Yang, Runyu; Ryu, Youngbok; Oe , Mikhail V.
A icle
Assessing he o eign di ec in es men pe o mance o
middle-income coun ies using da a en elopmen analysis
wi h ansla ion in a iance
Economies
P o ided in Coope a ion wi h:
MDPI – Mul idisciplina y Digi al Publishing Ins i u e, Basel
Sugges ed Ci a ion: Yang, Runyu; Ryu, Youngbok; Oe , Mikhail V. (2024) : Assessing he o eign
di ec in es men pe o mance o middle-income coun ies using da a en elopmen analysis wi h
ansla ion in a iance, Economies, ISSN 2227-7099, MDPI, Basel, Vol. 12, Iss. 11, pp. 1-27,
h ps://doi.o g/10.3390/economies12110314
This Ve sion is a ailable a :
h ps://hdl.handle.ne /10419/329241
S anda d-Nu zungsbedingungen:
Die Dokumen e au EconS o dü en zu eigenen wissenscha lichen
Zwecken und zum P i a geb auch gespeiche und kopie we den.
Sie dü en die Dokumen e nich ü ö en liche ode komme zielle
Zwecke e iel äl igen, ö en lich auss ellen, ö en lich zugänglich
machen, e eiben ode ande wei ig nu zen.
So e n die Ve asse die Dokumen e un e Open-Con en -Lizenzen
(insbesonde e CC-Lizenzen) zu Ve ügung ges ell haben soll en,
gel en abweichend on diesen Nu zungsbedingungen die in de do
genann en Lizenz gewäh en Nu zungs ech e.
Te ms o use:
Documen s in EconS o may be sa ed and copied o you pe sonal
and schola ly pu poses.
You a e no o copy documen s o public o comme cial pu poses, o
exhibi he documen s publicly, o make hem publicly a ailable on he
in e ne , o o dis ibu e o o he wise use he documen s in public.
I he documen s ha e been made a ailable unde an Open Con en
Licence (especially C ea i e Commons Licences), you may exe cise
u he usage igh s as speci ied in he indica ed licence.
h ps://c ea i ecommons.o g/licenses/by/4.0/
Ci a ion: Yang, Runyu, Youngbok
Ryu, and Mikhail V. Oe . 2024.
Assessing he Fo eign Di ec
In es men Pe o mance o
Middle-Income Coun ies Using Da a
En elopmen Analysis wi h
T ansla ion In a iance. Economies 12:
314. h ps://doi.o g/10.3390/
economies12110314
Academic Edi o : Robe Czudaj
Recei ed: 7 Oc obe 2024
Re ised: 1 No embe 2024
Accep ed: 8 No embe 2024
Published: 19 No embe 2024
Copy igh : © 2024 by he au ho s.
Licensee MDPI, Basel, Swi ze land.
This a icle is an open access a icle
dis ibu ed unde he e ms and
condi ions o he C ea i e Commons
A ibu ion (CC BY) license (h ps://
c ea i ecommons.o g/licenses/by/
4.0/).
A icle
Assessing he Fo eign Di ec In es men Pe o mance o
Middle-Income Coun ies Using Da a En elopmen Analysis
wi h T ansla ion In a iance
Runyu Yang , Youngbok Ryu * and Mikhail V. Oe
College o P o essional S udies, No heas e n Uni e si y, 360 Hun ing on A e, Bos on, MA 02115, USA;
[email p o ec ed] (R.Y.); [email p o ec ed] (M.V.O.)
*Co espondence: y[email p o ec ed]
Abs ac : Fo eign di ec in es men (FDI) is a p ima y ehicle o manu ac u ing ans e . Middle-
income coun ies can bene i by e ec i ely u ilizing FDI o achie e echnological de elopmen and
economic equali y and possibly add ess he middle-income ap issue. This s udy assessed he FDI
pe o mance o en middle-income coun ies and examined he s a is ical ela ionships be ween
hei pe o mance and hei con ex s: echnological de elopmen , economic equali y, and du ing he
COVID-19 pandemic. Fo he o me , we employed non- adial da a en elopmen analysis, aking
ad an age o i s ansla ion in a iance p ope y o de i e e iciency sco es; o he la e , we conduc ed
a se ies o K uskal–Wallis es s o examine he s a is ical ela ionships. Acco ding o he analysis
esul s, we ound ha (a) mos coun ies, excep China and India, showed s able e iciency sco es o e
ime, (b) hei e iciency sco es we e s a is ically signi ican ly associa ed wi h he le el o echnological
de elopmen (indica ed by hei echnology li ecycle-based sigmoid cu es) and economic equali y
( ep esen ed by Gini index and po e y indica o ); and (c) hei e iciency sco es we e no associa ed
wi h he COVID-19 pandemic. The esul s imply ha o imp o e hei o eign di ec in es men
pe o mance, hos coun ies may need o enhance hei abso p i e capaci y in bo h he echnological
and economic domains.
Keywo ds: o eign di ec in es men ; middle-income coun ies; da a en elopmen analysis; economic
inequali y; echnological de elopmen
1. In oduc ion
In he e a o a global supply chain, manu ac u ing ans e is an essen ial opic,
which desc ibes he p ocess o eloca ing manu ac u ing ope a ions om one coun y o
ano he along wi h he ans e o echnical and ope a ion knowledge. I has signi ican
implica ions o he in e na ional economy, especially in middle-income coun ies (Mo an
e al. 2005). Manu ac u ing, as a labo -in ensi e indus y, gene ally escapes om high-cos
home coun ies wi h s ic e egula ions o low-cos hos coun ies wi h lax egula ions
o build long- e m supply chains so ha businesses in home coun ies can achie e s able
p o i s (Pon andol o 1999).
The dominan pa hway o manu ac u ing ans e is o eign di ec in es men (FDI).
In he p ocess o manu ac u ing ans e , he e is signi ican FDI ac i i y and la ge capi al
lows in ol ed. I ends o begin wi h mul ina ional companies in es ing in se ing up
ac o ies o simple p ocessing and assembly, e ol ing in o in eg a ed supply chain clus e s,
and e en ually becoming key playe s and e en egional manu ac u ing hubs (Ande sen
2006). In his expanding and deepening in es men p ocess, in es o s no only gain mo e
ma gins bu also shape he global mac oeconomic ecosys em.
Middle-income coun ies seek o a ac FDI because hey an icipa e ha FDI will c ea e
a conside able numbe o jobs, s imula e domes ic in es men , and p omo e echnological
de elopmen . The e icien u iliza ion o FDI enables he economy o enjoy a i uous cycle,
Economies 2024,12, 314. h ps://doi.o g/10.3390/economies12110314 h ps://www.mdpi.com/jou nal/economies
Economies 2024,12, 314 2 o 27
leading o long- e m g ow h wi h he pa e n o “manu ac u ing + expo ” (Hanson and
Robe son 2008), as demons a ed by many middle-income coun ies like China, Vie nam,
and Malaysia (Meye 2004). Howe e , he lack o a egula o y amewo k o e pollu an
emissions in middle-income coun ies, a conside able po ion o which s ems om ene gy-
in ensi e manu ac u ing, leads o se ious en i onmen al issues.
Fu he mo e, i is conce ning ha middle-income coun ies p e en alling in o he
“middle-income ap” and o achie e con inuous g ow h h ough he e ec i e u iliza ion o
FDI. On he one hand, echnology ans e om ad anced coun ies o eme ging ma ke s
o en aces sys emic p oblems, as illus a ed by a Ko ean case s udy (Yoon 2009). The impo
o ad anced machine y can boos p oduc i i y in de eloping coun ies, bu a pe sis en
echnology gap exis s compa ed o de eloped na ions (Na a e i e al. 1998). On he o he
hand, hei abso p i e capaci y plays a c ucial ole in echnology ans e and inno a ion o
i ms in middle-income coun ies. I enables companies o acqui e, assimila e, ans o m,
and exploi knowledge om o eign sou ces (La ukha 2018;Khan e al. 2019). Fi ms
wi h a highe abso p i e capaci y a e mo e likely o bene i om in e na ional echnology
ans e h ough o eign owne ship, supplying mul ina ional en e p ises, and expo ing
(Van De Heiden e al. 2016). Howe e , many middle-income coun y i ms ace challenges
in de eloping abso p i e capaci y, c ea ing a conund um whe e hey s uggle o access new
knowledge wi hou p io upg ading (Khan e al. 2019). While abso p i e capaci y is c ucial
o inno a ion in low- ech companies (Del Ca pio Gallegos and Mi alles To ne 2018), i s
impo ance a ies depending on he indus y’s echnological le el and he coun y’s s age
o de elopmen (Mancusi 2008).
Rega ding manu ac u ing ans e , his s udy ocused on FDI as a p ima y ac o in
he pe o mance o en middle-income coun ies by comp ehensi ely conside ing mul iple
aspec s, including echnology ans e and spillo e , domes ic in es men , po e y educ-
ion, economic g ow h, and manu ac u ing pollu ion. While a la ge body o s udies has
sough o in es iga e FDI and manu ac u ing ans e using pa ame ic analysis o iden i y
signi ican ac o s, he e a e ela i ely ew s udies applying non-pa ame ic analysis o
e alua e ela i e e iciency sco es o coun ies based on iden i ied ac o s. To ill he gap
in he ex an li e a u e on non-pa ame ic echnique-based mac oeconomic esea ch, his
s udy employed an applied ma hema ical me hod called da a en elopmen analysis (DEA).
In add essing po en ial c i iques o ou app oach, we acknowledge he limi a ions o DEA,
pa icula ly ega ding i s eliance on a ailable inpu –ou pu da a, which may no ully
cap u e all ex e nali ies. Since ou s udy pe iod (2015–2022) includes COVID-19 imes,
some middle-income coun ies expe ienced nega i e FDI ne in low as an economic a e -
ma h o he global pandemic wi hin he s udy pe iod. To mi iga e his, we employed a
non- adial DEA model wi h ansla ion in a iance, which allowed us o accoun o he
non-posi i e alues in he da ase . Addi ionally, he use o a new indica o o echnological
de elopmen — he sigmoid knowledge accumula ion based on pa en da a—p o ides a
mo e nuanced unde s anding o echnology p og ess ac oss di e en coun ies, which
add esses he conce ns ela ed o he o e simpli ica ion o echnological ad ancemen s.
This s udy also con ibu es o he cu en li e a u e by es ing in e es ing hypo heses.
A e a me a e iciency on ie was c ea ed based on agg ega ed da a ac oss coun ies o e
he s udy pe iod and he e iciency sco es o each coun y in each yea we e compu ed,
we examined h ee hypo heses ela ed o echnological de elopmen , economic inequali y,
and global pandemic by applying a se ies o K uskal–Wallis es s o di e en se s o
middle-income coun ies. While we used well-es ablished indica o s o he es s (e.g.,
Gini coe icien o economic inequali y), we also p opose a new indica o and g ouping
middle-income coun ies by hei p og ess in echnological de elopmen . To ha end, we
applied he concep o echnology li ecycle o gene a e each coun y’s sigmoid knowledge
accumula ion, d awing on he numbe o pa en s and compu ed he in lec ion poin s o
hei S cu es i ed by logis ic unc ions.
Ou esea ch showed ha , while mos coun ies displayed s able e iciency le els,
China and India expe ienced e iciency luc ua ions associa ed wi h he pandemic and
Economies 2024,12, 314 3 o 27
in e nal poli ical aspec s. The analysis unco e ed co ela ions be ween FDI pe o mance
and echnological de elopmen and economic inequali y. These indings sugges ha
ad ancemen s in echnology and economic equi y a e c i ical in enhancing FDI e iciency
in middle-income coun ies.
The emaining sec ions a e o ganized as ollows. Sec ion 2de ails a li e a u e su ey
and p esen s ou esea ch hypo heses. Sec ion 3desc ibes ou me hods wi h a ocus on
DEA. Sec ion 4p o ides ou analysis esul s including he hypo hesis es ing. Sec ion 5
discusses ou empi ical esul s in ela ion o he ex an li e a u e. Sec ion 6concludes his
s udy along wi h u u e ex ensions.
2. Li e a u e Re iew and Hypo hesis De elopmen
2.1. Theo e ical F amewo k o FDI Pe o mance Analysis
The analysis o FDI pe o mance in middle-income coun ies si s a he in e sec ion
o h ee heo e ical s eams: e iciency measu emen heo y, echnology ans e heo y,
and economic de elopmen heo y. Da a en elopmen analysis has eme ged as a powe ul
me hodological amewo k o e alua ing complex economic sys ems whe e mul iple
inpu s p oduce mul iple ou pu s (Cha nes e al. 1978). Wi hin he con ex o FDI, his
app oach enables us o simul aneously conside bo h he di ec economic impac s and
indi ec spillo e e ec s ha cha ac e ize o eign in es men in manu ac u ing sec o s.
2.2. E olu ion o DEA Applica ions in Economic Pe o mance Assessmen
The applica ion o DEA o na ional and sub-na ional pe o mance assessmen s has
e ol ed signi ican ly o e he pas decades. Ea ly applica ions ocused p ima ily on
echnical e iciency in speci ic sec o s (Zaim 2004), bu ecen s udies ha e expanded o
inco po a e b oade economic and en i onmen al conside a ions (Sueyoshi and Ryu 2021).
These me hodological ad ances ha e pa icula ele ance o analyzing FDI pe o mance
in middle-income coun ies, whe e he in e play be ween economic g ow h and en i on-
men al impac emains a c i ical conce n.
Table 1summa izes hose s udies along wi h he speci ic me hodologies and inpu and
ou pu ac o s used by hem. In e ms o economic de elopmen pe o mance, o ins ance,
San ana e al. (2017) ook BRICS coun ies as an example o assess he le el o sus ainable
de elopmen ac oss he iple bo om line: economic, en i onmen al, and social aspec s.
Fang e al. (2013) conside ed employmen , in es men , consump ion, and o he ac o s o
e alua e he economic de elopmen e iciency o Chinese u ban agglome a ions.
Ano he ield o mac oeconomic esea ch has cen e ed on ene gy and pollu ion is-
sues. Fo example, Ma sumo o e al. (2020) explo ed he Eu opean Union’s coun y-le el
da a om 2000 o 2018 and e ealed ha he 2007–2009 inancial c isis had a nega i e
impac on en i onmen al pe o mance. Sueyoshi and Ryu (2021) e alua ed he sus ainable
de elopmen pe o mance o he 50 U.S. s a es and examined he ela ionship be ween
s a e-le el en i onmen al pe o mance measu es and hei poli ical and geog aphical con-
ex s. Zaim (2004) s udied he s a e-le el pe o mance o ai pollu ion s emming om he
manu ac u ing sec o s in he Uni ed S a es.
Al hough ew DEA s udies ha e ocused on FDI, he exis ing esea ch o e s di e se
pe spec i es. Lei e al. (2013) assessed he pe o mance o Chinese p o inces in a ac ing
o eign in es men . Zhang (2017) ocused on he echnological spillo e e ec caused by
he in low o FDI, which u he led o he imp o emen o p oduc i i y. Recen ly, Wanke
e al. (2024) in es iga ed he d i e s o FDI pe o mance, om an employmen pe spec i e,
in many coun ies a ound he wo ld.
Economies 2024,12, 314 4 o 27
Table 1. Da a en elopmen analysis applica ions o o eign di ec in es men .
S udy Summa y Inpu s Ou pu s
San ana e al. (2017)
This s udy used he BCC model o
e alua e he sus ainable
de elopmen pe o mance o BRICS
coun ies om h ee aspec s: he
economy, en i onmen , and socie y.
G oss ixed capi al o ma ion,
employed popula ion, R&D
expendi u e, g oss ixed capi al
o ma ion, R&D expendi u e,
g oss ixed capi al o ma ion,
employed popula ion,
R&D expendi u e
GDP, CO2emission,
li e expec ancy
Lei e al. (2013)
This pape es ablished a model o
assess he a ac i eness o o eign
di ec in es men a he p o incial
le el in China based on da a om
1997 o 2008.
Ma e ial capi al, human capi al,
ene gy, deg ee o openness
FDI pe o mance index, FDI
po en ial index
Ma sumo o e al. (2020)
This s udy assessed he
economic–ene gy–en i onmen al
pe o mance o EU coun ies based
on da a om 2000 o 2017.
Labo , capi al,
ene gy consump ion
GDP, CO2emissions, PM2.5
emissions, was e
Zhang (2017)
The pape ocused on he
echnological spillo e e ec caused
by he in low o FDI, which u he
led o he imp o emen
o p oduc i i y.
Numbe o esea che s, R&D
s ock, sha e o basic esea ch
expenses, sha e o expe imen al
esea ch expenses, FDI s ock
In en ion pa en s, u ili y
model, design pa en
Fang e al. (2013)
This s udy combined DEA wi h
mac oeconomics o s udy he
inpu –ou pu e iciency o China’s
u ban agglome a ions om a
comp ehensi e pe spec i e.
To al numbe o employees, ne
in es men in ixed asse s,
buil -up a ea
GDP, o al e ail sales in
social consume goods
Sueyoshi e al. (2021)
This s udy analyzed s a e-le el
en i onmen al pe o mance in
di e en poli ical and geog aphical
con ex s by employing
en i onmen al assessmen -o ien ed
DEA models.
Popula ion, go e nmen
expendi u e, ene gy
consump ion, pa en g an s
G oss s a e p oduc and
ca bon emissions
Zaim (2004)
Based on he idea ha pollu ion is a
majo byp oduc o manu ac u ing
ac i i y, his s udy measu ed and
compa ed manu ac u ing ou pu
and pollu ion ac oss U.S. s a es.
Manu ac u ing employmen ,
capi al s ock
G oss s a e p oduc in
manu ac u ing, SOx,
NOx, CO
Wanke e al. (2024)
This s udy used a no el RoCo
MCDM model o s udy he
pe o mance d i e s o o eign
di ec in es men in coun ies
a ound he wo ld.
Capi al expendi u es, FDI
amoun , incen i e pe job,
incen i e pe
capi al expendi u e
New jobs, sa egua ded jobs,
a e age sala y
2.3. Technological De elopmen and FDI Pe o mance
The e is subs an ial e idence ha many middle-income coun ies ha e s agna ed, un-
able o ansi ion o a high-income s a us (Eicheng een e al. 2013;P uchnik and Zowczak
2017). The key easons o his middle-income ap include insu icien in es men , inade-
qua e in eg a ion o new echnologies, and a lack o inno a ion (Felipe 2012). Acco ding
o he p oduc ion unc ion, highe echnological le els allow o g ea e ou pu wi h he
same le els o labo and capi al (Be na des and e Albuque que 2003). This enables de el-
oped coun ies o achie e sus ainable de elopmen h ough in es ing in echnology and
ans o ming p oduc ion. Howe e , de eloping coun ies equi e ex e nal assis ance o
accele a e he p ocess o echnology accumula ion o a oid he middle-income ap and
Economies 2024,12, 314 5 o 27
achie e sus ainable de elopmen . Bo h he P oduc Li e Cycle Theo y and he Technology
Di usion Theo y suppo he possibili y o accele a ing echnological de elopmen (Mi-
cho owska 2008). In es men is c ucial o os e ing echnological de elopmen , which in
u n enables indus ies—especially in he manu ac u ing sec o — o e ec i ely abso b and
u ilize new echnologies, he eby con ibu ing o economic e iciency and g ow h. Howe e ,
when he in eg a ion o hese echnologies (i.e., in usion) is incomple e o ine icien , coun-
ies s uggle o achie e he inno a ion-d i en g ow h needed o escape he middle-income
ap (Suh e al. 2010).
In his ein, many s udies ha e ound ha one o he key bene i s ha FDI b ings o
hos coun ies is he ans e and spillo e o echnology. These echnologies can ei he
be in en ionally ans e ed h ough o mal ag eemen s, such as pa ne ships o licensing,
o hey can indi ec ly spill o e o he local i ms h ough he in e ac ions wi h o eign
companies, wo k o ce aining, o exposu e o ad anced echnologies. Ma asco e al.
(2024) showed ha high- ech FDI has a s ong posi i e co ela ion wi h hos coun y
g ow h, especially in he manu ac u ing indus y. The main media ing ac o was whe he
he o eign capi al has echnology ha can p omo e p oduc i i y, leading o long- e m
economic g ow h. The wo k o Wang (2010) and Filla and Woe z (2011) suppo ed a
posi i e ela ionship be ween FDI and p oduc i i y, pa icula ly when high in es men
is combined wi h expo o ien a ion. Damijan e al. (2003) ocused on he c i ical ole
o echnology ans e in p oduc i i y imp o emen . In pa icula , o middle-income
coun ies, Tampakoudis e al. (2017) concluded ha a ac ing mo e FDI helps o a oid
alling in o he middle-income ap.
Meanwhile, some s udies ha e also no ed he challenges o in e nalizing and abso bing
echnology induced by FDI while o he s shed ligh on he ela ionship be ween a ious
de e minan s in economic g ow h. Mingyong e al. (2006) a gued ha enhancing abso p i e
capabili y and human capi al s ocks can con ibu e o long- e m economic g ow h. A jun
e al. (2020) ocused on manu ac u ing alue-added p oduc s along wi h he ole o ene gy,
human capi al, inance, and echnology. Razzaq e al. (2021) indica ed ha ela i ely
unde de eloped coun ies ind i di icul o in e nalize FDI spillo e s. Alna ah (2021)
emphasized in his s udy ha comme cializing knowledge ou pu s is a challenge aced
by BRICS coun ies. Radose ic and Yo uk (2018)’s s udy on middle-income coun ies
indica ed ha FDI o e s limi ed bene i s o coun ies whe e ac o s like human capi al and
ins i u ions all below ce ain h esholds.
As a measu e o e alua e echnology de elopmen , pa en da a ha e been used since
pa en s a e iled and g an ed o p o ec esea ch and de elopmen ou pu s unde an
in ellec ual p ope y igh egime. Chen e al. (2013), o ins ance, analyzed he uel cell
echnology de elopmen o leading coun ies using pa en da a. Fu he , Tampubolon
and Ramlogan (2004) employed pa en analysis o iden i y he coun y-le el echnological
change pa e ns in Eas Asia and Sou h Ame ica. In pa icula , hey used he non-linea
sigmoid echnology li ecycle concep , o en e e ed o as an S-cu e app oach.
In his ega d, we sough o explo e i he e is a signi ican di e ence in FDI pe o -
mance be ween wo g oups o middle-income coun ies: one a a leading posi ion in he
pa en S cu e and he o he a a lagging posi ion in he cu e.
Hypo hesis 1. The e is a signi ican di e ence in FDI pe o mance be ween middle-income
coun ies ha achie ed di e en le els o echnological de elopmen .
H1a. Coun ies ha ha e passed hei echnology li ecycle in lec ion poin by 2022 will demons a e
signi ican ly di e en FDI pe o mances compa ed o hose ha ha e no .
The 2022 benchma k p o ides a con empo a y snapsho o echnological de elopmen ,
e lec ing ecen ad ances in digi al ans o ma ion and Indus y 4.0 capabili ies. This
hypo hesis builds on Radose ic and Yo uk (2018)’s inding ha echnological capabili ies
signi ican ly in luence FDI bene i s in middle-income coun ies.
Economies 2024,12, 314 6 o 27
H1b. Coun ies abo e he median in lec ion poin in hei echnology li ecycle cu es will show
signi ican ly di e en FDI pe o mances compa ed o hose below he median.
This al e na i e hypo hesis accoun s o he ela i e posi ioning o coun ies in hei ech-
nological de elopmen ajec o ies, ollowing Lee’s (2013) a gumen ha ela i e echnological
capabili ies ma e mo e han absolu e le els in de e mining de elopmen ou comes.
2.4. Economic Inequali y and FDI Dynamics
The ela ionship be ween FDI and economic inequali y p esen s a complex pic u e
ha has e ol ed o e ime. Ea ly s udies sugges ed a s aigh o wa d ela ionship be ween
FDI and inequali y (Cla k e al. 2011), bu ecen esea ch e eals a mo e nuanced dynamic.
Kaulihowa and Adjasi (2018) iden i ied a U-shaped ela ionship be ween FDI and inequali y
in de eloping economies, sugges ing ha ini ial inc eases in inequali y may e en ually
e e se as bene i s di use h ough he economy.
This empo al dimension o FDI’s impac on inequali y becomes pa icula ly ele an
o middle-income coun ies, whe e domes ic ma ke de elopmen and ins i u ional capac-
i y play c ucial media ing oles. Ucal e al. (2016) sugges ed ha FDI has a nega i e impac
on he Gini coe icien based on Tu kish da a, meaning inequali y educ ion. In con as ,
Cla k e al. (2011) indica ed ha FDI gene ally inc eases economic inequali y. Majeed (2017),
who esea ched de eloping coun ies, a gued ha he impac o FDI a ies ac oss na ions.
FDI ends o educe inequali y in coun ies wi h a high le el o economic de elopmen ,
while in hose wi h a low le el o economic de elopmen , i ends o exace ba e inequali y.
Some o he s udies p o ided mo e nuanced ends. He ze and Nunnenkamp (2011),
ocusing on Eu opean coun ies, ound ha FDI has a posi i e impac on inequali y in he
sho e m bu a nega i e one in he long e m. Addi ionally, hey sugges ed a mu ual
causali y, whe e a educ ion in inequali y can also lead o inc eased FDI. Kaulihowa and
Adjasi (2018), examining he ela ionship be ween FDI and inequali y in A ica, desc ibed
i as a U-shaped cu e. FDI can inc ease inequali y in he ea ly s ages, bu inequali y ends
o dec ease as he bene i s o FDI become mo e widely dis ibu ed o e ime. Deng and Lin
(2012) s udied FDI based on income classi ica ion and ound ha FDI educes inequali y in
low-income coun ies wi h poo human capi al bu exace ba es inequali y in middle- and
high-income coun ies wi h abundan human capi al.
In his ein, we sough o in es iga e i he e is a signi ican di e ence in FDI pe o -
mance be ween wo g oups o coun ies: one wi h highe economic inequali y and ano he
wi h lowe economic inequali y.
Hypo hesis 2. The e is a signi ican di e ence in FDI pe o mance be ween middle-income
coun ies based on hei le els o economic inequali y.
H2a. Coun ies wi h highe Gini coe icien s will demons a e signi ican ly di e en FDI pe o -
mances compa ed o hose wi h lowe inequali y le els.
This hypo hesis builds on Wade (2020)’s a gumen ha inequali y a ec s he ins i u-
ional and social condi ions ha in luence FDI abso p ion capaci y. The Gini coe icien
p o ides a comp ehensi e measu e o income dis ibu ion ha cap u es bo h op-end and
bo om-end inequali ies.
H2b. Coun ies wi h highe po e y headcoun a ios a USD 3.65 a day will show signi ican ly
di e en FDI pe o mances compa ed o hose wi h lowe po e y le els.
This hypo hesis ocuses on bo om-end inequali y, ollowing Ra allion (2014)’s empha-
sis on po e y as a c ucial cons ain on de elopmen capabili ies. The USD 3.65 h eshold
speci ically cap u es ulne abili y in middle-income coun ies.
Economies 2024,12, 314 7 o 27
2.5. Global Pandemic and FDI Resilience
Some diseases ha e ansi ioned in o an epidemic o pandemic and ha e become a
na ional o global issue and ha e w ough ha oc in he in e na ional economy. Fo ins ance,
Omoleke e al. (2016) ook he example o Ebola Vi al Disease in Wes A ica and p esen ed
i s economic ami ica ions including a lowe a ailabili y o labo , es ic ions in business
ansac ions, and dis up ions in supply chains. Joo e al. (2019) looked in o he economic
consequences o a Middle Eas espi a o y synd ome (MERS) ou b eak in Sou h Ko ea, wi h
a ocus on he ou ism indus y. Sueyoshi e al. (2021) explo ed he ela ionships be ween
OECD coun ies’ COVID-19 esponse pe o mance and hei socioeconomic sys ems, wi h
a ocus on he anspo a ion and ene gy sec o s.
The COVID-19 pandemic has p o ided a unique na u al expe imen o examining he
esilience o FDI sys ems. P e ious esea ch on epidemic impac s (Joo e al. 2019) ocused
p ima ily on egional e ec s, bu he global na u e o COVID-19 allows us o examine
sys emic esponses ac oss mul iple economies simul aneously.
Since he COVID-19 became a pandemic in 2020, in es men ac i i ies ha e cooled
down. Ajide and Osinubi (2020), based on global da a, ound a posi i e co ela ion be ween
COVID-19 cases and dea hs and FDI ou lows. The p ima y easons we e he decline in
in es men due o ising inancing cos s and dec easing p o i s, as well as conce ns abou
employee heal h and sa e y. Ho and Gan (2021) demons a ed he nega i e impac s o
global heal h issues on FDI, pa icula ly FDI ne in lows in Asia-Paci ic coun ies and
eme ging economies. Fu e al. (2021) also concluded ha he impac o he pandemic
on FDI lies in educed p o i ma gins, a ec ing hos coun ies. In pa icula , he se ice
sec o ’s FDI was se e ely impac ed by he pandemic.
In such a backg ound, we sough o examine i he e we e any signi ican changes in
FDI pe o mance in middle-income coun ies o e ime, speci ically be o e and a e he
COVID-19 pandemic.
Hypo hesis 3. The e is a signi ican di e ence in FDI pe o mance be ween middle-income
coun ies be o e and a e he pandemic.
H3a. FDI pe o mance will show signi ican di e ences be ween he p e-pandemic (2015–2018)
and pos -pandemic (2019–2022) pe iods.
This hypo hesis d aws on Kogu and Singh (1988)’s concep o coun y isk assessmen
in FDI decisions, sugges ing ha pandemic expe iences may undamen ally al e isk
pe cep ions and in es men e iciency pa e ns.
H3b. FDI pe o mance will show signi ican di e ences du ing he acu e pandemic pe iod
(2020–2022)
compa ed o he p e-pandemic pe iod.
This hypo hesis ocuses on immedia e pandemic impac s, ollowing Con ac o (2022)’s
a gumen ha c isis pe iods can e eal unde lying s eng hs and weaknesses in in e na-
ional business sys ems.
3. Me hodology
3.1. Analy ic F amewo k
This s udy employed DEA wi h ansla ion in a iance a he i s s age and conduc ed
a se ies o K uskal–Wallis es s a he second s age o e i y ou esea ch hypo heses. As
shown in Figu e 1, we compu ed h ee ypes o e iciency sco es: he i s one unde con-
s an e u ns o scale, he second one unde a iable e u ns o scale, and he las one
wi h scale. Then, we applied K uskal–Wallis es s o examine he s a is ical di e ences
among a ious g oups o coun ies in di e en yea s depending on hei le els o ech-
nological de elopmen and economic inequali y, and on he dynamic changes in public
heal h conce ns.
Economies 2024,12, 314 8 o 27
Economies 2024, 12, x FOR PEER REVIEW 8 o 29
wi h scale. Then, we applied K uskal–Wallis es s o examine he s a is ical diffe ences
among a ious g oups o coun ies in diffe en yea s depending on hei le els o echno-
logical de elopmen and economic inequali y, and on he dynamic changes in public
heal h conce ns.
Figu e 1. Two s ages o analysis.
3.2. Da a
This s udy selec ed da a om 2015 o 2022 om en ypical manu ac u ing hos coun-
ies: B azil, China, India, Indonesia, Malaysia, Mexico, he Philippines, Thailand, and Vi-
e nam. The da a sou ces we e he Wo ld Bank Da abase, Wo ld In ellec ual P ope y O -
ganiza ion, Emissions Da abase o Global A mosphe ic Resea ch (EDGAR), and Ene gy
Ins i u e. See Appendix A o he aw da a.
The selec ed coun ies we e chosen based on mul iple conside a ions. Fi s ly, China,
India, and B azil a e among he majo coun ies ha a ac he mos FDI and ank in he
op h ee on he GMCI index o Compe i i eness in Fi e Yea s (Deloi e. n.d.). We also
ocused on smalle eme ging coun ies like Vie nam, Thailand, and he Philippines, which
ha e seen a ying deg ees o g ow h in manu ac u ing FDI. F om he OECD epo and
he UNCTAD in es men epo (UNCTAD 2020), we can ind da a suppo ing Malaysia
and Indonesia as manu ac u ing hubs in Sou heas Asia. Addi ionally, Mexico, as pa o
he No h Ame ican F ee T ade Ag eemen (NAFTA), has a ac ed subs an ial manu ac-
u ing FDI om No h Ame ica.
In ou DEA model, we used ou inpu s and ou ou pu s. The o me includes he
ne in low o FDI, g oss capi al o ma ion, popula ion, and p ima y ene gy consump ion
while he la e includes manu ac u ing alue added, GDP, numbe o pa en s, and g een-
house gas (GHG) emissions. Since he emission o GHGs, as byp oduc s o ou p oduc ion
p ocess, is an undesi able ou pu , i was ans e ed o he inpu side o calcula ion.
Ou selec ion o inpu and ou pu a iables ollowed a comp ehensi e amewo k
ha cap u es bo h he di ec and indi ec impac s o FDI on hos economies. The inpu
a iables e lec bo h he in es men channels and he s uc u al capaci y o hos econo-
mies, while he ou pu a iables cap u e he economic, echnological, and en i onmen al
dimensions o de elopmen ou comes.
Figu e 1. Two s ages o analysis.
3.2. Da a
This s udy selec ed da a om 2015 o 2022 om en ypical manu ac u ing hos
coun ies: B azil, China, India, Indonesia, Malaysia, Mexico, he Philippines, Thailand, and
Vie nam. The da a sou ces we e he Wo ld Bank Da abase, Wo ld In ellec ual P ope y
O ganiza ion, Emissions Da abase o Global A mosphe ic Resea ch (EDGAR), and Ene gy
Ins i u e. See Appendix A o he aw da a.
The selec ed coun ies we e chosen based on mul iple conside a ions. Fi s ly, China,
India, and B azil a e among he majo coun ies ha a ac he mos FDI and ank in he
op h ee on he GMCI index o Compe i i eness in Fi e Yea s (Deloi e 2013). We also
ocused on smalle eme ging coun ies like Vie nam, Thailand, and he Philippines, which
ha e seen a ying deg ees o g ow h in manu ac u ing FDI. F om he OECD epo and he
UNCTAD in es men epo (UNCTAD 2020), we can ind da a suppo ing Malaysia and
Indonesia as manu ac u ing hubs in Sou heas Asia. Addi ionally, Mexico, as pa o he
No h Ame ican F ee T ade Ag eemen (NAFTA), has a ac ed subs an ial manu ac u ing
FDI om No h Ame ica.
In ou DEA model, we used ou inpu s and ou ou pu s. The o me includes he ne
in low o FDI, g oss capi al o ma ion, popula ion, and p ima y ene gy consump ion while
he la e includes manu ac u ing alue added, GDP, numbe o pa en s, and g eenhouse
gas (GHG) emissions. Since he emission o GHGs, as byp oduc s o ou p oduc ion p ocess,
is an undesi able ou pu , i was ans e ed o he inpu side o calcula ion.
Ou selec ion o inpu and ou pu a iables ollowed a comp ehensi e amewo k ha
cap u es bo h he di ec and indi ec impac s o FDI on hos economies. The inpu a iables
e lec bo h he in es men channels and he s uc u al capaci y o hos economies, while
he ou pu a iables cap u e he economic, echnological, and en i onmen al dimensions
o de elopmen ou comes.
Fo inpu a iables, we inco po a ed FDI ne in lows as ou p ima y measu e o
o eign in es men ac i i y, ollowing he es ablished app oach o Wanke e al. (2024). G oss
capi al o ma ion se ed as a complemen a y inpu ha cap u es domes ic in es men
capaci y, which He ze and Nunnenkamp (2011) iden i ied as c ucial o FDI abso p ion.
Popula ion size, as was employed by Sueyoshi and Ryu (2021), ep esen s he human
Economies 2024,12, 314 15 o 27
Table 5. Scale e iciency.
Coun y 2015 2016 2017 2018 2019 2020 2021 2022
Bangladesh 0.984 0.986 0.988 0.990 0.992 0.994 0.997 1.000
B azil 0.999 1.000 1.000 0.999 0.999 1.000 0.997 0.998
China 0.895 1.000 1.000 1.000 1.000 1.000 0.938 1.000
India 1.000 1.000 0.943 0.990 0.976 0.987 0.874 0.855
Indonesia 0.983 1.000 1.000 0.999 1.000 1.000 1.000 0.987
Malaysia 1.000 1.000 0.999 1.000 1.000 1.000 0.996 1.000
Mexico 1.000 0.995 1.000 1.000 1.000 1.000 1.000 1.000
Philippines 0.993 0.993 0.993 0.994 0.993 1.000 0.992 0.993
Thailand 0.999 1.000 1.000 1.000 1.000 1.000 0.999 0.999
Vie nam 0.994 0.995 0.996 0.998 0.999 0.999 0.998 0.999
Economies 2024, 12, x FOR PEER REVIEW 15 o 29
Table 5. Scale efficiency.
Coun y 2015 2016 2017 2018 2019 2020 2021 2022
Bangladesh 0.984 0.986 0.988 0.990 0.992 0.994 0.997 1.000
B azil 0.999 1.000 1.000 0.999 0.999 1.000 0.997 0.998
China 0.895 1.000 1.000 1.000 1.000 1.000 0.938 1.000
India 1.000 1.000 0.943 0.990 0.976 0.987 0.874 0.855
Indonesia 0.983 1.000 1.000 0.999 1.000 1.000 1.000 0.987
Malaysia 1.000 1.000 0.999 1.000 1.000 1.000 0.996 1.000
Mexico 1.000 0.995 1.000 1.000 1.000 1.000 1.000 1.000
Philippines 0.993 0.993 0.993 0.994 0.993 1.000 0.992 0.993
Thailand 0.999 1.000 1.000 1.000 1.000 1.000 0.999 0.999
Vie nam 0.994 0.995 0.996 0.998 0.999 0.999 0.998 0.999
Figu e 4. Scale efficiency.
Compa ed o he CRS model, he VRS model was be e able o cap u e scale- ela ed
changes. Fluc ua ions can ha e diffe en impac s on economies o a ying scales. La ge
economies ind i mo e difficul o consis en ly emain a a good scale efficiency. When i
comes o mac oeconomics, luc ua ions in scale efficiency o diseconomies o scale may
s em om he ollowing: s uc u al economic changes caused by poli ical in e en ions;
ma ke economic ac i i ies, such as ma ke expansion and indus ial upg ading; and scale
inefficiencies in pa icula sec o s ha sp ead, leading o poo o e all scale efficiency in
he economy.
4.1.4. Resul Analysis
Table 6 p esen s he a e age and s anda d de ia ion alues o he wo ope a ional
efficiency sco es and scale efficiency sco es o he en coun ies. The a ying pa e ns ob-
se ed unde he CRS and VRS models e eal impo an insigh s in o he na u e o FDI
efficiency in diffe en economic con ex s. While he a e age efficiency sco es showed
Figu e 4. Scale e iciency.
4.1.4. Resul Analysis
Table 6p esen s he a e age and s anda d de ia ion alues o he wo ope a ional
e iciency sco es and scale e iciency sco es o he en coun ies. The a ying pa e ns
obse ed unde he CRS and VRS models e eal impo an insigh s in o he na u e o FDI
e iciency in di e en economic con ex s. While he a e age e iciency sco es showed b oad
simila i ies ac oss bo h models, se e al coun ies, pa icula ly India, exhibi ed no able
di e ences ha me i ca e ul examina ion.
The CRS model, which assumes a linea ela ionship be ween inpu s and ou pu s
ega dless o ope a ional scale, showed India main aining he lowes a e age e iciency
(0.879) wi h he highes ola ili y (s anda d de ia ion o 0.0502). Howe e , unde he VRS
model, which accoun s o scale-dependen a ia ions in e iciency, India demons a ed
a ma kedly di e en pa e n, which was pa icula ly e iden in i s pos -2021 eco e y
( ising om 0.857 in 2020 o 1.000 in 2022). This di e gence be ween he CRS and VRS
esul s sugges s ha India’s FDI e iciency is signi ican ly in luenced by scale e ec s, a
inding consis en wi h Banke e al. (1984)’s heo e ical amewo k on scale-dependen
e iciency measu emen s.
Economies 2024,12, 314 16 o 27
Table 6. Desc ip i e s a is ics o DEA esul s.
Coun y CRS—A e age CRS—Sd VRS—A e age VRS—Sd SE—A e age SE—Sd
Bangladesh 0.991 0.0055 1.000 0.0005 0.991 0.0055
B azil 0.993 0.0064 0.994 0.0054 0.999 0.0011
China 0.969 0.0386 0.990 0.0183 0.979 0.0403
India 0.879 0.0502 0.925 0.0573 0.953 0.0578
Indonesia 0.986 0.0149 0.989 0.0112 0.996 0.0068
Malaysia 0.999 0.0021 0.999 0.0018 0.999 0.0014
Mexico 0.997 0.0034 0.998 0.0035 0.999 0.0018
Philippines 0.993 0.0031 0.999 0.0013 0.994 0.0025
Thailand 0.994 0.0032 0.994 0.0029 1.000 0.0005
Vie nam 0.984 0.0005 0.987 0.0025 0.997 0.0020
The scale e iciency analysis u he illumina ed hese di e ences. Thailand achie ed
op imal scale e iciency (1.000), indica ing ha i s ope a ional scale aligns well wi h i s
echnological capabili ies. In con as , India’s lowe scale e iciency (0.953) sugges s ha i s
FDI ope a ions may be ope a ing a a subop imal scale. This pa e n aligns wi h Ray and
Das (2010)’s indings on scale e ec s in eme ging economies, whe e apid g ow h can lead
o empo a y misma ches be ween ope a ional scale and echnical e iciency.
La ge economies like China and India showed mo e p onounced luc ua ions in bo h
models, bu wi h di e en pa e ns. China’s e iciency sco es demons a ed g ea e s abili y
unde VRS (a e age 0.990) compa ed o CRS (a e age 0.969), sugges ing ha when scale
e ec s a e conside ed, i s FDI u iliza ion appea s mo e e icien . This inding esona es wi h
Ma gono and Sha ma (2006)’s obse a ions abou scale economies in la ge manu ac u ing
sec o s, whe e he bene i s o scale can pa ially o se o he ine iciencies.
The di e ing pa e ns be ween he CRS and VRS esul s can be a ibu ed o se e al
ac o s. Fi s , he VRS model’s abili y o accoun o scale-dependen e iciencies is pa icu-
la ly ele an o economies expe iencing apid s uc u al changes. Fo ins ance, India’s
imp o ed pe o mance unde VRS pos -2021 sugges s ha i s FDI e iciency gains we e
pa ly masked by scale- ela ed ac o s in he CRS model.
Second, coun ies wi h mo e s able e iciency sco es ac oss bo h models (such as
Malaysia and Thailand) likely ope a e a scales close o hei op imal e iciency on ie s.
This s abili y indica es ha hei FDI ope a ions ha e achie ed a be e alignmen be ween
scale and echnical e iciency, consis en wi h Tone and Tsu sui (2014)’s indings on e iciency
s abili y in ma u e manu ac u ing economies.
Thi d, he empo al pa e ns in bo h models e eal how ex e nal shocks, such as
he COVID-19 pandemic, a ec e iciency h ough di e en channels. The VRS model’s
esul s sugges ha some e iciency losses a ibu ed o scale e ec s in he CRS model
we e ac ually due o empo a y dis up ions in ope a ional scale a he han undamen al
e iciency declines.
4.2. Technology Li ecycles o Ten Middle-Income Coun ies
Table 7desc ibes he h ee pa ame e s o he en coun ies’ S cu es i ed by Model
(11) as well as hei R
2
alues o he goodness o i and o he simple s a is ics. On a e age,
he sa u a ion le el was expec ed o be app oxima ely 6 million pa en s while he maximum
g ow h a e was es ima ed o be 5.6%. China su passed o he coun ies in he sa u a ion
le el and maximum g ow h a e. The mean o he in lec ion poin s was p edic ed o be
he yea 2062. As o 2024, only h ee coun ies (Bangladesh, B azil, and China) passed
he in lec ion poin s o hei S cu es. The R
2
alues we e ela i ely high, all o which
we e g ea e han 96%, implying ha Model (11) i he da a well. See Appendix B o he
10 coun ies’ S cu es based on he numbe o accumula ed pa en s (ac ual and i ed by
logis ic unc ion cu es) o e ime.
Economies 2024,12, 314 17 o 27
Table 7. Desc ip i e s a is ics o en coun ies’ S cu es.
Coun y
Sa u a ion Le el
Max. G ow h Ra e In lec ion Yea R-Squa ed Value
Bangladesh 2815 0.041 2011 0.996
B azil 242,473 0.041 2016 1.000
China 20,701,734 0.138 2019 1.000
Indonesia 197,172 0.072 2037 0.993
India 6,809,312 0.054 2052 0.999
Mexico 3,852,296 0.024 2121 0.997
Malaysia 6,136,042 0.047 2080 0.978
Philippines 5,202,870 0.033 2118 0.991
Thailand 7,729,580 0.041 2092 0.963
Vie nam 9,490,702 0.065 2074 0.998
Mean 6,036,500 0.056 2062 0.992
Max. 20,701,734 0.138 2121 1.000
Min. 2815 0.024 2011 0.963
SD 6,146,488 0.032 41 0.012
In addi ion o echnology ad ances ( e lec ed by an inc ease in he numbe o pa en s)
as an ou pu , his s udy used manu ac u ing alue added as ano he ou pu . Technological
ad ancemen s can shi manu ac u ing om low alue added o high alue added. Supe-
io echnology clea ly aids decision-making uni s in achie ing highe e iciency sco es.
Acco ding o he Wo ld In es men Repo 2019, he in low o echnology-in ensi e FDI
g ew signi ican ly, accoun ing o o e 40% o global FDI. Among hem, echnologically
ad anced economies like China a ac ed a subs an ial amoun o high- ech FDI, mainly
due o i s echnological and inno a ion capabili ies (UNCTAD 2019). China is a ypical ep-
esen a i e o he sus ainable cycle, whe e policies a ac FDI, echnological ad ancemen s,
manu ac u ing shi s o add highe alue, and economic g ow h.
4.3. Hypo hesis Tes ing
Nex , he h ee hypo heses along wi h he six sub-hypo heses we e es ed. Based
on he CRS and VRS sco es ob ained, we used a se ies o K uskal–Wallis es s ac oss he
di e en g oups o middle-income coun ies o es he di e en hypo heses. The es
esul s a e summa ized in Table 8.
Table 8. K uskal–Wallis es esul s.
Hypo hesis 1 Hypo hesis 2 Hypo hesis 3
H1a H1b H2a H2b H3a H3b
CRS
G oup 1 Mean 0.984 0.964 0.995 0.962 0.981 0.980
G oup 2 Mean 0.976 0.993 0.967 0.989 0.976 0.977
Chi-Squa ed S a is ic 0.095 7.973 18.069 7.965 0.023 0.327
p-Value 0.758 0.005 *** 0.000 *** 0.005 *** 0.880 0.567
VRS
G oup 1 Mean 0.995 0.979 0.997 0.978 0.988 0.986
G oup 2 Mean 0.984 0.995 0.981 0.994 0.987 0.990
Chi-Squa ed S a is ic 4.187 0.913 9.074 0.509 0.033 1.258
p-Value 0.041 ** 0.339 0.003 *** 0.476 0.856 0.262
SE
G oup 1 Mean 0.990 0.984 0.998 0.984 0.993 0.993
G oup 2 Mean 0.991 0.998 0.986 0.996 0.989 0.987
Chi-Squa ed S a is ic 0.280 2.824 3.382 16.601 0.021 0.010
p-Value 0.597 0.093 * 0.066 * 0.000 *** 0.884 0.921
No e: *** p< 0.01, ** p< 0.05, and * p< 0.1.
Hypo hesis 1 was conce ned wi h whe he he e was a signi ican di e ence in FDI pe -
o mance be ween middle-income coun ies ha achie ed di e en le els o echnological
de elopmen . When g ouping coun ies by he in lec ion poin s o hei cumula i e numbe
Economies 2024,12, 314 18 o 27
o pa en s-based S cu es, we used he yea 2022 as he di ide and o med wo g oups
(H1a). G oup 1 included Bangladesh, B azil, and China, while g oup 2 included Indonesia,
India, Mexico, Malaysia, he Philippines, Thailand, and Vie nam. The sub-hypo hesis was
suppo ed a he 5% signi icance le el in he VRS model. When g ouping coun ies by
he median in lec ion poin o hei S cu es (H1b), wo g oups we e o med. G oup 1
included Bangladesh, B azil, China, Indonesia, and India, while g oup 2 included Mexico,
Malaysia, he Philippines, Thailand, and Vie nam. This sub-hypo hesis was suppo ed a
he 1% signi icance in he CRS model and a he 10% signi icance le el o SE.
Hypo hesis 2 was conce ned wi h whe he he e was a signi ican di e ence in FDI
pe o mance be ween middle-income coun ies ha achie ed di e en le els o economic
inequali y. When g ouping coun ies by hei Gini coe icien (H2a), wo g oups we e
o med. G oup 1 wi h a Gini coe icien abo e 0.4 included B azil, Malaysia, Mexico, and
he Philippines, while g oup 2 wi h a Gini coe icien below 0.4 included Bangladesh,
China, Indonesia, India, Thailand, and Vie nam. The sub-hypo hesis was suppo ed in
bo h he CRS and VRS models a he 1% signi icance le el and a he 10% le el o SE.
When e alua ing economic inequali y using a po e y headcoun a io o USD 3.65 a day
(H2b), wo g oups we e o med. G oup 1 wi h a a io abo e 10% included Bangladesh,
India, Indonesia, and he Philippines, while g oup 2 wi h a a io below 10% included B azil,
China, Malaysia, Thailand, and Vie nam. This sub-hypo hesis was suppo ed a he 1%
signi icance le el in he CRS model and a 1% o SE.
Hypo hesis 3 was conce ned wi h whe he he e was a signi ican di e ence in FDI
pe o mance be ween middle-income coun ies be o e and a e he COVID-19 pandemic.
The g oups o es ing H3a we e di ided in o wo ime windows: 2015–2018 and 2019–2022,
spli equally by ime. The g oups o es ing H3b we e di ided in o ano he wo ime
windows, 2015–2019 and 2020–2022, wi h a ime lag be ween he occu ence o he global
pandemic and ealized economic consequences. Bo h sub-hypo heses we e no signi ican
in ei he he CRS o VRS model.
5. Discussion
The DEA esul s showed se e al in e es ing poin s o discussion. Ou esul s ended
o show highe e iciency sco es han o he s udies. Wanke e al. (2024), o ins ance,
demons a ed FDI pe o mance sco es as low as 0.37 while ou sco es we e o e 0.85.
This signi ican di e ence s emmed p ima ily om he s udy sample and indus y sec o s.
Wanke e al. (2024) included no only de eloping coun ies bu also de eloped and unde -
de eloped ones, which d agged he pe o mance sco e down. Mo eo e , hey conside ed
o e all indus ies, including low- ech and low alue-added ones, which dec eased he
pe o mance sco e u he . In con as , ou s udy included an eli e g oup o middle-income
coun ies ha end o ecei e he bene i o subs an ial amoun s o FDI. Also, ou s udy
ocused on he manu ac u ing sec o , which ends o be high ech and high alue, so ou
pe o mance sco es we e ela i ely high.
Addi ionally, i is wo h adding mo e con ex o he pe o mance sco es o wo la ge
economies—China and India—conside ing hei signi ican con ibu ion o he global
economy. In he CRS model, 2015 s ood ou as an unusual yea o China, wi h an e iciency
sco e lowe han no mal. In ac , China’s economy expe ienced a slowdown in 2015,
d opping o below 7% o he i s ime since 1991 (Magnie 2016). In es o con idence
in he economic g ow h o China declined unde he backg ound o o e capaci y in he
manu ac u ing sec o (Xu and Liu 2018). In he CRS model, India’s e iciency sco es
o
2015–2016
we e highe han usual. India’s economy g ew apidly due o e o ms
implemen ed by he Modi go e nmen (Eche e i-Gen e al. 2021), su passing China o
become he as es -g owing majo economy (Bellman 2016). In gene al, sizable e en s
such as he shock o a pandemic wi h s ic lockdowns, economic ecessions, o e o ms
by a new go e nmen , which can impac he en i e economy, end o cause signi ican
luc ua ions in e iciency sco es. Miniscule e en s such as a empo a y inc ease in pollu ion,
Economies 2024,12, 314 19 o 27
mild pandemic con ainmen measu es, o sho - e m poli ical luc ua ions, which can only
a ec pa s o he economy, lead o a mode a e change in e iciency sco es.
China was he only coun y whose FDI e iciency pe o mance was signi ican ly
impac ed by he COVID-19 pandemic among he 10 middle-income coun ies. The man-
u ac u ing sec o was sluggish in 2020 due o he s ic ze o-COVID policy. The blow o
con idence om he pandemic con inued o keep consump ion, employmen , and he eal
es a e ma ke dep essed in 2021 (Qian 2023), esul ing in a d op in GDP g ow h o 3%
(Na ional Bu eau o S a is ics o China 2023). In SE, China and India, as la ge coun ies,
showed a need o u he adjus men s o achie e an op imal scale. This implies ha i may
be mo e challenging o la ge coun ies o sus ain an op imal scale.
The hypo hesis es esul s also o e ood o hough . The e ha e al eady been many
s udies indica ing ha he spillo e e ec s o FDI can p omo e echnological p og ess
in hos coun ies. This s udy also suppo s he ela ionship be ween FDI pe o mance
and echnological de elopmen . While mos ex an li e a u e used pa ame ic me hods
o examine he ela ionship be ween FDI, echnology, and o he ac o s, his s udy em-
ployed non-pa ame ic me hods o de i e e iciency sco es based on mul iple economic
ac o s and applied he echnology li ecycle concep o ake in o accoun he accumula i e
cha ac e is ics o echnological de elopmen .
Ano he aspec o he hypo hesis es ing esul s conce ned he ela ionship be ween
FDI pe o mance and economic inequali y. The cu en e idence o his ela ionship is
inconclusi e. Some s udies sugges ed ha FDI is associa ed wi h high inequali y, while
o he s a gued he opposi e. This s udy examined wo aspec s o economic inequali y:
he weal h gap and po e y. We o e a mo e ho ough unde s anding by analyzing he
simul aneous phenomena o a widening weal h gap and he educ ion in po e y. When
i comes o economic inequali y, bo h egional inequali y and income inequali y we e
conside ed. On he one hand, FDI ends o a o coas al and po ci ies, as well as he
ax- ee zones and ee ade a eas. While his may exace ba e egional inequali y (Wei
e al. 2009), i may be bene icial o o e all economic de elopmen as he mo e de eloped
egions can sp ead g ow h o less de eloped egions (Huang and Wei 2016). On he o he
hand, FDI business ac i i ies make business owne s weal hie . In ou li e a u e e iew,
some s udies ha acked long- e m changes in economic inequali y showed a dynamic
p ocess whe e inequali y i s widens and hen na ows (He ze and Nunnenkamp 2011;
Kaulihowa and Adjasi 2018). The coun ies we s udied a e de eloping na ions wi h middle
incomes, which a e s ill in he ea ly s ages o a dynamic shi , cha ac e ized by signi ican
economic inequali y. The u u e educ ion in economic inequali y may be d i en by
domes ic ein es men ha will bene i o he non-weal hy g oups and egions. Combining
he s a is ic esul s o hypo heses H2a and H2b, FDI was ound o ha e a po e y educ ion
e ec (Magombeyi and Odhiambo 2017), showing ha e en i he gap be ween he ich
and he poo widens, he poo es g oup will s ill bene i .
The insigni ican ela ionship be ween FDI pe o mance and he COVID-19 pandemic
in ou analysis p esen s an in iguing con as o s udies ocused on absolu e FDI lows.
While au ho s such as E ene (2020) and Fu e al. (2021) documen ed subs an ial declines
in global FDI olumes du ing he pandemic, ou e iciency-based analysis e eals a mo e
nuanced pic u e o FDI pe o mance du ing his pe iod.
Se e al ac o s help explain his pa adox. Fi s , he e iciency measu es in ou DEA
amewo k cap u e he ela ionship be ween inpu s and ou pu s a he han absolu e
alues. While bo h FDI in lows (inpu ) and manu ac u ing ou pu (ou pu ) declined
p opo ionally du ing he lockdowns, he e iciency sco es emained ela i ely s able. This
inding aligns wi h Kalo ay and Sass (2021)’s obse a ion ha manu ac u ing i ms adap ed
hei ope a ions o main ain p oduc i i y despi e he educed scale.
Second, he empo al pa e n o he pandemic impac s a ied signi ican ly ac oss
ou sample coun ies. China, o ins ance, expe ienced e iciency luc ua ions du ing i s
s ic ze o-COVID policy implemen a ion, which was pa icula ly e iden in he 2020–2021
pe iod. Howe e , o he coun ies in ou sample main ained ela i ely s able e iciency
Economies 2024,12, 314 20 o 27
sco es despi e expe iencing signi ican absolu e declines in FDI. This he e ogenei y in
esponses aligns wi h Pasca iu e al. (2021)’s inding ha coun y-speci ic ins i u ional
ac o s signi ican ly in luenced pandemic esilience.
Thi d, ou analysis e eals an impo an dis inc ion be ween sho - e m shocks o FDI
olumes and he unde lying e iciency in FDI u iliza ion. While he pandemic dis up ed
global in es men lows, he undamen al capabili ies o coun ies o e icien ly u ilize
FDI emained la gely in ac . This obse a ion suppo s Ge e i (2020)’s a gumen ha he
pandemic accele a ed exis ing ends a he han undamen ally al e ing he e iciency o
global p oduc ion ne wo ks.
Las ly, his s udy in es iga ed a leading g oup o middle-income coun ies, which a e
mo e esilien in e ms o FDI pe o mance, a he han a middle o lagging g oup, which
can be mo e ulne able o ex e nal shocks such he pandemic. The s abili y o e iciency
sco es du ing he pandemic pe iod may e lec he adap i e capaci y o manu ac u ing sec-
o s in middle-income coun ies. As no ed by So ic e al. (2022), many manu ac u ing i ms
in de eloping economies demons a ed ema kable esilience h ough he apid adop ion
o digi al echnologies and he eo ganiza ion o p oduc ion p ocesses. This adap a ion
helped main ain ope a ional e iciency e en as absolu e p oduc ion olumes luc ua ed.
The insigni icance o ou esul s, which ebu s he pandemic- ela ed hypo heses (H3a
and H3b), should he e o e no be in e p e ed as e idence ha COVID-19 had no impac
on FDI sys ems. Ra he , i sugges s ha e iciency measu es cap u e aspec s o economic
pe o mance ha a e di e en om adi ional olume-based me ics. This inding has
impo an implica ions o policy make s: while s a egies o es o e FDI olumes pos -
pandemic a e impo an , main aining and imp o ing he e iciency o FDI u iliza ion may
be equally c ucial o long- e m economic eco e y.
6. Conclusions
This s udy assessed he FDI pe o mance o 10 middle-income coun ies in hei
speci ic con ex s, wi h a ocus on echnological de elopmen , economic inequali y, and
pe o mance du ing he global pandemic. In he i s s age, we employed he non- adial
DEA model wi h i s ansla ion in a iance p ope y o add ess he nega i e ne in low o
FDI. In he model, we used i e inpu s— he ne in low o FDI, g oss capi al o ma ion,
popula ion, p ima y ene gy consump ion, and g eenhouse gas pollu ion (as an undesi able
ou pu )—and h ee ou pu s—manu ac u ing alue added, GDP, and numbe o pa en s.
A e calcula ing he ope a ional e iciency sco es unde he CRS and VRS condi ions, he SE
was ob ained as well. In he CRS model, Malaysia had he highes a e age e iciency sco e
o FDI pe o mance. In he VRS model, Bangladesh ou pe o med he o he coun ies.
India showed he lowes a e age e iciency in bo h he CRS and VRS models, wi h he
la ges s anda d de ia ion. As o SE, Thailand demons a ed an op imal scale, while he e
was oom o imp o emen o India who needs o adjus i s scale o he op imal le el.
In he second s age, we conduc ed K uskal–Wallis es s o examine h ee hypo heses,
composed o six sub-hypo heses, using bo h he CRS and VRS models. Among hem,
i e hypo heses we e suppo ed wi h s a is ically signi ican esul s. The e was a signi ican
di e ence in FDI pe o mance be ween middle-income coun ies ha achie ed di e en
le els o echnological de elopmen . When g ouped by in lec ion poin s o cumula i e
numbe o pa en cu es wi h 2022 as he di ide , a signi ican di e ence was obse ed
in he VRS model. When g ouped by he median alue o in lec ion poin s as he di ide ,
a signi ican di e ence was obse ed in he CRS model. We sugges ha he eason o
his lies in he i uous cycle be ween FDI and echnological de elopmen . FDI can b ing
abou echnology spillo e s and ans e s a i s . A e in e naliza ion, i can lead o
indus y upg ading in he hos coun y om low ech o high ech. In u n, a highe
echnology le el helps a ac highe alue-added manu ac u ing FDI, u he bene i ing
economic de elopmen .
The e was a signi ican di e ence in FDI pe o mance be ween he middle-income
coun ies ha ha e achie ed di e en le els o economic inequali y. When e alua ing
Economies 2024,12, 314 21 o 27
economic inequali y using he Gini coe icien , a signi ican di e ence was obse ed in
bo h he CRS and VRS models. When e alua ing economic inequali y using he po e y
headcoun a io o USD 3.65 a day, a signi ican di e ence was obse ed in he CRS model.
We sugges ha he inequali y b ough by FDI is na u al in he ea ly s ages, bu h ough
ein es men and o he ickle-down e ec s, i can ul ima ely p omo e economic g ow h.
While his pape con ibu es o he ex an li e a u e by explo ing he FDI issue du ing
he pandemic pe iod and by applying non- adial DEA wi h a ansla ion in a iance p op-
e y, i has some limi a ions. We a emp ed o use alida ed inpu and ou pu ac o s by
d awing on an ex ensi e li e a u e e iew, bu he e is a possibili y ha a be e se o ac o s
exis s o measu e FDI pe o mance. Simila ly, he e is a possibili y ha he inclusion o a
lagging g oup o de eloping coun ies, which a e no esilien in e ms o FDI pe o mance,
may lead o s a is ically signi ican esul s.
In e ms o da a limi a ions, he da a used in his s udy came om seconda y sou ces
p o ided by in e na ional o ganiza ions, including he Wo ld Bank Da abase, he Wo ld
In ellec ual P ope y O ganiza ion, EDGAR, and he Ene gy Ins i u e. They we e no
cus omized o ou s udy, which may b ing in impe ec measu es. Ano he issue was he
ime window be ween he inpu and ou pu ac o s. I may ake yea s o add alue o
manu ac u ing, inc ease GDP, and inc ease he numbe o pa en s om FDI in low. To ake
ha in o accoun , i may be be e o use ou pu da a wi h ime lags, bu o he bes o ou
knowledge, he e is li le esea ch on he iden i ica ion o app op ia e ime lags. Also, he e
may be he e ogenei y in ime lags among di e en ou pu ac o s. In ou u u e s udies,
we hope o ha e be e in o ma ion abou he ime lags and inco po a e hem in o he
DEA model.
Au ho Con ibu ions: Concep ualiza ion, R.Y.; me hodology, Y.R.; so wa e, R.Y.; alida ion, Y.R.;
o mal analysis, R.Y.; in es iga ion, Y.R.; esou ces, Y.R.; da a cu a ion, R.Y.; w i ing—o iginal d a
p epa a ion, R.Y.; w i ing— e iew and edi ing, Y.R. and M.V.O.; isualiza ion, R.Y.; supe ision,
Y.R. and M.V.O.; p ojec adminis a ion, Y.R. and M.V.O. All au ho s ha e ead and ag eed o he
published e sion o he manusc ip .
Funding: This esea ch ecei ed no ex e nal unding.
In o med Consen S a emen : No applicable.
Da a A ailabili y S a emen : The o iginal con ibu ions p esen ed in his s udy a e included in he
a icle. Fu he inqui ies can be di ec ed o he co esponding au ho (s).
Con lic s o In e es : The au ho s decla e no con lic s o in e es .
Appendix A
Table A1 p esen s he aw da a used o ou DEA model.
Table A1. Raw da a o inpu s and ou pu s.
Inpu s Ou pu s
Yea Coun y I 1 I 2 I 3 I 4 I 5 O 1 O 2 O 3
2015 Bangladesh 2.83 56.35 157.83 1.39 248.09 32.75 195.08 0.34
2015 B azil 64.74 313.79 205.19 12.66 1307.97 189.61 1802.21 30.22
2015 China 242.49 4782.45 1379.86 126.49 13,479.88 3202.51 11,061.60 1101.86
2015 India 19.78 293.23 259.09 28.52 961.41 180.66 860.85 45.66
2015 Indonesia 44.01 675.60 1322.87 6.78 3389.88 327.82 2103.59 9.15
2015 Malaysia 36.25 287.99 120.15 4.01 790.36 240.52 1213.29 7.73
2015 Mexico 9.86 76.62 31.07 7.93 321.31 67.18 301.36 18.07
2015 Philippines 5.64 65.40 103.03 1.60 210.10 61.07 306.45 3.73
2015 Thailand 8.93 89.71 70.29 4.98 447.45 109.85 401.30 7.93
2015 Vie nam 11.80 76.82 92.19 2.99 358.06 50.15 239.26 5.03
Economies 2024,12, 314 22 o 27
Table A1. Con .
Inpu s Ou pu s
Yea Coun y I 1 I 2 I 3 I 4 I 5 O 1 O 2 O 3
2016 Bangladesh 2.33 80.21 159.78 1.39 255.68 53.97 265.24 0.34
2016 B azil 74.29 268.81 206.86 12.36 1285.09 193.69 1795.69 28.01
2016 China 174.75 4788.92 1387.79 127.00 13,447.14 3153.13 11,233.30 1338.50
2016 India 4.54 315.52 261.85 29.80 956.68 191.25 931.88 45.06
2016 Indonesia 44.46 692.40 1338.64 6.80 3443.29 347.94 2294.80 8.54
2016 Malaysia 38.90 270.76 121.52 4.22 799.05 220.99 1112.23 7.24
2016 Mexico 13.47 78.31 31.53 8.11 318.39 65.66 301.26 17.41
2016 Philippines 8.28 78.44 104.88 1.75 221.04 62.42 318.63 3.42
2016 Thailand 3.49 87.24 70.61 5.08 449.92 112.21 413.37 7.82
2016 Vie nam 12.60 81.56 93.13 3.24 379.76 55.25 257.10 5.23
2017 Bangladesh 1.81 90.91 161.79 1.45 268.20 58.97 293.76 0.30
2017 B azil 68.89 301.80 208.51 12.47 1298.02 221.24 2063.51 25.66
2017 China 166.08 5295.15 1396.22 131.94 13,710.10 3460.35 12,310.50 1381.59
2017 India 39.97 821.48 1354.20 30.94 3590.03 204.75 2651.47 46.58
2017 Indonesia 20.51 342.37 264.50 7.04 1019.78 398.21 1015.62 9.30
2017 Malaysia 9.37 81.52 31.98 4.28 307.93 240.07 319.11 7.07
2017 Mexico 33.11 284.49 122.84 8.26 802.74 69.71 1190.72 17.18
2017 Philippines 10.26 83.96 106.74 1.92 239.39 64.05 328.48 3.40
2017 Thailand 8.29 104.66 70.90 5.17 449.46 123.28 456.36 7.87
2017 Vie nam 14.10 90.89 94.03 3.48 386.34 63.66 281.35 5.38
2018 Bangladesh 2.42 102.27 163.68 1.55 278.91 66.85 321.38 0.37
2018 B azil 78.16 289.36 210.17 12.51 1274.95 201.82 1916.93 24.86
2018 China 235.37 6085.06 1402.76 138.30 14,296.57 3868.48 13,894.90 1542.00
2018 India 42.12 874.21 1369.00 32.69 3754.62 207.03 2702.93 50.06
2018 Indonesia 18.91 360.32 267.07 7.72 1109.64 402.24 1042.27 9.75
2018 Malaysia 8.30 85.74 32.40 4.35 326.31 253.64 358.79 7.30
2018 Mexico 37.86 294.95 124.01 8.16 780.82 77.24 1256.30 16.42
2018 Philippines 9.95 94.17 108.57 1.97 246.03 66.24 346.84 4.30
2018 Thailand 13.75 127.80 71.13 5.33 446.29 135.37 506.75 8.15
2018 Vie nam 15.50 99.29 94.91 3.91 441.91 72.46 310.11 6.07
2019 Bangladesh 1.91 113.15 165.52 1.74 276.85 74.49 351.24 0.41
2019 B azil 69.17 290.67 211.78 12.72 1281.46 193.56 1873.29 25.40
2019 China 187.17 6176.24 1407.75 144.74 14,606.13 3823.42 14,280.00 1400.66
2019 India 50.61 853.41 1383.11 33.52 3731.12 220.50 2835.61 53.63
2019 Indonesia 24.99 378.03 269.58 8.22 1161.78 381.55 1119.10 11.48
2019 Malaysia 9.15 76.86 32.80 4.47 329.67 258.99 365.18 7.55
2019 Mexico 29.95 288.59 125.09 8.06 791.00 78.18 1305.21 15.94
2019 Philippines 8.67 99.49 110.38 2.03 253.39 69.77 376.82 4.38
2019 Thailand 5.52 129.55 71.31 5.34 453.57 139.38 543.98 8.17
2019 Vie nam 16.12 106.93 95.78 4.34 493.76 79.53 334.37 7.52
2020 Bangladesh 1.53 117.06 167.42 1.65 269.03 77.02 373.90 0.40
2020 B azil 38.27 237.89 213.20 12.22 1277.69 157.84 1476.11 24.34
2020 China 253.10 6369.59 1411.10 149.45 14,879.56 3860.70 14,687.70 1497.16
2020 India 64.36 768.15 1396.39 31.76 3519.12 210.40 2671.60 56.77
2020 Indonesia 19.18 342.53 271.86 7.61 1104.71 377.35 1059.05 8.16
2020 Malaysia 4.06 66.34 33.20 4.30 324.52 224.32 337.46 6.83
2020 Mexico 31.52 226.40 126.00 7.43 739.32 75.02 1120.74 14.31
2020 Philippines 6.82 63.07 112.19 1.84 242.64 63.88 361.75 3.99
2020 Thailand −4.95 118.80 71.48 4.97 449.40 127.89 500.46 7.53
2020 Vie nam 15.80 110.63 96.65 4.34 499.45 83.00 346.62 7.70
2021 Bangladesh 1.72 129.12 169.36 1.73 276.80 88.40 416.27 0.45
2021 B azil 46.44 320.44 214.33 12.85 1343.14 168.64 1649.62 24.23
2021 China 344.08 7687.80 1412.36 157.94 15,632.90 4909.01 17,820.50 1585.66
2021 India 44.73 983.70 1407.56 34.51 3754.63 228.33 3150.31 61.57
2021 Indonesia 21.21 373.14 273.75 7.76 1128.06 455.91 1186.51 8.80
2021 Malaysia 20.25 82.64 33.57 4.58 334.67 273.64 373.83 7.53
2021 Mexico 33.75 281.61 126.71 7.99 765.46 87.44 1312.56 16.16
Economies 2024,12, 314 23 o 27
Table A1. Con .
Inpu s Ou pu s
Yea Coun y I 1 I 2 I 3 I 4 I 5 O 1 O 2 O 3
2021 Philippines 11.98 83.31 113.88 1.96 254.43 69.52 394.09 4.39
2021 Thailand 15.16 144.73 71.60 5.01 455.67 137.40 505.57 8.24
2021 Vie nam 15.66 122.54 97.47 4.34 496.73 90.13 366.14 8.53
2022 Bangladesh 1.63 147.48 171.19 1.79 281.08 100.16 460.20 0.42
2022 B azil 74.61 348.37 215.31 13.41 1310.50 213.56 1920.10 24.76
2022 China 180.17 7776.13 1412.18 159.39 15,684.63 4975.61 17,963.20 1619.27
2022 India 49.94 1060.58 1417.17 36.44 3943.26 241.87 3416.65 77.07
2022 Indonesia 24.70 392.37 275.50 9.77 1240.83 456.06 1319.10 9.97
2022 Malaysia 14.73 95.68 33.94 4.84 353.92 314.70 407.03 7.37
2022 Mexico 39.10 333.41 127.50 8.73 819.87 95.22 1465.85 16.61
2022 Philippines 9.37 99.85 115.56 2.11 265.30 69.70 404.28 4.77
2022 Thailand 11.23 137.76 71.67 5.06 463.87 133.87 495.42 8.61
2022 Vie nam 17.90 136.57 98.19 4.59 489.16 101.22 408.80 8.71
No e: I 1 = ne in low o FDI; I 2 = g oss capi al o ma ion; I 3 = popula ion; I 4 = p ima y ene gy consump ion;
I 5 = GHG emissions; O 1 = manu ac u ing alue added; O 2 = GDP; O 3 = numbe o pa en s.
Appendix B
Figu e A1 p esen s a panel o he 10 coun ies’ S cu es based on he numbe o
accumula ed pa en s (ac ual and i ed by logis ic unc ion cu es) o e ime.
Economies 2024, 12, x FOR PEER REVIEW 24 o 29
2022 Malaysia 14.73 95.68 33.94 4.84 353.92 314.70 407.03 7.37
2022 Mexico 39.10 333.41 127.50 8.73 819.87 95.22 1465.85 16.61
2022 Philippines 9.37 99.85 115.56 2.11 265.30 69.70 404.28 4.77
2022 Thailand 11.23 137.76 71.67 5.06 463.87 133.87 495.42 8.61
2022 Vie nam 17.90 136.57 98.19 4.59 489.16 101.22 408.80 8.71
No e: I 1 = ne in low o FDI; I 2 = g oss capi al o ma ion; I 3 = popula ion; I 4 = p ima y ene gy
consump ion; I 5 = GHG emissions; O 1 = manu ac u ing alue added; O 2 = GDP; O 3 = numbe o
pa en s.
Appendix B
Figu e A1 p esen s a panel o he 10 coun ies S cu es based on he numbe o ac-
cumula ed pa en s (ac ual and i ed by logis ic unc ion cu es) o e ime.
(a)
(b)
(c)
(d)
Figu e A1. Con .
Economies 2024,12, 314 24 o 27
Economies 2024, 12, x FOR PEER REVIEW 25 o 29
(e)
( )
(g)
(h)
(i)
(j)
Figu e A1. Pa en -based S cu es o en middle-income coun ies. No e: C = cumula i e numbe o
pa en s (ac ual); S = cumula i e numbe o pa en s ( i ed by logis ics unc ion). (a) Bangladesh; (b)
B azil; (c) China; (d) Indonesia; (e) India; ( ) Mexico; (g) Malaysia; (h) he Philippines; (i) Thailand;
and (j) Vie nam.
Re e ences
(Ajide and Osinubi 2020) Ajide, Folo unsho M., and Tolulope T. Osinubi. 2020. COVID-19 Pandemic and Ou wa d Fo eign Di ec
In es men : A P elimina y No e. Economics 8: 79–88. h ps://doi.o g/10.2478/eoik-2020-0019.
Figu e A1. Pa en -based S cu es o en middle-income coun ies. No e: C
= cumula i e numbe
o pa en s (ac ual); S
= cumula i e numbe o pa en s ( i ed by logis ics unc ion). (a) Bangladesh;
(b) B azil; (c) China; (d) Indonesia; (e) India; ( ) Mexico; (g) Malaysia; (h) he Philippines; (i) Thailand;
and (j) Vie nam.
Re e ences
Ajide, Folo unsho M., and Tolulope T. Osinubi. 2020. COVID-19 Pandemic and Ou wa d Fo eign Di ec In es men : A P elimina y
No e. Economics 8: 79–88. [C ossRe ]
Alna ah, Ib ahim. 2021. E iciency E alua ion o BRICS’s Na ional Inno a ion Sys ems Based on Bias-Co ec ed Ne wo k Da a
En elopmen Analysis. Jou nal o Inno a ion and En ep eneu ship 10: 26. [C ossRe ]
