The role of comparative advantage in enhancing trade in value-added using a dynamic gmm model

Wu i, Josephine
A icle
The ole o compa a i e ad an age in enhancing ade in
alue-added using a dynamic gmm model
Economies
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MDPI – Mul idisciplina y Digi al Publishing Ins i u e, Basel
Sugges ed Ci a ion: Wu i, Josephine (2024) : The ole o compa a i e ad an age in enhancing ade in
alue-added using a dynamic gmm model, Economies, ISSN 2227-7099, MDPI, Basel, Vol. 12, Iss. 7,
pp. 1-21,
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Ci a ion: Wu i, Josephine. 2024. The
Role o Compa a i e Ad an age in
Enhancing T ade in Value-Added
Using a Dynamic GMM Model.
Economies 12: 187. h ps://doi.o g/
10.3390/economies12070187
Academic Edi o : B uce Mo ley
Recei ed: 9 June 2024
Re ised: 14 July 2024
Accep ed: 16 July 2024
Published: 18 July 2024
Copy igh : © 2024 by he au ho .
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economies
A icle
The Role o Compa a i e Ad an age in Enhancing T ade in
Value-Added Using a Dynamic GMM Model
Josephine Wu i
Depa men o Economics, Facul y o Economics, Sana a Dha ma Uni e si y, Yogyaka a 55281, Indonesia;
[email p o ec ed]
Abs ac : Cu en ly, in e na ional ade has e ol ed in o in e na ional p oduc ion agmen a ion
cap u ed in GVCs. Coun ies mus enhance in e media e expo s in compa a i e ad an age sec o s
o inc ease hei ade in alue-added (TVA) in global p oduc ion chains. Howe e , adi ional
measu emen s o e ealed compa a i e ad an age (RCA) based on g oss expo s need o be upda ed
due o o e alua ion, double coun ing, and implici dis o ions in in e na ional ade. This s udy
uses a new compa a i e ad an age measu e, “new e ealed symme ic compa a i e ad an age”
(NRSCA). Using a dynamic Gene al Me hod o Momen (GMM) app oach, we in es iga e he ole
o compa a i e ad an age in d i ing TVA ega ding backwa d and o wa d linkages and examine
he impac o he COVID-19 pandemic. We use da a om he cu en Asian De elopmen Bank
mul i- egional inpu –ou pu da abase o 2010–2020. Ou indings e eal ha compa a i e ad an age
signi ican ly impac ed in e na ional TVA, along wi h he suppo o quali y ins i u ional se ices in
each coun y. Implemen ing a new compa a i e ad an age measu e, NRSCA, p o ided accu a e
es ima ion esul s o o e come he o e alua ion p oblem. Mo eo e , he COVID-19 pandemic
dis up ed alue-added ade.
Keywo ds: compa a i e ad an age; ade in alue added; dynamic GMM model; mul i- egional
inpu ou pu ; pandemic
1. In oduc ion
In he new in e na ional ade heo y, in e na ional ade has de eloped in o ade
in alue-added (TVA) and is included in global alue chains (GVCs). In e na ional ag-
men a ion in he p oduc ion o goods has enabled each coun y o specialize in p oducing
high- alue-added goods (Amendolagine e al. 2019;Fan e al. 2023;Hummels e al. 2001;
Inoma a 2013;Johnson and Nogue a 2017). Fu he mo e, he oppo uni ies o GVC
pa icipa ion ha e a ac ed o eign in es men and allowed o p o i -sha ing and eco-
nomic, echnological, and indus ial upg ading (Ge e i e al. 2005;González and Kowalski
2017;P e e e al. 2018;Zhang 2024), hus enabling de eloping coun ies o ca ch up wi h
de eloped na ions.
The pa icipa ion o coun ies in GVCs is measu ed by decomposing g oss expo s
o ace domes ic alue added (DVA) and o eign con ibu ions (Z. Wang e al. 2018).
Backwa d- and o wa d-linked app oaches a e used o de e mine he le el o coun ies’
pa icipa ion in TVA, which aces he alue added in each p oduc ion phase (Asian
De elopmen Bank 2019;Koopman e al. 2014;P e e e al. 2018;Z. Wang e al. 2018;Wu i
e al. 2023).
In ol emen in GVC acili a es he eme gence o new global compe i o s and has
challenged he ade dominance o de eloped coun ies. Consequen ly, conce ns o e
compe i i eness ha e been esea ched in ecen yea s.
Each coun y needs o enhance i s compa a i e ad an age o inc ease pa icipa ion
in GVCs. Unde s anding compa a i e ad an ages enables coun ies o op imize esou ce
alloca ion and ocus on indus ies wi h signi ican po en ial o enhancing alue-added.
Economies 2024,12, 187. h ps://doi.o g/10.3390/economies12070187 h ps://www.mdpi.com/jou nal/economies
Economies 2024,12, 187 2 o 21
This p omo es sus ainable economic g ow h, ein o ces economic in eg a ion, and enhances
global compe i i eness in in e na ional ade (Elsalih e al. 2021;Lau sen 2015). Balassa
(1965) in oduced e ealed compa a i e ad an age (RCA), which anked p oduc -speci ic
specializa ion in c oss-coun y ade. A coun y has a compa a i e ad an age in a speci ic
sec o i he sha e o ha sec o in i s o al expo s exceeds i s sha e o o al wo ld expo s
(I o e al. 2017). Mos coun ies con inue o ely on adi ional measu es o compa a i e
ad an age, which emains a c i ical issue o policymake s and academics.
Howe e , he adi ional RCA (TRCA) measu e based on g oss expo s does no
accu a ely e lec coun ies’ compa a i e ad an age, as he calcula ion includes o eign
esou ce componen s (Johnson and Nogue a 2017). Fu he mo e, ade measu emen s
can become o e alued and de elop implici dis o ions (Asian De elopmen Bank 2019;
A huko ala and Yamashi a 2006;Inoma a 2013;Koopman e al. 2014).
To add ess he gap in cu en esea ch, his s udy de eloped a new compa a i e ad-
an age measu e, NRSCA. The symme ic calcula ion was based on DVA and excluded
o eign alue-added (FVA) and pu e double-coun ed e ms in g oss expo s o ob ain an
accu a e measu e o a coun y’s compa a i e ad an age. The NRSCA encou ages TVA
using high-quali y ins i u ions as con ol a iables such as go e nmen e ec i eness and
con ol o co up ion. The e o e, coun ies wi h high-quali y ins i u ions can ensu e e i-
ciency and ai con ac s, educe co up ion, educe en i onmen al deg ada ion, p omo e
policy coo dina ion and ade, and ul ima ely s imula e economic g ow h (Fan e al. 2023;
Ge e i e al. 2005;Mouanda and Gong 2019;Q. Wang e al. 2024;Ze gawu e al. 2020).
The pandemic dis up ed ade in ensi y among coun ies due o bo de closu es and
qua an ine- ela ed es ic ions (Baldwin and Mau o 2020;Vidya and P abheesh 2020). Glob-
ally imposed es ic ions con inue o cause supply chain losses. We u he es ima ed he
ole o he compa a i e ad an age in d i ing alue-added ade by conside ing ins i u-
ional, ime-in a ian a iables ha can di e by coun y because o he e ogenei y among
hem (Faheem U e al. 2024;Ze gawu e al. 2020). Addi ionally, we use a new compa a i e
ad an age measu e o o e come p oblems wi h adi ional measu es. The model was
u ilized o in es iga e he impac o he COVID-19 pandemic on TVA. We employed a
dynamic GMM app oach o add ess his issue and o o e come po en ial endogenei y
p oblems. The dynamic GMM echnique o e s he ad an age o e alua ing dynamic
adjus men obse a ions, which a e aluable o measu ing he dynamics o adjus men
be ween coun ies conce ning TVA. To his end, his s udy used da a om he cu en Asian
De elopmen Bank mul i- egional inpu –ou pu (ADB MRIO) o ace he in e connec ed
alue added among coun ies om 2010 o 2020, which was a challenge o ob ain. This
aspec en iches he g owing body o esea ch on he ole o compa a i e ad an age in
in e na ional p oduc ion agmen a ion.
The emainde o his a icle is s uc u ed as ollows: a li e a u e e iew is in oduced
in Sec ion 2. Da a and Me hodology is explained in de ail in Sec ion 3, while he empi ical
esul s and analysis a e p esen ed in Sec ion 4. The inal sec ion concludes wi h signi ican
indings and policy ecommenda ions.
2. Li e a u e Re iew
The analysis o TVA has been widely discussed since he de elopmen o he new
in e na ional ade heo y, which aces he dis ibu ion o alue added in in e na ional
ade (A huko ala and Yamashi a 2006;Bo in and Mancini 2019;Johnson and Nogue a
2012;Koopman e al. 2014;Z. Wang e al. 2018). Cu en ly, coun ies do no need o p oceed
wi h he accep ed p oduc ion s ages. Ins ead, hey can specialize in a speci ic p oduc ion
s age (Amendolagine e al. 2019;Inoma a 2013;P e e e al. 2018). GVCs occu when he
a ious s ages o he p oduc ion chain o goods and se ices, om he p oduc design
o he dis ibu ion o goods o inal consume s, a e p oduced and assembled h ough
he ne wo king o a ious coun ies, ac oss in e na ional bo de s (Hummels e al. 2001;
Inoma a 2013;P e e e al. 2018).
Economies 2024,12, 187 3 o 21
The pa icipa ion o coun ies in alue-added ade is measu ed h ough he decom-
posi ion o expo s. This app oach iden i ies domes ic and o eign alue-added sha es
embedded in in e media e expo s (Asian De elopmen Bank 2019;Ceglowski 2017;John-
son and Nogue a 2012;Z. Wang e al. 2018;Wu i e al. 2022). Howe e , ew s udies ha e
simul aneously pe o med bo h analyses. Ou s udy employs bo h app oaches o p o ide
a mo e comp ehensi e analysis.
Fu he mo e, a coun y’s in e na ional ade pe o mance depends on i s dynamic
compa a i e ad an age (Bu lina and Di Ma ia 2020). The e o e, na ions wo ldwide can
inc ease hei pa icipa ion in alue-added ade by specializing in p oduc s wi h a compa -
a i e ad an age (I o e al. 2017). T adi ional me hods o measu ing compa a i e ad an age
based on g oss expo s a e ou da ed due o an inabili y o ack alue added and mi iga e
he o e alua ion p oblem (A huko ala and Yamashi a 2006;Koopman e al. 2014;Timme
e al. 2013). A mo e p ecise me hod o calcula ing he alue-added con ibu ion and
dis ibu ion o in e media e expo goods is c i ical, as goods may c oss na ional bo de s
se e al imes, hus leading o se e al imposi ions o a i s and anspo a ion cos s (Asian
De elopmen Bank 2019;A huko ala and Yamashi a 2006;Koopman e al. 2014).
The new e ealed compa a i e ad an age measu e p ecisely e lec s he compa a i e
ad an age o domes ic esou ces by excluding o eign esou ces o add ess he o e alua-
ion issue (Asian De elopmen Bank 2019;A huko ala and Yamashi a 2006;Koopman e al.
2014;Le omain and O i ice 2014;Ma ca o e al. 2019;Shuai e al. 2022;Song e al. 2021).
Fu he mo e, gi en he e e -inc easing ade in in e media es, his me hodology suppo s
he a gumen ha compa a i e ad an age measu es should ocus mo e on o wa d-linked
alue-added indica o s o measu e RCA. I is because he use o alue-added RCA p o ides
mo e in o ma ion ega ding he wo king o a eal economy han he g oss alue o RCA
(B akman and Van Ma ewijk 2017;Bu lina and Di Ma ia 2020;Ceglowski 2017;Liu e al.
2020;Song e al. 2021;Z. Wang e al. 2018). We inco po a ed his measu e o alue-added
RCA as a symme ical measu e, which will hence o h be e e ed o as he “new e ealed
symme ic compa a i e ad an age” (NRSCA). I is essen ial o adjus he symme ical
measu e o be compa ed on bo h sides o uni y.
COVID-19 has placed an eno mous s ain on he global public heal h sys em and
economy and weakened he ade sec o s o mos coun ies (Hayakawa and Mukunoki
2021;Qin e al. 2020). ASEAN coun ies expe ienced a 0.83% dec ease in o wa d GVC
pa icipa ion due o he social es ic ion policies implemen ed o mi iga e he sp ead o
he i us. China expe ienced a 13.54% dec ease in o wa d pa icipa ion. As China is a
global manu ac u ing hub, his se e ely dis up ed supply chains ac oss he wo ld (Baldwin
and Mau o 2020;Chen and Chen 2022). Simila ly, he a e age GVC pa icipa ion in he
Eu opean Union (EU) and No h Ame ican coun ies also dec eased (Wu i e al. 2022).
La ge in e na ional ade olumes a e associa ed wi h be e ins i u ions, commonly
ound in de eloped coun ies. Acco ding o Le chenko (2007), dispa i ies in ins i u ional
quali y could be a sou ce o compa a i e ad an age and a c ucial de e minan o ade
pa e ns. A coun y wi h high ins i u ional quali y can p omo e en i onmen al quali y
in ade while a oiding nega i e consequences such as pollu ion and ca bon emissions
(Pa a e al. 2023;Q. Wang e al. 2024). The e o e, his s udy de ines wo con ol a iables
based on ins i u ional quali y go e nmen e ec i eness and con ol o co up ion. A be e
ins i u ion con ibu es o less co up ion and an imp o ed egula o y en i onmen .
3. Me hodology
3.1. Da a Desc ip ion
This s udy es ima ed he impo ance o compa a i e ad an age in d i ing TVA using
ADB’s annual MRIO da a, co e ing 35 indus ies in 62 coun ies and 132 coun ies classi ied
as “ es o wo ld” (ROW) o 2010–2020 (Asian De elopmen Bank 2019). Fu he mo e,
ins i u ional a iables we e conside ed con ol a iables (Kau mann e al. 2010). This
s udy ocused on 41 coun ies ha we e membe s o se e al g oups: ASEAN, Eas Asia,
he EU, and No h Ame ica (NA) (Appendix A, Table A1). This s udy will in es iga e
Economies 2024,12, 187 4 o 21
ASEAN in e - and in a egional alue-added ade and p o ide in-dep h insigh s in o
he dynamics o compa a i e ad an ages and alue-added ade on a global le el. The
da a we e ob ained om he ADB MRIO and Wo ld Bank Wo ld Go e nance Indica o s.
Mul i egional Inpu -Ou pu (MRIO) da a we e collec ed by he Asian De elopmen Bank
(ADB) by in eg a ing a ious na ional and in e na ional da a sou ces. ADB collec s da a
om he na ional inpu –ou pu (I-O) ables p o ided by each membe coun y. These
da a a e usually collec ed by na ional s a is ical agencies o economic minis ies in hose
coun ies. ADB in ol es in e na ional collabo a ion, he in eg a ion o a ious da a sou ces,
and echnologies o managing and analyzing MRIO da a. The Asian De elopmen Bank
Mul i-Regional Inpu –Ou pu Da abase (ADB MRIO) co e s 2010–2020. The yea 2010
was chosen as a s a ing poin since wo ldwide ade ci cums ances had begun o eco e
ollowing he inancial c isis. The de ails a e p esen ed in Table 1.
Table 1. Desc ip ion o Va iables and Sou ces o Da a.
Va iables Desc ip ion Measu emen Expec a ion Sou ce
BPR Backwa d GVC
pa icipa ion a io
Sha e o o eign alue added
(FVA) o o al wo ld expo s
( a io)
-
Mul i-Regional
Inpu –Ou pu (MRIO),
compu ed by au ho s,
2010–2020
FPR Fo wa d GVC
pa icipa ion a io
Sha e o domes ic alue
added (DVA) o o al wo ld
expo s ( a io)
-MRIO, compu ed by
au ho s, 2010–2020
TVA T ade in alue added FPR + BPR - MRIO, compu ed by
au ho s, 2010–2020
NRSCA
New e ealed
symme ic compa a i e
ad an age
Sha e o an economic sec o ’s
o wa d-linked measu e o
DVA in expo s
Posi i e MRIO, compu ed by
au ho s, 2010–2020
COVID Co ona i us disease 19
pandemic
Dummy COVID-19
pandemic (1 = 2019–2020,
0 = o he wise)
Nega i e -
GOV Go e nmen
e ec i eness
Index lies be ween
−2.5 and 2.5 Posi i e
Wo ld Go e nance
Indica o s (WGI),
2010–2020
CC Con ol o co up ion Index lies be ween
−2.5 and 2.5 Posi i e WGI, 2010–2020
We ex ended he basic inpu –ou pu amewo k o a single economy by using he
MRIO model o ace he ela ionships be ween coun ies and sec o s (Asian De elopmen
Bank 2019;Leon ie 1936). In addi ion, he inpu –ou pu model is use ul o unde s anding
he impac o a ious go e nmen policies on speci ic indus ies and he economy as a
whole (Kee and Tang 2016).
3.2. Measu ing T ade in Value Added
Each coun y’s pa icipa ion in TVA was measu ed by decomposi ion g oss expo s
(Johnson and Nogue a 2012;Leon ie 1936;Z. Wang e al. 2018). The ela ionship be ween
p oduc ion and inal demand is as ollows:
X=(I−A)−1Y(1)
whe e Xand Ya e he ec o s o g oss ou pu and inal demand, espec i ely, p o ided
by he economy sec o and Iis an N
×
N iden i y ma ix. Ais he N
×
N ma ix o he
inpu coe icien . We disagg ega ed each coun y’s g oss ou pu by ea anging he inal
demands o bo h coun ies in o a ma ix o ma based on sou ces and des ina ions.

Economies 2024,12, 187 5 o 21
This decomposi ion is dis inguished by he o wa d and backwa d linkages. The
o wa d-linked pe spec i e, o o wa d GVC pa icipa ion a io (FPR), measu es he sha e
o domes ic alue added (DVA) embedded in in e media e expo s compa ed o o al wo ld
expo s. Con e sely, he backwa d-linked pe spec i e o backwa d GVC pa icipa ion a io
(BPR) e eals he sha e o FVA used o p oduce a coun y’s expo goods compa ed o o al
wo ld expo s (Asian De elopmen Bank 2015;Koopman e al. 2014;Z. Wang e al. 2018;
Wu i e al. 2022). Fu he mo e, TVA was he sum o he BPR and FPR (Amendolagine e al.
2019;Ayadi e al. 2021;P e e e al. 2018).
3.3. Measu ing Compa a i e Ad an age
To enhance TVA, coun ies wo ldwide should inc ease hei in e media e expo s
in sec o s whe e hey ha e a compa a i e ad an age. Z. Wang e al. (2018) p oposed a
new app oach o measu ing compa a i e ad an age (NRCA), which is based on o wa d-
linked DVA expo s. DVA e e s o he domes ic alue-added gene a ed by he coun y’s
sec o and is ul ima ely embodied in expo s, ega dless o he place o consump ion o
hese expo s (Asian De elopmen Bank 2019;Ceglowski 2017). This new measu e was
analogous o he Balassa measu e, excep ha i was based on DVA.
The NRCA index is he sha e o an economic sec o ’s o wa d-linked measu e o DVA in
i s expo s. The
NRCAsk
o coun y sin sec o k(i, s = 1, 2,
...
,G;k= 1, 2, N) is as ollows (Asian
De elopmen Bank 2019;Bu lina and Di Ma ia 2020;Liu e al. 2020;Z. Wang e al. 2018):
NRCAsk =VAX_Gsk
∑N
k=1VAX_Gsn ,∑G
i=1VAX_Gik
∑N
k=1∑G
iVAX_Gin
(2)
The subsc ip i e e s o all coun ies excep coun y s, and subsc ip nis all sec o s
excep sec o k.VAX_Gsk is he DVA expo s o coun y sin sec o k:
VAX_Gsk =∑k∑ DVA_FINk
s +DVA_INTk
s +DVA_INT exk
s (3)
The VAX_G o mula is p esen ed in Table 2(Liu e al. 2020;Z. Wang e al. 2018).
The i s ca ego y was DVA in inal expo s (DVA_FIN). The second ca ego y was DVA
in in e media e expo s used by di ec impo e o p oduce he inal local p oduc s
(DVA_INT). Summing up he hi d, ou h, and i h ca ego ies yielded he DVA o economy
sin i s in e media e expo s used by he di ec impo e o p oduce expo s and ul ima ely
abso b o he economies, excep o he sou ce economy s(DVA_INT ex).
Table 2. The VAX_G Decomposi ion Equa ion.
Ca ego y Te m Desc ip ion Fo mula
DVA FIN 1
Domes ic Value Added in inal use commodi y expo s
(VsBssT#Ys
DVA_INT 2 DVA in in e media e expo s u ilized by di ec
impo e s o manu ac u e inal local p oduc s. (VsLssT#(As B Y )
DVA_INT ex 3
DVA in in e media e expo s used by he di ec
impo e o p oduce in e media e expo s and
consumed in o he coun ies excep o he sou ce
coun y s.
(VsLssT# As G
∑
=s,
B Y !
4
DVA in in e media e expo s u ilized by he di ec
impo e o p oduce inal-use expo s o o he
coun ies excep o he sou ce coun y s. (VsLssT# As B G
∑
=s,
Y !
5
DVA in in e media e expo s u ilized by he di ec
impo e o p oduce in e media e expo s o o he
coun ies excep o he sou ce coun y s. (VsLssT# As G
∑
=s,
G
∑
u=s,
B Y u!
Sou ce: (Asian De elopmen Bank 2015;Z. Wang e al. 2018).
Economies 2024,12, 187 6 o 21
In Table 2,
Vs
ep esen s he DVA in coun y s.
Bss
shows he in e se Leon ie N
×
N
ma ix as he o al equi emen ma ix ep esen ing he numbe o g oss ou pu s needed
by coun y s o p oduce a uni o inal demand inc ease in coun y s,
Ys
is he N
×
1
ma ix o he inal demand o coun y o he inal p oduc s p oduced in coun y s,
Lss
illus a es he local Leon ie in e se, and
As
is he N
×
N inpu –ou pu ma ix coe icien .
Addi ionally,
Xs
is he N
×
1 ma ix o he g oss ou pu o coun y s. The symbol # means
an elemen -wise ma ix mul iplica ion ope a ion (Z. Wang e al. 2018). Following Lau sen
(2015), we modi ied he NRCA index in o a symme ical index as ollows:
NRSCAsk =(NRCA sk−1)
,(NRCA sk+1)
(4)
The
NRSCAsk
(he ea e , NRSCA) index anges om
−
1 o1(
−
1
≤
NRSCA
≤
1). An
NRSCA g ea e han 0 indica es ha coun y shas compa a i e ad an ages in sec o k.
Con e sely, an NRSCA o less han 0 sugges s ha coun y shas compa a i e disad an ages
in sec o k.
3.4. Dynamic GMM Model Speci ica ion
A dynamic panel echnique was used o in es iga e he ole o compa a i e ad an age
based on he DVA in d i ing he TVA. The applica ion o he SYS-GMM model begins
wi h iden i ying he s udy objec i es. I hen iden i ies he a iables and panel da a ha
will be u ilized in he model spanning om 2000 o 2020. The nex s age is o assess he
s a iona y and analyze he SYS-GMM model o es ima e he ela ionship be ween a iables.
The Hansen and A ellano–Bond es s assess ins umen alidi y. Finally, hese me hods
we e employed as obus ness alida o s o de e mine he consis ency o he ela ionships
be ween he a iables o in e es .
Dynamic panel da a es ima ion in es iga es dynamically adjus ed obse a ions, con-
ols o unobse ed indi idual he e ogenei y, p o ides mo e in o ma ion and da a ola il-
i y, and educes he possibili y o mul icollinea i y (Bal agi 2005;Wu i e al. 2022).
A ellano and Bond (1991) and A ellano and Bo e (1995) de eloped a gene alized
me hod o momen s (GMM) panel es ima o o dynamic models. Dynamic panel cha -
ac e is ics a e ep esen ed in he model by lag-dependen a iables (Rahayu e al. 2024).
I he lag o he dependen a iable is co ela ed wi h he e o e m, he o dina y leas
squa e es ima o is biased and inconsis en . Thus, he GMM app oach was used o p oduce
a consis en and unbiased es ima o .
Wi hin he GMM amewo k, econome ic analysis uses wo es ima ion echniques:
he sys em GMM (SYS-GMM) and i s -di e ence GMM (FD-GMM). Because o he limi a-
ions o he FD-GMM es ima o , speci ically, i s weak ins umen , he SYS-GMM analysis
was used in his s udy. The e o e, he SYS-GMM es ima o was de eloped o educe
bias and o e come his limi a ion (Bal agi 2005;Blundell and Bond 1998;Rahayu e al.
2024). The empi ical esea ch indica es ha dynamic panel da a es ima ion based on he
SYS-GMM can add ess unobse ed indi idual he e ogenei y, omi ed a iable bias, and
po en ial endogenei y. The e o e, he GMM app oach can p oduce consis en and unbiased
es ima o s (Wu i e al. 2022;Xu 2016). The dynamic panel assumes ha he dis u bance is
independen and iden ically dis ibu ed (IID). (2) The p oblem o unobse ed indi idual
he e ogenei y is almos always ime-in a ian . (3) Compa a i e ad an age is cha ac e ized
as dynamic due o supply and demand luc ua ions in domes ic and in e na ional ma ke s.
(4) No pe ec collinea i y. Pe ec mul icollinea i y is no allowed among independen
a iables in a model. (5) Assump ion o endogenei y. In e nal ins umen s a e used o
sol e his p oblem. (6) Assump ion o alid ins umen s. The ins umen mus be alid,
meaning i mus co ela e wi h an endogenous independen a iable bu no wi h e o
e ms— he assump ion o no second-o de se ial co ela ion. (7) E o e ms mus no ha e
second-o de au oco ela ion. I is es ed using he A ellano-Bond es o ensu e ha he
ins umen used does no co ela e wi h pas e o e ms (Bal agi 2005).
Economies 2024,12, 187 7 o 21
This es ima o employed a lagged a iable as an ins umen , on he assump ion ha
whi e noise e o s would lose consis ency i se ially co ela ed. The ollowing wo speci i-
ca ion es s de e mined he consis ency o he SYS-GMM es ima o : Fi s , he Hansen es
assessed he alidi y o an exogenous ins umen by isola ing o e -iden i ying es ic ions.
In his es , he null hypo hesis s a ed ha he ins umen was alid because he e was no
co ela ion wi h he e o e m. I he Hansen es ejec ed he null hypo hesis, hen he
ins umen and he e o e m we e ela ed, and he es ima e was biased and inconsis en .
Second, he AB es was a es o he p esence o esidual se ial co ela ion. Acco ding
o he null hypo hesis, he e is no second-o de se ial co ela ion o au oco ela ion in
idiosync a ic e o s (Blundell and Bond 1998;Rahayu e al. 2024;Xu 2016). The e o e,
based on he SYS-GMM model, he empi ical model o analyzing he ole o compa a i e
ad an age in TVA is as ollows:
Model 1
FPRi =α+∑p
j=1βjFPRi, −j+∑p
j=1δjNRSCAi, −j+ωCOVID19i +τ1Xi +µi+ i (5)
Model 2
BPRi =σ+∑p
j=1θjBPRi, −j+∑p
j=1ρjNRSCAi, −j+ϵCOVID19i +τ2Xi +µi+ i (6)
Model 3
TVAi =γ+∑p
j=1φjTVAi, −j+∑p
j=1εjNRSCAi, −j+ϑCOVID19i +τ3Xi +µi+ i (7)
whe e subsc ip s iand deno e he coun y and ime index, espec i ely;
µi
is an un-
obse ed ime-in a ian ; and
i
ep esen s idiosync a ic e o . Va iables
µi
and
i
a e
assumed~
IID0, σ2

. Mo eo e ,
FPRi
is he o wa d GVC pa icipa ion a io o coun y
idu ing pe iod ,
BPRi
is he backwa d GVC pa icipa ion a io,
TVAi
is he TVA, and
NRSCAi
is he new e ealed symme ic compa a i e ad an age. In he model, we consid-
e ed he economic impac o he COVID-19 pandemic by including a dummy a iable.
Xi
is a se o con ol a iables and
τ
deno es a column ec o comp ising he co esponding
coe icien s o hese con ol a iables. Ou con ol a iables we e go e nmen e ec i eness
(GOV i )
and con ol o co up ion (
CCi )
. The a iables
α
,
σ
,
and γ
a e cons an , while
β
,
δ
,
ω
,
τ
,
θ
,
ρ
,
ϵ
,
φ
,
ε
, and
ϑ
a e he es ima ed coe icien s. The s udy pe iod spanned om
2010 o 2020. In addi ion, we examined he in luence o he COVID-19 pandemic shock on
he TVA model. Finally, hese app oaches we e used as obus ness alida o s o assess he
consis ency o he ela ionships be ween he a iables o in e es .
Be o e s a ing he empi ical es ima ion, i was c ucial o de e mine whe he he
a iables o in e es we e s a iona y o no . We pe o med s a iona y analysis using he
Augmen ed Dickey–Fulle (ADF) and Le in–Lin–Cu (LLC) es s p oposed by Hao e al.
(2015). This app oach has been widely applied o a oid biased esul s o panel da a wi h
s uc u al b eaks and has a ac ed a en ion in in e na ional ade ne wo k analyses.
4. Empi ical Resul s and Discussion
4.1. Summa y S a is ics
Table 3p esen s he desc ip i e s a is ical esul s o all a iables. I epo s he mean,
s anda d de ia ion (SD), a iance, maximum, and minimum o he a iables o in e es .
Table 3 e eals he ull sample and g oup coun ies. The ull sample a e age o FPR was
0.420, wi h Mal a (EU) ha ing he lowes a 0.164 in 2013, and B unei (ASEAN) ha ing
he highes in 2015 a 0.846. A s anda d de ia ion o 0.111 indica es minimal dispe sion
om he sample means. Simila ly, he a e age sample alue o BPR was 0.345 wi h a
s anda d de ia ion o 0.128, hus indica ing dispe sion om he sample mean. The coun y
wi h he lowes BPR o 0.077 was B unei (ASEAN) in 2010, whe eas Luxembou g (EU)
showed he highes alue o 0.726 in 2011. In addi ion, he coun y wi h he highes TVA
was Bulga ia (EU) a 1.000 in 2011, whe eas he lowes alue o 0.431 was eco ded o he
Economies 2024,12, 187 8 o 21
Philippines (ASEAN) in 2011. A s anda d de ia ion o 0.093 e ealed ha he coun ies
we e signi ican ly dispe sed om a sample a e age o 0.765.
Table 3. Desc ip i e s a is ics.
G oup Va iable Obs Mean SD Va iance Maximum Minimum
Full Sample FPR 451 0.420 0.111 0.012 0.846 0.164
BPR 451 0.345 0.128 0.016 0.726 0.077
TVA 451 0.765 0.093 0.009 1.000 0.431
NRSCA 451 0.114 0.206 0.042 0.654 −0.824
GOV 451 0.952 0.724 0.524 2.335 −0.943
CC 451 0.738 0.949 0.900 2.405 −1.326
ASEAN FPR 99 0.464 0.162 0.026 0.846 0.210
BPR 99 0.286 0.128 0.016 0.563 0.077
TVA 99 0.750 0.111 0.012 0.960 0.431
NRSCA 99 0.132 0.155 0.024 0.654 −0.095
GOV 99 0.352 0.894 0.780 2.335 −0.943
CC 99 −0.117 0.977 0.955 2.180 −1.326
Eas Asia FPR 33 0.432 0.047 0.002 0.522 0.347
BPR 33 0.236 0.088 0.008 0.396 0.133
TVA 33 0.669 0.077 0.006 0.818 0.532
NRSCA 33 −0.095 0.073 0.005 0.022 −0.170
GOV 33 1.041 0.582 0.339 1.822 0.004
CC 33 0.592 0.791 0.626 1.695 −0.562
EU FPR 297 0.393 0.083 0.007 0.721 0.164
BPR 297 0.388 0.110 0.012 0.726 0.162
TVA 297 0.782 0.083 0.007 1.000 0.586
NRSCA 297 0.135 0.223 0.050 0.608 −0.824
GOV 297 1.092 0.564 0.318 2.241 −0.329
CC 297 0.975 0.787 0.620 2.405 −0.272
NA FPR 22 0.562 0.039 0.002 0.702 0.508
BPR 22 0.184 0.064 0.004 0.258 0.107
TVA 22 0.746 0.055 0.003 0.861 0.678
NRSCA 22 0.067 0.056 0.003 0.151 −0.012
GOV 22 1.629 0.147 0.022 1.854 1.319
CC 22 1.600 0.313 0.098 2.070 1.069
No e: FPR, o wa d GVC pa icipa ion a io; BPR, backwa d GVC pa icipa ion a io; TVA, ade in alue-
added; NRSCA, new e ealed symme ic compa a i e ad an age; GOV, go e nmen e ec i eness; CC, con ol o
co up ion; SD, s anda d de ia ion.
The a e age sample alue o compa a i e ad an age measu ed using NRSCA was
0.114, wi h he lowes alue o
−
0.824 om I aly (EU) in 2018, whe eas he highes alue
o 0.654 was eco ded o Lao PDR (ASEAN) in 2019. Fu he mo e, he a e age NRSCA
a iance was 0.042. This alue inc eased du ing he obse a ion pe iod, showing ha
coun ies compe ed wo ldwide o p oduce in e media e good expo s by specializing
in ce ain s ages ha p o ided high alue added. The a e age alues o go e nmen
e ec i eness and con ol o co up ion a e gene ally he highes in NA, while hey a e
he lowes in ASEAN. Con ol o co up ion has he lowes ins i u ional sco e in ASEAN
(−0.117), while NA has he highes (1.600).
4.2. Uni -Roo -Tes Resul
Table 4p esen s he s a iona y es esul s ob ained using ADF and LLC es s. We
conduc ed he es s using S a a 17. The esul s indica e ha he p- alue o he uni oo es
was less han 5%, hus ejec ing he null hypo hesis (Ho) ha all panels con ained a uni
oo . Fu he mo e, he es esul s showed ha each a iable was a s a iona y sequence
and allowed us o p oceed wi h u he analyses.
Economies 2024,12, 187 15 o 21
NRSCA alue. The occu ence o he COVID-19 pandemic inc eased he p ima y sec o ’s
compa a i e ad an age by 38.55%. As a esul , he NRSCA Canada p ima y sec o alue
inc eased om 0.332 in 2019 o 0.460 in 2020. Meanwhile, o he indus ies appea ed o
be con ac ing. The policy o he downs eamness o a coun y’s sec o s u ilizes FVA in
conjunc ion wi h inc easing he coun y’s in ol emen in GVCs.
4.5. The Sys em GMM Dynamic Panel Es ima ion
A dynamic GMM app oach was employed o examine he in luence o he compa a i e
ad an age in encou aging TVA and a oid any po en ial endogenei y issues. SYS-GMM- ype
ins umen s we e employed in his model wi h he i s and highe lags o he p ede e -
mined a iable and he second and highe lags o he endogenous a iable (A ellano and
Bond 1991;A ellano and Bo e 1995;Blundell and Bond 1998). The i s lagged dependen
a iable, FPR, BPR, o TVA, was chosen as he p ede e mined a iable. As TVA is a p ocess,
he models a e he lagged o m o he a iable o allow o he pa ial adjus men o he
TVA o i s long- e m equilib ium alue. Thus, p e ious TVA le els in luenced he cu en
le els. We used S a a 17 o he analysis (STATA; S a aCo p, College S a ion, TX, USA).
A ellano and Bond’s (1991) esidual se ial co ela ion es s we e AR (1) and AR (2). As
p e iously s a ed, Hansen’s disease is a es o o e -iden i ica ion es ic ions.
Table 5summa izes he SYS-GMM es ima ion esul s o all models. The s udy es-
ima ed compa a i e ad an age o d i e TVA by conside ing ins i u ional a iables as a
con ol a iable o a sample o 41 coun ies using he wo-s ep SYS-GMM A ellano–Bond
es ima o . Fu he mo e, we in es iga ed he impac o he COVID-19 pandemic on he TVA.
Table 5. The SYS-GMM esul s o ade in alue-added (TVA), 2010–2020.
Va iables FPR BPR TVA
(1) (2) (3)
Lag o Dep Va 0.115 *** 0.831 *** 0.034 ***
(0.009) (0.053) (0.004)
NRSCA 0.265 *** 0.010 *** 0.171 ***
(0.022) (0.014) (0.019)
GOV 0.012 *** 0.029 *** 0.045 ***
(0.004) (0.011) (0.004)
CC 0.032 *** 0.021 ** 0.021 ***
(0.008) (0.009) (0.004)
COVID-19 −0.010 *** −0.010 *** −0.009 ***
(0.001) (0.001) (0.0008)
Cons an 0.424 ** 0.002 0.726 ***
(0.007) (0.010) (0.006)
No. o obse a ions 369 328 369
No. o coun ies 41 41 41
Hansen es , p- alue 35.13; 0.972 34.21; 0.194 37.60; 0.488
AB–AR (1); p- alue −1.76; 0.079 −3.55; 0.000 −1.70; 0.090
AB–AR (2); p- alue −0.73; 0.464 −0.58; 0.560 0.44; 0.657
No e: *** and ** ep esen s a is ical signi icance a he 1% and 5% le els, espec i ely. SYS-GMM = sys em GMM
es ima o ; in he o wa d linkage, he dependen a iable is FPR, and in he backwa d linkage, he dependen
a iable is BPR; in ade in alue-added, he dependen a iable is TVA. S anda d e o s a e shown in pa en heses.
Sou ce: Calcula ed by he au ho s using S a a 17.
The dependen lagged pe iod includes he expec ed posi i e coe icien and is s a is i-
cally signi ican in all models, hus indica ing ha he dependen a iable o he p e ious
pe iod a ec s he cu en pe iod. The posi i e sign o he coe icien sugges s ha he
coun ies’ TVA in p e ious pe iods con ibu ed posi i ely o ha o he cu en pe iod
because o aw ma e ial impo s in he p e ious pe iod. App oxima ely 11.5% o DVA
expo s e lec he las pe iod’s expo s (Model 1). The posi i e sign o he BPR coe icien
indica es ha app oxima ely 83.1% o o eign alue-added expo s e lec ed he p e ious

Economies 2024,12, 187 16 o 21
pe iod’s expo s (Model 2), and app oxima ely 3.4% o he o al alue added e lec ed he
p e ious pe iod’s expo s (Model 3).
All indings suppo NRSCA’s goal o enhancing TVA by imp o ing he ins i u ional
en i onmen acco ding o go e nmen e ec i eness and he con ol o co up ion. Fo all
models, he es ima ion esul s e ealed ha compa a i e ad an age (NRSCA) posi i ely
and signi ican ly a ec ed TVA. Fo he FPR, BPR, and TVA models, he NRSCA coe icien s
a e 0.265, 0.010, and 0.171, espec i ely.
The implemen a ion o a new compa a i e ad an age measu e, NRSCA, p o ided
accu a e es ima ion esul s o o e come he o e alua ion p oblem ha a ises when using
TRCA. Gi en he inc eased in e media y ade, RCA should be mo e o ien ed owa d
o wa d-linked alue-added expo s (see also Z. Wang e al. 2018). In addi ion, wi h
he eme gence o dynamic compa a i e ad an age, ASEAN’s pa e n o compa a i e
ad an age may become simila o ha o de eloped coun ies, ollowing he lying geese
(FG) pa adigm (Widodo e al. 2018). In his amewo k, indus y is ansmi ed om leade
o ollowe coun ies. Thus, he compa a i e ad an ages o coun ies con inue o e ol e
(Asian De elopmen Bank 2019;B akman and Van Ma ewijk 2017;I o e al. 2017). ASEAN
is a key pa icipan in GVC ac i i ies, playing a e y impo an ole in global ade and
global policy. This is because ASEAN is he main p oduc ion base and inal assemble in
p oduc ion o he global economy and he dominance o ASEAN coun ies’ expo sha e
in he global ma ke eaches 79.2% (Zhong and Su 2021).
Fu he mo e, he COVID-19 pandemic educed he a e age o alue-added ade
(Espi ia e al. 2022;Kazunobu and Hi oshi 2020;Wu i e al. 2023). The coe icien o
COVID-19 was nega i e and s a is ically signi ican o he FPR model (
−
0.010), BPR
model (
−
0.010), and TVA model (
−
0.009). The pandemic has o ced many coun ies o
implemen es ic i e policies o con ain he sp ead o his i us (Vidya and P abheesh
2020). They es ic c oss-bo de ade, which leads coun ies o use domes ic esou ces,
he eby inc easing hei compa a i e ad an age based on DVA. The supply o in e media e
inpu s om o he coun ies was limi ed, hus esul ing in a educed cu en agg ega e
demand and supply (Ayadi e al. 2021;Baldwin and Mau o 2020). The e o e, he ou pu
gap and inal demand o coun ies’ p oduc s a e low (Ghuzini e al. 2020;Wu i e al. 2024).
This implies ha he COVID-19 pandemic has ad e sely a ec ed global ade (Espi ia e al.
2022;Qin e al. 2020;Vidya and P abheesh 2020;Zapa a e al. 2023).
Howe e , he posi i e and signi ican coe icien s on go e nmen e ec i eness and
co up ion con ol sugges ed ha high-quali y ins i u ions would p omo e TVA in in e na-
ional p oduc ion sha ing (Amendolagine e al. 2019;Faheem U e al. 2024;Ge e i e al.
2005;Mouanda and Gong 2019;Ze gawu e al. 2020). The es ima ion esul s we e consis en
h oughou he ins i u ional coe icien analysis using SYS-GMM, wi h a posi i e sign and
s a is ical signi icance o FPR, BPR, and TVA. The posi i e ins i u ional coe icien sugges s
ha a high-quali y ins i u ion inc eases o wa d and backwa d linkage GVC pa icipa ion
(Mouanda and Gong 2019). Ins i u ions, among o he s, play a ole in con ac en o cemen ,
p ope y igh s, and sha eholde p o ec ion. Coun ies could pa icipa e in TVA mo e
when hey had highe go e nmen e ec i eness and be e co up ion con ol. In addi ion,
a mo e e ec i e go e nmen can p o ide a mo e conduci e egula o y en i onmen by
elimina ing quo as o inc ease he Eas e n Eu opean clo hing sec o (Smi h e al. 2014).
4.6. Robus ness Tes s
We examined he obus ness o ou baseline esul s on he ole o compa a i e ad an-
age in d i ing coun ies’ pa icipa ion in TVA using di e en indica o s o he COVID-19
a iable (Ze gawu e al. 2020). We subs i u ed he COVID-19 dummy measu e wi h
COVID-19
shocks o ep esen economic luc ua ions (Wu i e al. 2023). The COVID-19
shocks we e calcula ed based on he g oss expo gap, which is he di e ence be ween eal
and po en ial expo s (Ghuzini e al. 2020;Hubba d e al. 2014;Wu i e al. 2024). The expo
a iable was chosen because i was di ec ly a ec ed by ade luc ua ions. To assess he
impac o he COVID-19 pandemic on global coun y pa icipa ion in TVA, i is c i ical o
Economies 2024,12, 187 17 o 21
de e mine whe he he pe o mance o coun ies is abo e o below hei po en ial (González
and Kowalski 2017). When he po en ial alue is g ea e han he eal alue, a ecession
would occu , which would hen cause an economic ecession, and ice e sa.
In eali y, po en ial expo s we e no obse ed; he e o e, hey we e o en p oxied by
he expec ed alue. We calcula ed he expec ed expo alue based on he Hod ick–P esco
il e (Hubba d e al. 2014). The e o e, he COVID-19 shocks indica e luc ua ions in expo s
du ing he es ima ion pe iod. This app oach was used o examine he in luence o o he
aspec s o COVID-19 on TVA ac i i y.
Table 6displays he co esponding esul s. The esul s om he able illus a ed he
same conclusion in all he models. The dependen lagged pe iod includes he expec ed
posi i e coe icien and is s a is ically signi ican in all models. The posi i e sign o he
coe icien sugges s ha he coun ies’ TVA in p e ious pe iods con ibu ed posi i ely o
ha o he cu en pe iod. App oxima ely 11.6% o DVA expo s e lec he las pe iod’s
expo s. The posi i e sign o he BPR coe icien indica es ha app oxima ely 7.7% o o eign
alue-added expo s e lec ed he p e ious pe iod’s expo s, and app oxima ely 1.2% o
he o al alue added e lec ed he p e ious pe iod’s expo s. Fo all models, he es ima ion
esul s e ealed ha compa a i e ad an age (NRSCA) posi i ely and signi ican ly a ec ed
TVA. Fo he FPR, BPR, and TVA models, he NRSCA coe icien s a e 0.248, 0.024, and 0.032,
espec i ely. Thus, compa a i e ad an age plays a c ucial ole in he p omo ion o TVA (I o
e al. 2017). Fu he , he impac o he COVID-19 shock was nega i e and signi ican wi h
he ins i u ional a iable as a con ol a iable, hus indica ing ha he pandemic educed
alue-added ading ac i i y (Qin e al. 2020;Vidya and P abheesh 2020;Wu i e al. 2022).
Table 6. The SYS-GMM esul s o obus ness es s, ade in alue-added (TVA) wi h COVID-19
shocks, 2010–2020.
Va iables FPR BPR TVA
(1) (2) (3)
Lag o Dep Va 0.116 *** 0.077 *** 0.012 **
(0.008) (0.011) (0.005)
NRSCA 0.248 *** 0.024 * 0.032 ***
(0.015) (0.013) (0.012)
GOV 0.009 ** 0.069 *** 0.069 ***
(0.004) (0.007) (0.009)
CC 0.029 *** 0.036 *** 0.033 ***
(0.009) (0.008) (0.008)
COVID shocks −0.031 *** −0.063 *** −0.083 ***
(0.005) (0.007) (0.003)
Cons an 0.406 *** 0.207 *** 0.733 ***
(0.007) (0.019) (0.009)
No. o obse a ions 369 410 410
No. o coun ies 41 41 41
Hansen es , p- alue 34.99; 0.973 35.51; 0.969 38.86; 0.652
AB–AR (1); p- alue −1.69; 0.092 −2.50; 0.012 −1.33; 0.185
AB–AR (2); p- alue −0.83; 0.408 −1.37; 0.172 −1.02; 0.307
No e: ***, **, and * ep esen s a is ical signi icance a he 1%, 5%, and 10% le els, espec i ely.
SYS-GMM = sys em
GMM es ima o ; in he o wa d linkage, he dependen a iable is FPR, and in he backwa d linkage, he dependen
a iable is BPR; in ade in alue-added, he dependen a iable is TVA. S anda d e o s a e shown in pa en heses.
Sou ce: Calcula ed by he au ho s using S a a 17.
5. Conclusions
In his a icle, we employed he sys em GMM es ima o s o a dynamic panel model
o in es iga e he ole o he compa a i e ad an age in d i ing TVA by conside ing in-
s i u ional quali y as a con ol a iable, using he ADB MRIO o he pe iod 2010–2020.
Mo eo e , he COVID-19 pandemic a iable was included in his s udy’s model o examine
he pandemic’s impac on alue-added ade. In pa icula , we ocused on a new e ealed
symme ic compa a i e ad an age measu e, NRSCA. This symme ic measu e was used
Economies 2024,12, 187 18 o 21
o accu a e calcula ions, using DVA h ough o wa d linkage, ins ead o g oss expo s.
NRSCA add essed he issues o o e alua ion, double coun ing, and implici dis o ions in
in e na ional ade ac oss bo de s.
The esul s sugges ed an inc ease in alue-added ade wi h he signi ican ole o he
compa a i e ad an age, along wi h he suppo o quali y ins i u ional se ices in each
coun y. Wo ldwide coun ies’ compa a i e ad an ages changed dynamically. Indonesia
had a compa a i e ad an age in he p ima y and low echnology manu ac u ing sec o s.
Malaysia emained e y compe i i e in he p ima y sec o s. In addi ion, Malaysia had
a compa a i e ad an age based on DVA in se e al sec o s in low, medium, and high
echnology manu ac u ing. The Philippines emained highly compe i i e in low echnol-
ogy manu ac u ing. In addi ion, he Philippines had a compa a i e ad an age based on
DVA in se e al o he medium and high echnology manu ac u ing and public se ices
sec o s. Singapo e emained highly compe i i e in se e al o he medium echnology
manu ac u ing and business se ices sec o s. Thailand emained highly compe i i e in
p ima y indus ies such as ag icul u e, hun ing, o es y, and ishing. Thailand also had a
compa a i e ad an age based on DVA in se e al low, medium, and high echnology manu-
ac u ing and business se ices sec o s. China had a compa a i e ad an age in he Eas
Asia Region in low, medium, and high echnology manu ac u ing sec o s. Howe e , Japan
and Ko ea had a compa a i e ad an age in medium and high echnology manu ac u ing.
The posi i e NRSCA a e age alue indica ed ha Ge many had a compa a i e ad an age
in he medium and high echnology manu ac u ing sec o s. Fu he mo e, Poland and he
Slo ak Republic had a compa a i e ad an age om he pe spec i e o o wa d linkage
in he low echnology manu ac u ing sec o . In he mean ime, G eece had a compa a i e
ad an age in se e al p ima y indus ies and low echnology manu ac u ing. In he US
A ea, he US had a compa a i e ad an age om he pe spec i e o o wa d linkage in he
p ima y sec o , business se ices, and pe sonal and public se ices. Meanwhile, Canada
had a compa a i e ad an age in he p ima y sec o . The COVID-19 pandemic slowed
down TVA and po en ially dis up ed many sec o s.
Fu he mo e, go e nmen s should de elop alue-added expo s based on NRSCA o
es ablish a compe i i e ad an age and enhance in es men in esea ch and de elopmen .
Mo eo e , he go e nmen is expec ed o build anspo a ion and logis ics in as uc u e
o imp o e supply chain e iciency and acili a e in e - and in a- egional ade. Fu he
esea ch is equi ed o inco po a e con ol a iables, such as g a i y con ol, in as uc u e,
GDP pe capi a, and ade egula ion, and o calcula e he posi ion o he leading sec o
om inal use.
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 p esen ed in his s udy a e a ailable on eques om he
co esponding au ho .
Acknowledgmen s: The au ho is hank ul o he ADB eam o p o iding he equi ed da a. I would
also like o hank anonymous e iewe s o hei aluable commen s and sugges ions.
Con lic s o In e es : The au ho decla es no con lic o in e es .
Economies 2024,12, 187 19 o 21
Appendix A
Table A1. Lis o ADB mul i- egional inpu –ou pu coun ies.
No. G oup Coun ies
1 ASEAN
Malaysia, Indonesia, Thailand, Philippines, Singapo e, Vie Nam, B unei Da ussalam, Lao PDR, Cambodia
2 Eas Asia Japan, People’s Republic o China, Republic o Ko ea
3 EU
Aus ia, Bulga ia, Belgium, Czech Republic, Cyp us, Ge many, Denma k, Spain, Es onia, F ance, Finland,
G eece, C oa ia, Hunga y, I eland, I aly, Li huania, Luxembou g, Mal a, La ia, Ne he lands, Poland,
Po ugal, Romania, Slo enia, Slo ak Republic, Sweden
4 NA Canada, Uni ed S a es
Sou ce: Au ho s’ compila ions.
Re e ences
Amendolagine, Vi o, And ea F. P esbi e o, Robe a Rabello i, and Ma co San ilippo. 2019. Local Sou cing in De eloping Coun ies:
The Role o Fo eign Di ec In es men s and Global Value Chains. Wo ld De elopmen 113: 73–88. [C ossRe ]
A ellano, Manuel, and Olympia Bo e . 1995. Ano he Look a he Ins umen al Va iables Es ima ion o E o Componen Models.
Jou nal o Econome ics 68: 29–51. [C ossRe ]
A ellano, Manuel, and S ephen Bond. 1991. Some Tes s o Speci ica ion o Panel Da a: Mon e Ca lo E idence and an Applica ion o
Employmen Equa ions. Re iew o Economic S udies 58: 277–97. [C ossRe ]
Asian De elopmen Bank. 2015. Global Value Chains Indica o s o In e na ional P oduc ion Sha ing. Key Indica o s o Asia and he Paci ic
2015. Manila: Asian De elopmen Bank. A ailable online: h ps://www.adb.o g/si es/de aul / iles/publica ion/175162/g c.
pd (accessed on 9 Ma ch 2022).
Asian De elopmen Bank. 2019. The E olu ion o Indonesia’s Pa icipa ion in Global Value Chains. Manila: Asian De elopmen Bank. Manila:
Asian De elopmen Bank. [C ossRe ]
A huko ala, P ema-Chand a, and Nobuaki Yamashi a. 2006. P oduc ion F agmen a ion and T ade In eg a ion: Eas Asia in Global
Con ex . No h Ame ican Jou nal o Economics and Finance 17: 233–56. [C ossRe ]
Ayadi, Rym, Gio gia Gio anne i, En ico Ma asi, Giulio Vannelli, and Chahi Zaki. 2021. Demand and Supply Exposu e h ough
Global Value Chains: Eu o-Medi e anean Coun ies du ing COVID. The Wo ld Economy 45: 637–56. A ailable online: h ps:
//onlinelib a y.wiley.com/doi/epd /10.1111/ wec.13156 (accessed on 1 July 2023). [C ossRe ] [PubMed]
Balassa, Bela. 1965. T ade Libe alisa ion and ‘Re ealed’ Compa a i e Ad an age. The Manches e School 33: 99–123. [C ossRe ]
Baldwin, Richa d E., and Bea ice W. di Mau o, eds. 2020. Economics in he Time o COVID-19. A VoxEU.o g eBook. London: CEPR
P ess. A ailable online: h ps:// oxeu.o g/a icle/economics- ime-co id-19-new-ebook (accessed on 2 Ap il 2023).
Bal agi, Badi H. 2005. Econome ic Analysis o Panel Da a. Hoboken: John Wiley & Sons L d.
Blundell, Richa d, and S ephen Bond. 1998. Ini ial Condi ions and Momen Res ic ions in Dynamic Panel Da a Models. Jou nal o
Econome ics 87: 115–43. A ailable online: h ps://www.ucl.ac.uk/~uc p39a/Blundell-Bond-1998.pd (accessed on 15 June 2022).
Bo in, Alessand o, and Michele Mancini. 2019. Measu ing Wha Ma e s in Global Value Chains and Value-Added T ade. WPS 8804.
A ailable online: h p://hdl.handle.ne /10986/31533 (accessed on 30 No embe 2022).
B akman, S e en, and Cha les Van Ma ewijk. 2017. A Close Look a Re ealed Compa a i e Ad an age: G oss- e sus Value-Added
T ade Flows. Pape s in Regional Science 96: 61–92. [C ossRe ]
Bu lina, Chia a, and Eleono a Di Ma ia. 2020. Manu ac u ing and Value-Added Dynamics in Global Value Chains: The Case o I aly.
Compe i i eness Re iew 30: 457–70. [C ossRe ]
Ceglowski, Jane . 2017. Assessing Expo Compe i i eness h ough he Lens o Value Added. Wo ld Economy 40: 275–96. [C ossRe ]
Chen, Ji-Ming, and Yi-Qing Chen. 2022. China Can P epa e o End I s Ze o-COVID Policy. Na u e Medicine 28: 1104–1105. [C ossRe ]
Elsalih, Osama, Kamil Se oglu, and Mus a a Besim. 2021. De e minan s o Compa a i e Ad an age o C ude Oil P oduc ion: E idence
om OPEC and Non-OPEC Coun ies. In e na ional Jou nal o Finance and Economics 26: 3972–83. [C ossRe ]
Espi ia, Al a o, Aadi ya Ma oo, Nadia Rocha, Michele Ru a, and Debo ah Winkle . 2022. Pandemic T ade: COVID-19, Remo e Wo k
and Global Value Chains. Wo ld Economy 45: 561–89. [C ossRe ]
Faheem U , Rehman, Islam Md. Moni ul, and Kazi Sohag. 2024. Does In as uc u al De elopmen Allu e Fo eign Di ec In es men ?
The Role o Bel and Road Ini ia i es. In e na ional Jou nal o Eme ging Ma ke s 19: 1026–50. [C ossRe ]
Fan, Zhaobin, Sajid Anwa , and Ying Zhou. 2023. Cen aliza ion o T ade Ag eemen s Ne wo k and Global Value Chain Pa icipa ion.
Qua e ly Re iew o Economics and Finance 94: 11–24. [C ossRe ]
Ge e i, Ga y, John Humph ey, and Timo hy S u geon. 2005. The Go e nance o Global Value Chains. Re iew o In e na ional Poli ical
Economy 12: 78–104. [C ossRe ]
Ghuzini, Diny, Josephine Wu i, and Kun a i Dasih. 2020. S uc u al Shocks and Mac oeconomic Condi ions in Indonesia. Jou nal o
Applied Economic Sciences XV: 488–506. A ailable online: h ps://www.ceeol.com/sea ch/a icle-de ail?id=894712 (accessed on
25 June 2024).
Economies 2024,12, 187 20 o 21
González, Ja ie Lopez, and P zemyslaw Kowalski. 2017. Global Value Chain Pa icipa ion in Sou heas Asia: T ade and Rela ed Policy
Implica ions. In P oduc ion Ne wo ks in Sou heas Asia. Edi ed by Lili Yan Ing and Fukuna i Kimu a. New Yo k: Rou ledge.
Hao, Yu, Hua Liao, and Yi-Ming Wei. 2015. Is China’s Ca bon Reduc ion Ta ge Alloca ion Reasonable? An Analysis Based on Ca bon
In ensi y Con e gence. Applied Ene gy 142: 229–39. [C ossRe ]
Hayakawa, Kazunobu, and Hi oshi Mukunoki. 2021. Impac s o COVID-19 on Global Value Chains. De eloping Economies 59: 154–77.
[C ossRe ]
Hubba d, R. Glenn, An hony P. O’B ien, Ma hew Ra e y, and Robe J. Go don. 2014. Mac oeconomics. London: Pea son Educa ion
Limi ed.
Hummels, Da id, Jun Ishii, and Kei-Mu Yi. 2001. The Na u e and G ow h o Ve ical Specializa ion in Wo ld T ade. Jou nal o
In e na ional Economics 54: 75–96. [C ossRe ]
Ing, Lili Yan, and Fukuna i Kimu a, eds. 2017a. P oduc ion Ne wo ks in Sou heas Asia. Economic Resea ch Ins i u e o ASEAN and
Eas Asia. New Yo k: Rou ledge, Taylo and F ancis G oup. A ailable online: h ps://www.e ia.o g/publica ions/p oduc ion-
ne wo ks-in-sou heas -asia/ (accessed on 24 Sep embe 2022).
Ing, Lili Yan, and Fukuna i Kimu a, eds. 2017b. Global Value Chain Pa icipa ion in Sou heas Asia: T ade and Rela ed Policy
Implica ions. In P oduc ion Ne wo ks in Sou heas Asia. New Yo k: Rou ledge.
Inoma a, Si oshi. 2013. T ade in Value Added: An Eas Asian Pe spec i e. ADBI Wo king Pape Se ies; Tokyo: Asian De elopmen Bank
Ins i u e. [C ossRe ]
I o, Tadashi, Lo enzo Ro unno, and Pie e Louis Vézina. 2017. Hecksche –Ohlin: E idence om Vi ual T ade in Value Added. Re iew
o In e na ional Economics 25: 427–46. [C ossRe ]
Johnson, Robe C., and Guille mo Nogue a. 2012. Accoun ing o In e media es: P oduc ion Sha ing and T ade in Value Added.
Jou nal o In e na ional Economics 86: 224–36. [C ossRe ]
Johnson, Robe C., and Guille mo Nogue a. 2017. A Po ai o T ade in Value-Added o e Fou Decades. Re iew o Economics and
S a is ics 99: 896–911. [C ossRe ]
Kau mann, Daniel, Aa K aay, and Massimo Mas uzzi. 2010. The Wo ldwide Go e nance Indica o s: Me hodology and Analy ical
Issues. Hague Jou nal on he Rule o Law 3: 220–46. [C ossRe ]
Kazunobu, Hayakawa, and Mukunoki Hi oshi. 2020. Impac s o COVID-19 on Global Value Chains. Ins i u e o De eloping Economies
(IDE) Discussion Pape s 791. A ailable online: h ps://i .ide.go.jp/?ac ion=pages_ iew_main&ac i e_ac ion= eposi o y_ iew_
main_i em_de ail&i em_id=51871&i em_no=1&page_id=39&block_id=158 (accessed on 15 Janua y 2023).
Kee, Hiau Looi, and Heiwai Tang. 2016. Domes ic Value Added in Expo s: Theo y and Fi m E idence om China. Ame ican Economic
Re iew 106: 1402–36. [C ossRe ]
Koopman, Robe , Zhi Wang, and Shang-Jin Wei. 2014. T acing Value-Added and Double Coun ing in G oss Expo s. Am ican Economic
Re iew 104: 459–94. [C ossRe ]
Lau sen, Keld. 2015. Re ealed Compa a i e Ad an age and he Al e na i es as Measu es o In e na ional Specializa ion. Eu asian
Business Re iew 5: 99–115. [C ossRe ]
Leon ie , Wassily W. 1936. Quan i a i e Inpu and Ou pu Rela ions in he Economic Sys em o he Uni ed S a es. Re iew o Economics
and S a is ics 18: 105–25. A ailable online: h ps://o ion.ma h.ias a e.edu/d iessel/15Models/1936_Inpu _Ou pu .pd (accessed
on 15 Augus 2022). [C ossRe ]
Le omain, Elsa, and Gianluca O i ice. 2014. New Re ealed Compa a i e Ad an age Index: Da ase and Empi ical Dis ibu ion.
In e na ional Economics 139: 48–70. [C ossRe ]
Le chenko, And ei A. 2007. Ins i u ional Quali y and In e na ional T ade. Re iew o Economic S udies 74: 791–819. [C ossRe ]
Liu, Xuepeng, Aadi ya Ma oo, Zhi Wang, and Shang-Jin Wei. 2020. Se ices De elopmen and Compa a i e Ad an age in Manu ac-
u ing. Jou nal o De elopmen Economics 144: 102438. [C ossRe ]
Lo ano, Giusy, Su eyya Me iç, Gülsüm Emel Zengin, and De in O hon. 2013. Chemical and Biological T ea men Technologies o
Lea he Tanne y Chemicals and Was ewa e s: A Re iew. Science o he To al En i onmen 461–62: 265–81. [C ossRe ]
Ma ca o, Ma ilia, Ca olina Bal a , and Fe nando Sa i. 2019. In e na ional Compe i i eness in a Ve ically F agmen ed P oduc ion
S uc u e: Empi ical Challenges and E idence. Economics Bulle in 39: 876–93. A ailable online: h ps://ideas. epec.o g/a/ebl/
ecbull/eb-18-00788.h ml (accessed on 5 Sep embe 2023).
Mouanda, GilhaiméM., and Jiong Gong. 2019. De e minan s o Global Value Chains Pa icipa ion o Landlocked Coun ies.
In e na ional Jou nal o Social Science and Economic Resea ch 4: 3265–94. A ailable online: h ps://ijsse .o g/ iles_2019/ijsse _04__24
6.pd (accessed on 25 June 2023).
Na suda, Kao u, No iyuki Segawa, and John Thobu n. 2013. Libe aliza ion, Indus ial Na ionalism, and he Malaysian Au omo i e
Indus y. Global Economic Re iew 42: 113–34. A ailable online: h ps://www. and online.com/doi/abs/10.1080/1226508X.2013.7
91475 (accessed on 8 Sep embe 2023). [C ossRe ]
Pa obek, Jan, Hube Paluš, Ma ina Kalama o a, E ika Louˇcano a, Anna K ižano a, and Ka a ina Repko a Š o ko a. 2016. Compa a-
i e Analysis o Wood and Semi-Finished Wood P oduc T ade o Slo akia and I s Cen al Eu opean T ading Pa ne s. D ewno 59:
183–94. [C ossRe ]
Pa a, Ugu Ko ku , Mehme Me in Dam, and Funda Kaya. 2023. How E ec i e A e Renewable Ene gy, Tou ism, T ade Openness,
and Fo eign Di ec In es men on CO
2
Emissions? An EKC Analysis o ASEAN Coun ies. En i onmen al Science and Pollu ion
Resea ch 30: 14821–37. [C ossRe ]

Economies 2024,12, 187 21 o 21
P e e, Da ide Del, Gio gia Gio anne i, and En ico Ma asi. 2018. Global Value Chains: New E idence o No h A ica. In e na ional
Economics 153: 42–54. [C ossRe ]
Qin, Meng, Xiuyan Liu, and Xiaoxue Zhou. 2020. COVID-19 Shock and Global Value Chains: Is The e a Subs i u e o China? Eme ging
Ma ke s Finance and T ade 56: 3588–98. [C ossRe ]
Rahayu, Caecilia Wahyu Es ining, Ch is ina He i T i Rahmawa i, Josephine Wu i, Yuliana Rini Ha dan i, and Lau en ius Bambang
Ha no o. 2024. Role o Indonesia’s G20 P esidency and Exchange Ra e on LQ45 S ock P ice: Dynamic Panel Model App oach.
Mig a ion Le e s 21: 926–39. [C ossRe ]
Shuai, Jing, Xinjie Peng, Yujia Zhao, Yilan Wang, Wei Zu, Jinhua Cheng, Yang Lu, and Jingjin Wang. 2022. A Dynamic E alua ion
on he In e na ional Compe i i eness o China’s Ra e Ea h P oduc s: An Indus ial Chain and Tech-Inno a ion Pe spec i e.
Resou ces Policy 75: 102444. [C ossRe ]
Smi h, Ad ian, John Pickles, Milan Buˇcek, Rudol Pás o , and Bob Begg. 2014. The Poli ical Economy o Global P oduc ion Ne wo ks:
Regional Indus ial Change and Di e en ial Upg ading in he Eas Eu opean Clo hing Indus y. Jou nal o Economic Geog aphy 14:
1023–51. [C ossRe ]
Song, Yi u, Chunjiao Yu, Lulu Hao, and Xi Chen. 2021. Pa h o China’s High-Tech Indus y o Pa icipa e in he Recons uc ion o
Global Value Chains. Technology in Socie y 65: 101486. [C ossRe ]
Timme , Ma cel P., Ba Los, Robe S eh e , and Gaai zen J. de V ies. 2013. F agmen a ion, Incomes, and Jobs: An Analysis o Eu opean
Compe i i eness. Economic Policy 28: 613–61. [C ossRe ]
Vidya, C. T., and K.P. P abheesh. 2020. Implica ions o COVID-19 Pandemic on he Global T ade Ne wo ks. Eme ging Ma ke s Finance
and T ade 56: 2408–21. [C ossRe ]
Wang, Qiang, Jiayi Sun, Rong ong Li, and Ugu Ko ku Pa a. 2024. Linking T ade Openness o Load Capaci y Fac o : The Th eshold
E ec s o Na u al Resou ce Ren and Co up ion Con ol. Gondwana Resea ch 129: 371–80. [C ossRe ]
Wang, Zhi, Shang-jin Wei, and Kun u Zhu. 2018. Quan i ying In e na ional P oduc ion Sha ing a he Bila e al and Sec o Le els. NBER
Wo king Pape 19677. Camb idge: Na ional Bu eau o Economic Resea ch, Re ised Feb ua y 2018. A ailable online: h ps:
//www.nbe .o g/pape s/w19677 (accessed on 5 Ma ch 2021).
Widodo, T i, Rini Se yas u i, and S i Adiningsih. 2018. ‘Flying Geese’ Pa adigm: Re iew, Analy ical Tool, and Applica ion. Munich
Pe sonal RePEc A chi e. A ailable online: h ps://mp a.ub.uni-muenchen.de/87171/ (accessed on 10 Feb ua y 2024).
Wu i, Josephine, T i Widodo, and Ami ullah Se ya Ha di. 2022. Global Value Chains Pa icipa ion du ing he COVID-19 Pandemic: A
Dynamic Panel App oach. Economies 10: 121. [C ossRe ]
Wu i, Josephine, T i Widodo, and Ami ullah Se ya Ha di. 2023. Speed o Con e gence in Global Value Chains: Fo wa d o Backwa d
Linkage. Heliyon 9: e18070. [C ossRe ] [PubMed]
Wu i, Josephine, Yuliana Rini Ha dan i, Lau en ius Bambang Ha no o, Caecilia Wahyu Es ining Rahayu, and Ch is ina He i T i
Rahmawa i. 2024. The Impac o In e es Ra e Spillo e on Ou pu Gap: A Dynamic Spa ial Du bin Model. Economies 12: 22.
[C ossRe ]
Xu, Hai eng. 2016. Financial In e media ion and Economic G ow h in China: New E idence om Panel Da a. Eme ging Ma ke s Finance
and T ade 52: 724–32. [C ossRe ]
Zapa a, Amadeo Na a o, Ma ía A azola, and Joséde He ia. 2023. De e minan s o High-Tech Expo s: New E idence om OECD
Coun ies. Jou nal o he Knowledge Economy 15: 1103–17. [C ossRe ]
Ze gawu, Y. Zewdu, Yabibal M. Walle, and JoséM. G. Gómez. 2020. The Join Impac o In as uc u e and Ins i u ions on Economic
G ow h. Jou nal o Ins i u ional Economics 16: 481–502. [C ossRe ]
Zhang, Qian. 2024. The Impac o Digi aliza ion on he Upg ading o China’s Manu ac u ing Sec o ’s Global Value Chains. Jou nal o
he Knowledge Economy, 1–24. [C ossRe ]
Zhong, Sheng, and Bin Su. 2021. In es iga ing Asean’s Pa icipa ion in Global Value Chains: P oduc ion F agmen a ion and Regional
In eg a ion. Asian De elopmen Re iew 38: 159–88. [C ossRe ]
Disclaime /Publishe ’s No e: The s a emen s, opinions and da a con ained in all publica ions a e solely hose o he indi idual
au ho (s) and con ibu o (s) and no o MDPI and/o he edi o (s). MDPI and/o he edi o (s) disclaim esponsibili y o any inju y o
people o p ope y esul ing om any ideas, me hods, ins uc ions o p oduc s e e ed o in he con en .