o he in oduc ion o new echnology and ideas and enhancing he
e iciency o he labo o ce in poo e na ions. This, in u n, s eamlines he p oduc ion
p ocess, and he combina ion o physical and human capi al p e en s diminishing ma ginal
e u ns. The e o e, he Solow g ow h heo y places signi ican impo ance on human capi al
de elopmen , emphasizing he labo o ce and new ideas.
The expanded model can be e o mula ed as ollows:
Y =A( )L( )αK( )β
Y =A( )L( )αK( )β(Zi( ))δ(4)
LnY =LnA( )+αLnL( )+βLnK( )+δLnZi( )+e (5)
In Equa ion (4), Y( ) ep esen s economic g ow h. A( ) s ands o o al ac o p o-
duc i i y (TFP), which includes heal h and educa ion. K( ) is he amoun o physical
capi al, and L( ) is he labo o ce pa icipa ion, while Zi ep esen s o he con ol a iables;
α
,
β
,
δ
s and o he p oduc ion elas ici ies o he labo o ce, physical capi al, and knowl-
edge, espec i ely, whe e edeno es he e o e m. Equa ion (5) ep esen s i s log-linea
o m. We can pe o m sepa a e eg essions on he models using equa ions ha inco po a e
loga i hmic o ms.
4. Da a and Me hodology
4.1. Da a
We employed he annual ime se ies da a o Pakis an o he ime pe iod om 1980
o 2022. The esea ch a iables included economic g ow h (EG), labo o ce pa icipa ion
(LF), heal h expendi u es (Heal h), educa ion expendi u es (Edu), physical capi al (PC),
in la ion (INF), e ms o ade (TOT), and indus ializa ion (IND), as de ailed in Table 1. In
he Appendix A, Table A1 also p esen s he co e a ibles da a based on i e-yea a e ages.
Table 1. De ail o a iables.
Va iables Desc ip ions Signs Sou ce
Dependen Va iables
WDI, WB
Economic G ow h (EG) G ow h o GDP (annual %)
Co e Va iables
Labo Fo ce Pa icipa ion (LF)
Labo o ce pa icipa ion a e (% o o al popula ion ages abo e 15)
+
Heal h Expendi u es (Heal h) Go e nmen heal h expendi u es (% o GDP) +
Educa ion Expendi u es (Edu)
Go e nmen educa ion expendi u es (% o GDP) +
Con ol Va iables
Physical Capi al (PC) G oss ixed capi al o ma ion (% o GDP) +
In la ion (INF) In la ion, GDP de la o (annual %) −
Te m o T ade (TOT) T ade (% o GDP) +
Indus ializa ion (IND) Indus y alue added (annual % g ow h) +
Economies 2024,12, 113 8 o 21
4.2. Me hods and Model Speci ica ions
This s udy employed he au o eg essi e dis ibu ed lag (ARDL) echnique alongside
an e o co ec ion model (ECM) o in es iga e he ela ionship among a iables. The choice
o using he ARDL model is jus i ied by i s e ec i eness and app op ia eness in examining
dynamic associa ions among a iables, a ac ha is suppo ed by se e al no able s udies
such as Pesa an and Shin (1995), Pesa an e al. (2001), and Na ayan (2005). The ARDL
model is pa icula ly sui able o ou analysis as i allows us o assess bo h sho - un
dynamics and long- un ela ionships simul aneously. This is essen ial o unde s anding
he complex in e ac ions be ween labo o ce, heal h, educa ion, and economic g ow h o e
ime. The ARDL bound es ing echnique, as in oduced by Pesa an e al. (2001), enables
us o in es iga e he exis ence o long- un ela ionships while accoun ing o po en ial
sho - un dynamics.
This s a egy ou pe o ms p e ious me hodologies, such as Johansen (1988), o a
a ie y o easons. Unlike Johansen’s me hod, he ARDL amewo k does no equi e ha
all a iables be in eg a ed in he same o de ; hey can be I(1) o I(0). This adap abili y
imp o es i s ele ance o eal-wo ld da a, whe e a iables may exhibi di e en le els o
in eg a ion. Fu he mo e, he ARDL amewo k sol es he issue o se ial co ela ion, which
can dis o esul s in o he me hodologies. By including lagged alues o a iables, i
e ec i ely cap u es any au oco ela ion p esen in he da a, hus p oducing mo e eliable
es ima es (Pesa an e al. 1999). Mo eo e , he ARDL app oach allows o he simul aneous
examina ion o sho - and long- un e ec s, p o iding a comp ehensi e unde s anding o
he dynamics be ween he a iables unde in es iga ion (Nko o and Uko 2016). The ARDL
amewo k p oduces unbiased and e icien esul s, making i he p e e ed me hod o
empi ical analysis in a a ie y o ields (Menegaki 2019).
The ARDL is sui able o modeling a iables wi h di e en o de s o in eg a ion, such
as le els I(0) and i s di e ences I(1). This lexibili y allows o he inclusion o bo h
s a iona y and non-s a iona y a iables in he same model, which is common in economic
and social sciences esea ch. Na ayan (2005) sugges s ha he ARDL es ima ion echnique
is well known o yielding obus and consis en esul s e en wi h a small sample size,
ypically anging om 30 o 80. This adap abili y makes i especially use ul in empi ical
esea ch en i onmen s whe e da a a ailabili y may be limi ed. So, he ARDL amewo k
s ands ou as a use ul and eliable me hod o analyzing he long- un ela ionship be ween
a iables, p o iding ad an ages o e adi ional echniques while ensu ing accu a e and
e icien es ima ion e en in scena ios wi h limi ed da a o a ying le els o a iable in eg a ion.
Addi ionally, o ensu e he obus ness o ou empi ical models, we conduc ed a
obus ness analysis using he DOLS (Dynamic O dina y Leas Squa e), FMOLS (Fully
Modi ied O dina y Leas Squa e), and G ange causali y echniques. This s ep u he
s eng hened he eliabili y o ou indings by examining he ela ionships among he
a iables om di e en pe spec i es. Ou empi ical models a e as ollows:
Model 1
EG =ϕ0+ϕ1LF +ϕ2Heal h +ϕ3Edu +ϕ4Zi +µ (6)
Model 2
EG =ϕ0+ϕ1LF +ϕ2Heal h +ϕ3Edu +ϕ4LF ∗Heal h +ϕ5Zi +µ (7)
Mode 3
EG =ϕ0+ϕ1LF +ϕ2Heal h +ϕ3Edu +ϕ4LF ∗Edu +ϕ5Zi +µ (8)
whe e Equa ion (6) se es as an illus a ion o he model’s undamen al s uc u e in which
we examine he e ec o LF,Heal h, and Edu on EG. In Equa ion (7), we explo e he ole
o heal h expendi u es in he nexus be ween labo o ce and economic g ow h. Simi-
la ly, Equa ion (8) explo es he ole o educa ion expendi u es in he labo o ce-economic
g ow h nexus.
Economies 2024,12, 113 15 o 21
Table 7. Robus ness analysis.
Dep. Va :
Economic G ow h
DOLS FMOLS
Model 1 Model 2 Model 3 Model 1 Model 2 Model 3
LF
0.4999 ***
0.352 * 0.246 *** 0.405 ** 0.397 *** 0.323 *
(0.184) (0.195) (0.083) (0.179) (0.067) (0.172)
Heal h 0.213 ** 0.523 ** −0.221 * 0.404 ** 0.342 *** 1.039 ***
(0.089) (0.191) (0.123) (0.163) (0.072) (0.038)
Edu 1.035 *** 1.037 *** 1.048 *** 0.221 ** 1.419 *** 0.112 **
(0.044) (0.041) (0.052) (0.086) (0.232) (0.052)
LF*Heal h 2.143** 2.553 *
(1.007) (1.405)
LF*Edu 2.257 ** 3.766 **
(0.955) (1.802)
PC 0.716 *** 0.105 *** 0.036 * 0.425 * 0.398 *** 1.310 *
(0.138) (0.031) (0.021) (0.224) (0.069) (0.789)
INF −0.290 * −0.311 1.506 −0.103 * −0.332 * −0.097
(0.162) (1.159) (1.652) (0.055) (0.179) (0.086)
TOT 0.011 1.431 0.256 ** 0.071 0.061 ** 0.037*
(0.083) (1.023) (0.123) (0.061) (0.028) (0.020)
IND 0.351 *** 0.109 * −0.098 2.029 0.024 * 0.252 ***
(0.071) (0.049) (0.062) (1.647) (0.014) (0.085)
Cons an 7.892 *** 11.552 ** 6.373 ** 5.280 * 5.440 ** 6.538 ***
(1.739) (4.643) (2.928) (2.709) (2.481) (2.190)
No es: S anda d e o s in pa en heses; ***, **, and * show signi icance le els a 1%, 5%, and 10%, espec i ely.
In he con ex o Pakis an, hese esul s unde sco e he c i ical impo ance o in es ing
in human capi al de elopmen . By p io i izing ini ia i es ha p omo e labo o ce pa icipa-
ion, imp o e heal h ou comes, and enhance educa ional oppo uni ies, policymake s can
lay he g oundwo k o long- e m economic p ospe i y. This empi ical e idence se es as a
s ong endo semen o he no ion ha os e ing a skilled, heal hy, and engaged wo k o ce
is key o unlocking Pakis an’s economic po en ial o e he long un
5.5. Diagnos ic Tes s
The diagnos ic es s o long- un es ima es, encompassing he se ial co ela ion LM,
Du bin–Wa son, Whi e’s es , B eusch–Pagan–God ey es , no mali y es , and Ramsey
RESET es we e used o e alua e he obus ness and eliabili y o he models. The ob ained
esul s in Table 8indica e no signi ican issues ac oss all h ee models, as e idenced by he
es s a s and co esponding p- alues.
Table 8. Diagnos ic es s o long- un es ima es.
Tes s Model 1 Model 2 Model 3
Tes -S a P obabili y Tes -S a P obabili y Tes -S a P obabili y
Se ial Co ela ion LM 1.311 0.223 0.658 0.796 0.721 0.397
Du bin–Wa son 2.053 - 2.069 - 1.913 -
Whi e’s es 1.728 0.134 0.735 0.763 1.078 0.438
B eusch–Pagan–God ey 1.723 0.152 0.721 0.651 0.071 0.785
No mali y Tes 1.213 0.533 0.723 0.069 0.251 0.615
Ramsey RESET Tes 0.012 0.915 0.098 0.756 0.230 0.635
The esul s o he se ial co ela ion LM es and Du bin–Wa son es indica e ha
he e is no issue o au oco ela ion in all h ee models. Simila ly, he esul s o Whi e’s es
and he B eusch–Pagan–God ey es e eal ha he e is no e idence o he e oskedas ici y
in he models. Fu he mo e, he no mali y es indica es ha he esiduals a e no mally
dis ibu ed. Finally, he Ramsey RESET es esul s show ha he e is no issue o unc ional
o m misspeci ica ion and omi ed a iables bias ac oss all h ee models.
Economies 2024,12, 113 16 o 21
5.6. S abili y Es ima es
The cumula i e sum (CUSUM) and he squa e o he cumula i e sum (CUSUMSQ)
es s se e as c i ical ools o assessing he sho - e m s abili y o he model. In essence,
he CUSUM es analyzes he eg ession coe icien s’ beha io , while he CUSUMSQ es
e alua es he cons ancy o hese coe icien s (B own e al. 1975).
The s a is ical ou comes o hese es s con i m ha all h ee models main ain s abili y
wi hin a 5% con idence in e al. This s abili y is isually shown in Figu es 1–3, showcasing
he eliabili y and obus ness o he models o e he sho un. These esul s no only
alida e he models’ in eg i y bu also p o ide a solid ounda ion o hei applicabili y and
p edic i e powe wi hin he speci ied con ex .
Economies 2024, 12, x FOR PEER REVIEW 17 o 22
-15
-10
-5
0
5
10
15
00 02 04 06 08 10 12 14 16 18 20 22
CUSUM 5% Signi icance
-0.4
-0.2
0.0
0.2
0.4
0.6
0.8
1.0
1.2
1.4
00 02 04 06 08 10 12 14 16 18 20 22
CUSUM o Squa es 5% Signi icance
Figu e 1. CUSUM and CUSUMSQ o Model 1.
-15
-10
-5
0
5
10
15
00 02 04 06 08 10 12 14 16 18 20 22
CUSUM 5% Signi icance
-0.4
-0.2
0.0
0.2
0.4
0.6
0.8
1.0
1.2
1.4
00 02 04 06 08 10 12 14 16 18 20 22
CUSUM o Squa es 5% Signi icance
Figu e 2. CUSUM and CUSUMSQ o Model 2.
-15
-10
-5
0
5
10
15
00 02 04 06 08 10 12 14 16 18 20 22
CUSUM 5% Signi icance
-0.4
-0.2
0.0
0.2
0.4
0.6
0.8
1.0
1.2
1.4
00 02 04 06 08 10 12 14 16 18 20 22
CUSUM o Squa es 5% Signi icance
Figu e 3. CUSUM and CUSUMSQ o Model 3.
5.7. G ange Causali y Analysis
In examining he s eng h o he causal ela ionships among economic a iables, he
G ange causali y echnique se es as a i al ool. I helps us unde s and no only he di-
ec ion bu also he magni ude o in luence be ween he dependen and independen a -
iables (Hiems a and Jones 1994). To ensu e compliance wi h he p e equisi es o he
G ange causali y es , which equi es a iables o exhibi s a iona i y (Lopez and Webe
2017), we employed a ans o ma ion echnique known as diffe encing on he non-s a ion-
a y a iables. This in ol ed aking he i s diffe ences o non-s a iona y a iables and
compu ing he change in each a iable’s alue om one ime pe iod o he nex . This s ep
was c ucial as i helped achie e da a s a iona i y, a equi emen o accu a e and eliable
Figu e 1. CUSUM and CUSUMSQ o Model 1.
Economies 2024, 12, x FOR PEER REVIEW 17 o 22
-15
-10
-5
0
5
10
15
00 02 04 06 08 10 12 14 16 18 20 22
CUSUM 5% Signi icance
-0.4
-0.2
0.0
0.2
0.4
0.6
0.8
1.0
1.2
1.4
00 02 04 06 08 10 12 14 16 18 20 22
CUSUM o Squa es 5% Signi icance
Figu e 1. CUSUM and CUSUMSQ o Model 1.
-15
-10
-5
0
5
10
15
00 02 04 06 08 10 12 14 16 18 20 22
CUSUM 5% Signi icance
-0.4
-0.2
0.0
0.2
0.4
0.6
0.8
1.0
1.2
1.4
00 02 04 06 08 10 12 14 16 18 20 22
CUSUM o Squa es 5% Signi icance
Figu e 2. CUSUM and CUSUMSQ o Model 2.
-15
-10
-5
0
5
10
15
00 02 04 06 08 10 12 14 16 18 20 22
CUSUM 5% Signi icance
-0.4
-0.2
0.0
0.2
0.4
0.6
0.8
1.0
1.2
1.4
00 02 04 06 08 10 12 14 16 18 20 22
CUSUM o Squa es 5% Signi icance
Figu e 3. CUSUM and CUSUMSQ o Model 3.
5.7. G ange Causali y Analysis
In examining he s eng h o he causal ela ionships among economic a iables, he
G ange causali y echnique se es as a i al ool. I helps us unde s and no only he di-
ec ion bu also he magni ude o in luence be ween he dependen and independen a -
iables (Hiems a and Jones 1994). To ensu e compliance wi h he p e equisi es o he
G ange causali y es , which equi es a iables o exhibi s a iona i y (Lopez and Webe
2017), we employed a ans o ma ion echnique known as diffe encing on he non-s a ion-
a y a iables. This in ol ed aking he i s diffe ences o non-s a iona y a iables and
compu ing he change in each a iable’s alue om one ime pe iod o he nex . This s ep
was c ucial as i helped achie e da a s a iona i y, a equi emen o accu a e and eliable
Figu e 2. CUSUM and CUSUMSQ o Model 2.
Economies 2024, 12, x FOR PEER REVIEW 17 o 22
-15
-10
-5
0
5
10
15
00 02 04 06 08 10 12 14 16 18 20 22
CUSUM 5% Signi icance
-0.4
-0.2
0.0
0.2
0.4
0.6
0.8
1.0
1.2
1.4
00 02 04 06 08 10 12 14 16 18 20 22
CUSUM o Squa es 5% Signi icance
Figu e 1. CUSUM and CUSUMSQ o Model 1.
-15
-10
-5
0
5
10
15
00 02 04 06 08 10 12 14 16 18 20 22
CUSUM 5% Signi icance
-0.4
-0.2
0.0
0.2
0.4
0.6
0.8
1.0
1.2
1.4
00 02 04 06 08 10 12 14 16 18 20 22
CUSUM o Squa es 5% Signi icance
Figu e 2. CUSUM and CUSUMSQ o Model 2.
-15
-10
-5
0
5
10
15
00 02 04 06 08 10 12 14 16 18 20 22
CUSUM 5% Signi icance
-0.4
-0.2
0.0
0.2
0.4
0.6
0.8
1.0
1.2
1.4
00 02 04 06 08 10 12 14 16 18 20 22
CUSUM o Squa es 5% Signi icance
Figu e 3. CUSUM and CUSUMSQ o Model 3.
5.7. G ange Causali y Analysis
In examining he s eng h o he causal ela ionships among economic a iables, he
G ange causali y echnique se es as a i al ool. I helps us unde s and no only he di-
ec ion bu also he magni ude o in luence be ween he dependen and independen a -
iables (Hiems a and Jones 1994). To ensu e compliance wi h he p e equisi es o he
G ange causali y es , which equi es a iables o exhibi s a iona i y (Lopez and Webe
2017), we employed a ans o ma ion echnique known as diffe encing on he non-s a ion-
a y a iables. This in ol ed aking he i s diffe ences o non-s a iona y a iables and
compu ing he change in each a iable’s alue om one ime pe iod o he nex . This s ep
was c ucial as i helped achie e da a s a iona i y, a equi emen o accu a e and eliable
Figu e 3. CUSUM and CUSUMSQ o Model 3.
5.7. G ange Causali y Analysis
In examining he s eng h o he causal ela ionships among economic a iables, he
G ange causali y echnique se es as a i al ool. I helps us unde s and no only he
di ec ion bu also he magni ude o in luence be ween he dependen and independen
Economies 2024,12, 113 17 o 21
a iables (Hiems a and Jones 1994). To ensu e compliance wi h he p e equisi es o
he G ange causali y es , which equi es a iables o exhibi s a iona i y (Lopez and
Webe 2017), we employed a ans o ma ion echnique known as di e encing on he non-
s a iona y a iables. This in ol ed aking he i s di e ences o non-s a iona y a iables
and compu ing he change in each a iable’s alue om one ime pe iod o he nex . This
s ep was c ucial as i helped achie e da a s a iona i y, a equi emen o accu a e and
eliable esul s in ime se ies analysis. Once he a iables we e ans o med in o hei i s
di e ences, we p oceeded o conduc he G ange causali y es o explo e bidi ec ional
causali y be ween he co e a iables.
The indings, as p esen ed in Table 9, illumina e he dynamics o hese ela ionships.
Fi s ly, he analysis indica es ha labo o ce pa icipa ion in he G ange es causes
economic g ow h, demons a ing a s a is ically signi ican impac a a le el o 1%. This
implies ha changes in labo o ce pa icipa ion p ecede and con ibu e o a ia ions in
economic g ow h, showcasing he in e connec edness o hese a iables.
Table 9. G ange causali y esul s.
Causal Di ec ion Tes S a is ics p-Value
LF →EG 10.909 0.004 ***
HEALTH →EG 5.861 0.053 **
EDU→EG 6.378 0.051 **
EG →LF 0.026 0.987
HEALTH →LF 3.229 0.100 *
EDU →LF 8.089 0.018 **
EG →HEALTH 6.125 0.056 *
LF →HEALTH 3.695 0.158
EDU →HEALTH 7.236 0.015 **
EG →EDU 3.254 0.165
LF →EDU 5.156 0.524
HEALTH →EDU 7.594 0.069 *
No e: ***, **, and * show signi icance le els a 1%, 5%, and 10%, espec i ely.
Addi ionally, he esul s un eil ha heal h and educa ion expendi u es also play
signi ican oles in d i ing economic g ow h, albei a di e en signi icance le els o 5%
and 10%, espec i ely. This implies ha in es men s in he heal h and educa ion sec o s can
ha e angible impac s on o e all economic pe o mance, wi h highe expendi u es in hese
a eas leading o no able imp o emen s in economic g ow h o e ime. Mo eo e , del ing
in o he in e play be ween hese a iables, he analysis e eals ha heal h and educa ion
expendi u es in he G ange es cause labo o ce pa icipa ion. This sugges s a eedback
loop whe e in es men s in heal h and educa ion no only con ibu e o economic g ow h
bu also in luence he size and composi ion o he labo o ce, highligh ing he mul i ace ed
na u e o hese ela ionships. Fu he mo e, he bidi ec ional causal ela ionship obse ed
be ween heal h expendi u es and educa ion expendi u es unde sco es he in e connec ed
na u e o in es men s in human capi al de elopmen . As heal h imp o emen s can lead o
enhanced educa ional ou comes, and ice e sa, policymake s can le e age hese insigh s
o o mula e comp ehensi e s a egies ha p omo e bo h heal h and educa ion, he eby
os e ing sus ainable economic de elopmen .
6. Conclusions and Policy Implica ions
Pakis an, as a de eloping na ion wi h a high popula ion g ow h a e, necessi a es sig-
ni ican human capi al o ma ion o suppo economic g ow h due o i s labo abundance.
The e o e, in es ing in human capi al de elopmen is c ucial o ensu e a well-in o med,
skilled, and heal hy wo k o ce, essen ial o e ec i ely u ilizing he na ion’s esou ces o os-
e g ow h and de elopmen . Hence, we explo ed he e ec o he labo o ce on economic
g ow h, ocusing on i s dependency on he le els o heal h and educa ion expendi u es.
This s udy employed ARDL, ECM, and G ange causali y echniques o empi ical analysis.
Economies 2024,12, 113 18 o 21
The s udy’s es ima ion backg ound is obus , ha ing p ope ly applied uni oo es s such
as KPSS, DF-GLS, and Ng-Pe on. These es s p oduced mixed esul s, demons a ing ha
some a iables a e s a iona y a le el and o he s a i s di e ence, p o iding su icien
e idence o he applica ion o he ARDL me hod. The es ima ion p ocess also employed
he ECM echnique, enhancing he accu acy and eliabili y o he model. These echniques
iden i ied bo h long- un and sho - un ela ionships be ween labo o ce pa icipa ion,
heal h expendi u es, educa ion expendi u es, and economic g ow h.
The sho - un and long- un esul s o ARDL analysis highligh a signi ican and pos-
i i e ela ionship be ween labo o ce pa icipa ion and economic g ow h. This inding
sugges s ha as mo e indi iduals en e he labo o ce, ei he h ough inc eased employ-
men a es o highe pa icipa ion a es, he o e all economic ou pu o he coun y ends o
expand. Mo eo e , he es ima ion esul s e ealed an in e es ing dynamic in ol ing heal h-
ca e and educa ion. Speci ically, he es ima ions indica e ha imp o emen s in heal hca e
acili ies and educa ional oppo uni ies con ibu e o s eng hening he posi i e impac o
labo o ce pa icipa ion on economic g ow h. These indings unde sco e he complemen-
a y ela ionship o heal h, educa ion, and labo o ce pa icipa ion in os e ing economic
g ow h. When indi iduals ha e access o be e heal hca e se ices, hey a e mo e likely
o emain heal hy and p oduc i e in he wo k o ce, he eby enhancing hei con ibu ion
o economic ac i i ies. Simila ly, a well-educa ed wo k o ce is be e equipped o ake on
skilled jobs and inno a e, leading o inc eased p oduc i i y and economic g ow h.
Fu he mo e, indings indica ed ha in he sho un, he ole o heal h expendi u e
appea s o be mo e powe ul compa ed o educa ion expendi u e, indica ing ha immedia e
imp o emen s in heal hca e acili ies can lead o signi ican economic bene i s h ough a
heal hie and mo e p oduc i e wo k o ce. Howe e , in he long un, he ole o educa ion
expendi u e eme ges as mo e in luen ial han heal h expendi u e. This sugges s ha long-
e m in es men s in educa ion, such as imp o ing educa ional oppo uni ies and skill
de elopmen , ha e a mo e subs an ial impac on economic g ow h by os e ing a highly
skilled and inno a i e wo k o ce.
Mo eo e , he G ange causali y analysis con i med he in luen ial ole o labo o ce
pa icipa ion, heal h, and educa ion expendi u es in os e ing economic g ow h. This means
ha no only do hese ac o s indi idually con ibu e o economic ad ancemen , bu hey
also in e ac and ein o ce each o he ’s impac , leading o a mo e obus and sus ainable
g ow h ajec o y. These indings unde sco e he impo ance o comp ehensi e policies
ha in eg a e labo ma ke s a egies wi h in es men s in human capi al de elopmen o
achie e long- e m economic p ospe i y.
These indings ha e impo an policy implica ions o Pakis an and o he labo -su plus
coun ies. Policymake s should p io i ize sho - e m measu es o enhance heal hca e
access and quali y o ealize immedia e economic gains h ough imp o ed wo k o ce
heal h. Simul aneously, long- e m s a egies ocusing on educa ion and skill de elopmen
a e essen ial o sus ainably boos economic g ow h by c ea ing a highly educa ed and
skilled labo o ce capable o d i ing inno a ion and p oduc i i y. In eg a ed policies ha
add ess bo h heal h and educa ion needs, alongside ini ia i es o p omo e highe labo o ce
pa icipa ion h ough skill de elopmen p og ams, job c ea ion ini ia i es, and incen i es
o wo k o ce engagemen , will be key o unlocking he ull po en ial o human capi al
and achie ing las ing economic p ospe i y. Recognizing he complemen a y ela ionship
be ween heal h, educa ion, and labo o ce pa icipa ion, policymake s should s i e o
os e syne gy among hese sec o s by ensu ing he coo dina ion and in eg a ion o policies
ac oss hese sec o s, coupled wi h con inuous moni o ing and e alua ion, will be c ucial o
maximizing he impac o in es men s in human capi al.
Au ho Con ibu ions: Concep ualiza ion, W.A. and M.U.; me hodology, B.H.; so wa e, V.M.A.;
alida ion, C.F. and M.L.Z.; o mal analysis, W.A. and M.U.; in es iga ion, B.H. and V.M.A.; da a
cu a ion, C.F.; w i ing—o iginal d a p epa a ion, W.A., M.U. and B.H.; w i ing— e iew and edi ing,
M.U., W.A., B.H., C.F., M.L.Z. and V.M.A. All au ho s ha e ead and ag eed o he published e sion
o he manusc ip .
Economies 2024,12, 113 19 o 21
Funding: This esea ch ecei ed no ex e nal unding.
Ins i u ional Re iew Boa d S a emen : No applicable.
In o med Consen S a emen : No applicable.
Da a A ailabili y S a emen : The da a ha suppo he indings o his s udy a e openly a ailable on
he websi e o he Wo ld Bank.
Con lic s o In e es : The au ho s decla e ha hey ha e no con lic s o in e es ega ding he
publica ion o his pape .
Appendix A
Table A1. Va iable’s da a based on i e-yea a e ages.
Va iables EG LF Heal h Edu
1980–1984 7.30 50.22 1.08 0.05
1985–1989 6.43 45.80 0.88 0.18
1990–1994 4.54 49.41 0.84 0.06
1994–1999 3.41 49.56 0.83 0.09
2000–2004 4.73 50.52 0.82 0.19
2005–2009 4.36 49.45 0.50 0.21
2010–2014 3.39 50.57 0.56 0.13
2015–2019 4.67 50.70 0.83 0.18
2020–2022 3.80 52.35 1.00 2.38
No e: Da a a e aken om WDI, Wo ld Bank.
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