Beyond borders: The effects of immigrants on value-added trade

Tadesse, Bedassa; Whi e, Roge
A icle
Beyond bo de s: The e ec s o immig an s on alue-added
ade
Economies
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MDPI – Mul idisciplina y Digi al Publishing Ins i u e, Basel
Sugges ed Ci a ion: Tadesse, Bedassa; Whi e, Roge (2024) : Beyond bo de s: The e ec s o
immig an s on alue-added ade, Economies, ISSN 2227-7099, MDPI, Basel, Vol. 12, Iss. 9, pp. 1-21,
h ps://doi.o g/10.3390/economies12090222
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Ci a ion: Tadesse, Bedassa, and Roge
Whi e. 2024. Beyond Bo de s: The
E ec s o Immig an s on Value-
Added T ade. Economies 12: 222.
h ps://doi.o g/10.3390/
economies12090222
Academic Edi o s: Ma ina-Selini
Ka sai i, Ma oula Kh aiche and
M i ika Shamsuddin
Recei ed: 6 July 2024
Re ised: 11 Augus 2024
Accep ed: 20 Augus 2024
Published: 23 Augus 2024
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economies
A icle
Beyond Bo de s: The E ec s o Immig an s on
Value-Added T ade
Bedassa Tadesse 1,* and Roge Whi e 2,*
1Depa men o Economics, Labo i z School o Business and Economics, Uni e si y o Minneso a Dulu h,
1318 Ki by D i e, Dulu h, MN 55812, USA
2Depa men o Economics, Whi ie College, 13406 E. Philadelphia S ee , Whi ie , CA 90506, USA
*Co espondence: [email p o ec ed] (B.T.); whi e1@whi ie .edu (R.W.); Tel.: +1-(218)-726-8365 (B.T.);
+1-(562)-907-4908 (R.W.); Fax: +1-(218)-726-6905 (B.T.); +1-(562)-907-4956 (R.W.)
Abs ac : While he e ec s o immig an s on agg ega e ade lows ha e been ex ensi ely examined,
he ole o immig an s in shaping ade in alue added (TiVA) emains unde explo ed. Employing
a panel da ase co e ing 38 O ganiza ion o Economic Co-ope a ion and De elopmen (OECD)
membe hos coun ies and 64 immig an home coun ies spanning 2000–2018 and es ima ing a
andom in e cep and andom slope mixed-e ec s model, we ind ha immig an s play a signi ican
ole in enhancing he alue added om hei home coun ies ha is embedded in hei hos coun ies’
expo s o he wo ld. We documen hese e ec s a he agg ega e le el and ac oss sec o s (i.e.,
manu ac u ing, ag icul u e, and se ices). The e is, howe e , conside able a ia ion in he in luence
o immig an s on TiVA ac oss coun y pai s. Ou indings highligh ha immig an s signi ican ly
enhance ade sophis ica ion by p omo ing specializa ion and upwa d mo emen in he alue chain,
yielding economic bene i s o hei home and hos coun ies.
Keywo ds: immig a ion; alue-added ade; ade cos s; p oduc i e capaci y
JEL Classi ica ion: F22; F14; F23; F10
1. In oduc ion
Immig an s play indispensable and mul i ace ed oles in shaping he economic oo -
p in s o bo h hei home and hos coun ies, especially in he global ma ke place. As wo k-
e s, hey ill c i ical labo ma ke gaps, b inging unique skills and pe spec i es ha d i e
p oduc i i y and inno a ion (Ke 2023). As consume s, hei p e e ences o home coun y
p oduc s signi ican ly in luence bila e al ade lows (Gould 1994). As en ep eneu s, hey
enhance hei hos coun y’s compe i i e edge in global ade by in oducing new p oduc s
and se ices, c ea ing alue, and con ibu ing o esea ch and de elopmen (Hun and
Gau hie -Loiselle 2010). Immig an s also s imula e economic ac i i y in hei home coun-
ies h ough emi ances, acili a ing new businesses and os e ing he in lows o o eign
di ec in es men s (Cuad os e al. 2016;Flisi and Mu a 2011).
Immig an ne wo ks a e also i al in p omo ing in e na ional ade h ough educ ions
in ela ed ansac ion cos s. Gould (1994) i s p oposed ha immig an s, h ough e hnic
ne wo ks (i.e., business and social connec ions) and hei knowledge o home and hos
coun y ma ke s, b idge in o ma ion asymme ies, enhance he en o cemen o con ac s,
and in luence he bila e al ade p e e ences o hei home and hos coun ies. Se e al
s udies con i m he posi i e in luences o immig an s on bila e al ade lows (e.g., Head
and Ries 1998;Genc e al. 2012). Fo example, Rauch and T indade (2002) ind ha he
p esence o e hnic Chinese ne wo ks signi ican ly inc eases bila e al ade.
1
Pa sons and
Vézina (2018) conclude ha in addi ion o acili a ing he low o inal p oduc s, immig an
ne wo ks help o ensu e he smoo h low o in e media e goods and se ices, which
Economies 2024,12, 222. h ps://doi.o g/10.3390/economies12090222 h ps://www.mdpi.com/jou nal/economies
Economies 2024,12, 222 2 o 21
a e essen ial o es ablishing ading ela ionships and alue c ea ion a a ious s ages
o p oduc ion.
Building on hese insigh s, se e al s udies ha e employed inno a i e me hodologies
o isola e he causal e ec s o mig a ion on ade. Pa sons and Vézina (2018) le e age a
na u al expe imen in ol ing Vie namese boa people ese led in he U.S. o es ablish a
causal link be ween mig a ion and ade. They ind ha U.S. expo s o Vie nam we e
signi ican ly highe in s a es wi h la ge Vie namese popula ions, wi h a 10 pe cen inc ease
in Vie namese immig an s co esponding wi h a 4.5 pe cen inc ease in expo s. This
s udy p o ides compelling e idence o he ade-c ea ion e ec o immig an s, pa icula ly
h ough hei ole in educing in o ma ion ba ie s and con ac en o cemen cos s.
The ole o e hnic ne wo ks in acili a ing in e na ional ade has been u he eluci-
da ed by Rauch and T indade (2002), who ocus on e hnic Chinese ne wo ks. They ind
ha hese ne wo ks signi ican ly inc ease bila e al ade, wi h he e ec being pa icula ly
p onounced o di e en ia ed p oduc s. Fo coun ies wi h e hnic Chinese popula ions in
he i s and hi d qua iles, he ne wo ks a e associa ed wi h inc eases in bila e al ade o
60 pe cen o di e en ia ed goods and 150 pe cen o all goods combined. This unde -
sco es he impo ance o social and business ne wo ks in o e coming in o ma ional ba ie s
o ade, especially o complex, di e en ia ed p oduc s ha o en comp ise a signi ican
po ion o alue-added ade.
Ha zigeo giou (2010) p o ides addi ional e idence on mig a ion’s ade- acili a ing
ole, inding ha immig a ion and emig a ion posi i ely impac ade lows. The s udy
e eals ha a 10 pe cen inc ease in immig an s ock is associa ed wi h a 4.5 pe cen inc ease
in impo s and a 5 pe cen inc ease in expo s. In compa ison, a simila inc ease in he
emig an s ock co esponds o a 5 pe cen ise in impo s and a 4.5 pe cen inc ease in
expo s. These indings highligh he bidi ec ional na u e o he mig a ion- ade ela ionship
and sugges ha immig an s and emig an s can se e as condui s o ade h ough hei
knowledge o home and hos coun y ma ke s.
Fu he mo e, Kugle and Rapopo (2011) ex end he analysis beyond ade o examine
he ela ionship be ween mig a ion, o eign di ec in es men (FDI), and ade ma gins.
They ind ha skilled mig a ion is posi i ely associa ed wi h u u e FDI, pa icula ly in he
se ice sec o . This ela ionship is complemen a y o ade, wi h mig a ion con ibu ing o
bo h he ex ensi e (new ade ela ionships) and in ensi e (inc eased olume o exis ing
ade) ma gins. Thei indings sugges ha mig an s acili a e ade and play c ucial oles
in a ac ing FDI and expanding he scope o in e na ional economic ela ionships. This
can u he enhance alue-added ade be ween coun ies.
The a ailable li e a u e sugges s ha immig an ne wo ks educe in o ma ional ba -
ie s, making hos coun y i ms mo e likely o engage in in e na ional ou sou cing o
in e media e inpu s o he immig an s’ home coun ies (Bandyopadhyay e al. 2008;Hille
2013). Hille (2013) epo s ha immig an employees inc ease he likelihood o a i m
engaging in expo s by app oxima ely 5–6 pe cen age poin s compa ed o i ms wi hou
immig an employees. Simila ly, Bandyopadhyay e al. (2008) ind ha a 10% inc ease in
he immig an popula ion om a speci ic coun y wi hin a U.S. s a e is associa ed wi h
app oxima ely a 1.5% inc ease in ha s a e’s expo s o he immig an s’ coun y o o igin.
Simila ly, Mi a i onna e al. (2017) also conclude ha access o immig an s’ con ac s and
knowledge likely acili a es hos coun y impo s o inpu s and pa icipa ion in supply
chain ne wo ks cen e ed a ound majo hub coun ies.
Gi en hei my iad posi i e in luences, i can be in e ed ha immig an s a ec in e -
na ional ade in alue added (TiVA) by educing in o ma ion asymme y and ansac ion
cos s and making a smoo he low o in e media e goods and se ices possible, pa icula ly
in he complex domain o alue-added ade. Thus, any analysis o he immig an – ade
ela ionship solely ocusing on hei e ec s on g oss ade lows is incomple e. Speci ically,
because g oss ade lows accoun o he o al mone a y alue o aded goods wi hou
dis inguishing he o igins o hei componen s, hey o e look he in icacies o global alue
chains (GVCs), whe e p oduc componen s a e sou ced om mul iple coun ies. Immi-
Economies 2024,12, 222 3 o 21
g an s may in luence GVCs h ough ade in inal goods and he alue added a a ious
s ages o p oduc ion (Timme e al. 2015); hei oles migh be mo e p ominen in speci ic
segmen s o hese chains, such as in p oducing in e media e goods o in sec o s whe e he
immig an s’ home coun ies ha e a compa a i e ad an age (Bas os and Sil a 2012).
Since immig an s o en possess speci ic skills and knowledge ele an o indus ies in
which hei home (hos ) coun y has a compe i i e ad an age, hey may p o ide knowledge
ha signi ican ly enhances he p oduc i e capaci y o he hos (home) coun y, especially in
sec o s whe e such skills a e in sho supply. The esul ing inc ease in p oduc i i y may
inc ease he alue added in he p oduc ion p ocesses (Docquie and Rapopo 2012). Fo
example, skilled immig an s con ibu e o inno a ion and echnological ad ancemen s in
hei hos coun ies, po en ially leading o he de elopmen o new p oduc s and se ices
(Ke e al. 2016). The abili y o a coun y o add alue is shaped by se e al key ac o s: he
a ailabili y o esou ces such as labo ; physical and human capi al ( he skills, knowledge,
and expe ise o he wo k o ce); echnological capabili ies and in as uc u e; and he
e iciency o managemen p ac ices and ins i u ional amewo ks. The e o e, con olling
o he ela i e p oduc i e capaci ies o he home and hos coun ies when analyzing how
immig an s in luence alue-added ade is c ucial.
Finally, due o hei specialized knowledge, skills, and ne wo ks, immig an s can
enhance ade in ways no immedia ely appa en h ough g oss ade igu es. Fo ins ance,
immig an s may acili a e ade by educing ansac ion cos s, connec ing businesses ac oss
bo de s, o d i ing demand o speci ic goods and se ices om hei home coun ies
(Aleksynska and Pe i 2014). Such con ibu ions may indi ec ly in luence alue c ea ion
h ough imp o ed p oduc ion e iciencies o heigh ened demand o specialized compo-
nen s. Thus, o ully g asp he impac o immig an s on in e na ional ade, i is essen ial o
look beyond hei e ec s on g oss ade alues.
Ou p ima y objec i e is o in es iga e he in luence o immig an s on TiVA while
con olling o di e ences in he p oduc i e capaci ies o hei home and hos coun ies
ha de e mine alue c ea ion. Es ima ing a se ies o mul ile el models using panel da a
ha span he yea s 2000–2018 on agg ega e and sec o -speci ic measu es o TiVA in 38
O ganiza ion o Economic Co-ope a ion and De elopmen (OECD) coun ies ha se e
as hos s o immig an s om 64 home coun ies, we ind ha an inc ease in he s ock o
immig an s om a ypical home coun y ha eside in each hos coun y has posi i e and
s a is ically disce nible impac s on he alue ha is gene a ed in he home coun ies and
embedded in he expo s o he hos coun ies o in e na ional ma ke s.
Ou s udy makes wo key con ibu ions. Fi s , by demons a ing he impac s o immi-
g an s pu ely on he TiVA om hei home coun ies ha is embedded in he expo s o
hei hos coun ies— ep esen ing he economic oo p in s o bo h he home and hos coun-
ies in he global p oduc ion ne wo ks—we highligh hei mul i ace ed ole in enabling
coun ies o specialize, mo e up he alue chain, and enhance ade sophis ica ion. Second,
by demons a ing he impac o immig an s on ade in goods and se ices ha c osses a
leas wo bo de s, we shed ligh on immig an s’ signi ican ye o e looked ole in global
ade, unde sco ing he need o suppo i e, o wa d-looking immig a ion policies ha
ecognize and ha ness immig an s’ economic po en ial in highly globalized ma ke s.
We p oceed as ollows: Sec ion 2o e s an o e iew o he li e a u e explo ing he
nexus be ween immig an s and TiVA. Sec ion 3ou lines ou empi ical amewo k, de ailing
he da a sou ces, p ima y a iables, and con ols. Ou esul s, including in e p e a ions
and obus ness checks, a e p esen ed in Sec ion 4. Finally, Sec ion 5concludes he a icle
wi h an emphasis on po en ial policy implica ions.
2. Li e a u e Re iew
Due o i s policy implica ions, pa icula ly in he ace o ising globaliza ion, he ela-
ionship be ween in e na ional mig a ion and ade ga ne s a en ion om bo h heo e ical
and empi ical pe spec i es. T adi ional in e na ional ade heo ies, such as he Rica dian
model, o e cul u al and p e e ence explana ions o he complemen a i y be ween immi-
Economies 2024,12, 222 4 o 21
g an s and ade lows. Gould (1994), Rauch and T indade (2002), and Rauch (2001), o
example, iden i y immig an s as i al in e media ies in bila e al ade o easing language
ba ie s, aiding business ma chmaking, and educing in o ma ion asymme ies.
Mo e ecen s udies inco po a ing he e ogeneous i m ade heo ies unde sco e he
ole o immig an ne wo ks in educing he cos s associa ed wi h in e na ional ade. U i-
lizing Meli z’s i m (Meli z 2008) he e ogenei y amewo k, esea che s ha e p oposed a
“business ne wo k” na a i e, which sugges s ha immig an s p o ide i al ma ke in o -
ma ion, con ac s, and esou ces, he eby acili a ing i m en y in o o eign ma ke s (Kugle
and Rapopo 2011;I anzo and Pe i 2009). D awing on Chaney (2014) and Bu cha di
e al. (2019), o example, obse e ha skilled immig an s ac as “pionee s”, p o iding
in o ma ion abou oppo uni ies in des ina ion coun ies and encou aging he engagemen
o i ms om hei coun ies o o igin.
Summa izing he heo e ical unde pinnings, Felbe may e al. (2010) asse ha
he p esence o immig an s p omo es ade be ween hei home and hos coun ies by
mi iga ing incomple e in o ma ion, a enua ing ic ions due o asymme ic in o ma ion,
and se ing as a loyal consume base. Fi s , by helping o e come in o mal ba ie s o
in e na ional ade, such as di e ences in languages, cul u es, o ins i u ions, immig an s
c ea e business ela ionships and make aluable in o ma ion on o eign sales and sou cing
oppo uni ies mo e eadily a ailable. Second, h ough hei ne wo ks, immig an s educe
ic ion caused by asymme ic in o ma ion and lowe he isk o oppo unis ic beha io
in business dealings, which may educe he olume o ansac ions below he socially
desi able le el. Las ly, immig an s boos ade be ween hei home and hos coun ies
h ough na u al p e e ences o he goods p oduced in hei home coun ies.
Ex ensi e empi ical esea ch p esen s s ong e idence ha suppo s he ole played by
immig an s in shaping bila e al ade pa e ns bo h a na ional and subna ional le els (e.g.,
Bo e and Elia 2017;Aleksynska and Pe i 2014;Bas os and Sil a 2012;Pe i and Requena-
Sil en e 2010;Bandyopadhyay e al. 2008;Dunle y 2006;Combes e al. 2005;He ande and
Saa ed a 2005;Rauch and T indade 2002;Gi ma and Yu 2002;Wagne e al. 2002;Head and
Ries 1998; and Gould 1994). Pooling 284 expo and 229 impo elas ici ies om 48 s udies
ha apply he g a i y model in he con ex o he ade-c ea ion e ec o immig an s and
conduc ing a me a-analysis, Genc e al. (2012) epo a e age elas ici ies o bila e al expo s
and impo s o inc eased immig an s ocks o 0.16 and 0.15, espec i ely.2
Despi e he oluminous esea ch add essing immig an s’ impac s on agg ega e ade
lows, s udies examining hei in luence on alue-added ade a e limi ed. Immig an s
may a ec alue-added ade in mo e dis inc ways han agg ega e ade lows. Fi s ,
hey in oduce specialized skills essen ial o he ope a ion o indus ies. These skills
enhance he e iciency and p oduc i i y o he sec o s in ol ed in in e na ional ade,
he eby inc easing he alue added by hese indus ies (O a iano e al. 2018). Second, hey
acili a e economic and cul u al linkages ha can imp o e in e na ional coope a ion and
educe ansac ion cos s, making hem in aluable in s eamlining ope a ions and enhancing
he in eg a ion o supply chains, u he bols e ing he alue added o p oduc s and se ices
(Zhou and Anwa 2022). Thi d, by os e ing inno a ion and en ep eneu ship, immig an s
may in oduce new p ocesses and p oduc s, s eng hening a coun y’s compe i i e posi ion
globally (Ke and Lincoln 2010). They also p o ide labo ma ke lexibili y, adap ing
quickly o changes in p oduc ion demands, which is c ucial o indus ies ha mus
espond dynamically o global ma ke condi ions (Azoulay e al. 2022). This lexibili y,
combined wi h hei unique insigh s in o egula o y and ma ke en i onmen s, enhances
ade acili a ion, which is a c i ical componen in he e iciency o GVCs.
Finally, immig an s o en ha e p o ound cul u al and emo ional connec ions o p od-
uc s om hei home coun ies, such as ood i ems, clo hing, and en e ainmen , ha go
beyond he essen ial u ili y o hese goods, c ea ing loyal consume bases o speci ic hos
coun y impo s. Many goods (e.g., e hnic oods o adi ional a i e) a e unique and no eas-
ily eplicable; he specialized na u e o hese p oduc s may equi e indigenous p oduc ion
p ocesses, ing edien s, o c a smanship, which enhances he alue-added con en o hese

Economies 2024,12, 222 5 o 21
impo s. People o en ega d he quali y and au hen ici y o ce ain goods, pa icula ly
i ems o cul u al signi icance, om hei home coun ies as supe io . This pe cep ion may
lead hem o a o impo s om hei home coun ies o e local al e na i es. Consequen ly,
while he mechanism applies o bo h g oss ade and alue-added ade, he p e e ence
e ec s o immig an s on alue-added ade may be subs an ial.
3. Empi ical Model, Da a, and Va iables
3.1. The Empi ical Model
Gi en ha we ocus on alues ha c oss a leas wo bo de s, excluding domes ic
consump ion, ins ead o he adi ional economic mass (i.e., le els o GDP), ou baseline
model a ibu es TiVA o he p oduc i e capaci ies o coun ies
i
and
j
, each loca ed in
egion
k
, du ing yea
(
PCIk
i
and
PCIk
j
, espec i ely, which a e in he ec o
ωij
), he
immig an s ock om home coun y
i
ha esides in he hos coun y
j
(
Immigk
ij
), and ad
alo em a i -equi alen bila e al ade cos s (
τij
) a ec ing ade lows be ween he home
and hos coun ies. Equa ion (1) illus a es he model.
Yk
ij =λ0+γlnωk
ij +δlnImmigk
ij +θlnτk
ij +uk
ij (1)
Ou p ima y dependen a iable (
Yk
ij
) is he alue added gene a ed in he home
coun y
i
ha is embedded in he agg ega e- and sec o -le el (ag icul u al, manu ac u ing,
and se ices) expo s o hos coun y
j
o he wo ld du ing yea
(
TiVAk
ij
). Fo compa ison,
we also use he hos coun y
j
’s g oss impo s om (expo s o) he home coun y idu ing
yea as ou dependen a iable.
As no ed,
ωk
ij
includes he measu es o p oduc i e capaci y o each home and hos
coun y. The alues a e mul idimensional indexes ep esen ing ad anced echnologies,
skilled wo k o ces, e icien in as uc u es, and e ec i e ins i u ions. The p oduc i e
capaci ies o he home (hos ) coun ies de e mine hei abili ies o p oduce and deli e
goods and se ices (UNCTAD 2021). Encompassing a coun y’s capaci y o specialize,
a ain economies o scale, b oaden hei ou pu a ie y, uphold supe io quali y s anda ds,
d aw in es men s, and os e inno a ion a a b oade le el, a na ion’s p oduc i e capaci y
is pi o al in shaping i s TiVA. Equa ion (2) u he desc ibes he ela ionship.
ωk
ij =PCI k
i ×PCI k
j (2)
The second e m in Equa ion (1),
Immigk
ij
, is he numbe o immig an s om home
coun y
i
ha eside in coun y
j
du ing yea
. As no ed, immig an s’ access o business
and social ne wo ks may acili a e ade, in es men , and knowledge exchanges. I is
also an icipa ed ha h ough skill ans e , en ep eneu ship, capi al in lows, emi ances,
knowledge dissemina ion, and he c ea ion o business ne wo ks, immig an s shape he
p oduc i e capaci ies o hei home and hos coun ies. Addi ionally, la ge diaspo a com-
muni ies may in es in signi ican p ojec s in hei home coun ies ha bols e p oduc i e
capaci y (e.g., in as uc u e de elopmen , educa ional ins i u ions, o echnological hubs).
P oduc i e capaci ies may be pi o al in in luencing how immig an s os e TiVA be-
ween hei home and hos coun ies. Fo example, a hos coun y wi h a obus p oduc i e
capaci y may o e an en i onmen ha is mo e conduci e o inno a ion and in eg a ion
in o es ablished indus ies, allowing immig an s o ac as b idges o ade by sha ing
unique insigh s in o ma ke demand and he business p ac ices o hei home coun ies.
Con e sely, i he hos na ion has a limi ed p oduc i e capaci y, immig an s migh ace
challenges in con ibu ing o TiVA be ween hei na i e and adop ed lands. Acco dingly,
we augmen Equa ion (2) wi h a e m ha in e ac s he immig an s ock a iable and he
p oduc i e capaci y measu es.
ωk
ij =[PCI α1
i ×PCI α2
j i×hImmigα3
ij i(3)
Economies 2024,12, 222 6 o 21
The inal a iable in Equa ion (1),
τk
ij
, is an ad alo em a i -equi alen measu e o
bila e al ade cos s. De i ed om he in e se g a i y amewo k (No y 2013), he measu e
cap u es ade cos s in i s b oad sense, including bo h in e na ional anspo cos s and
a i s as well as o he ade cos componen s, as discussed by Ande son and an Wincoop
(2004), such as he di ec and indi ec cos s o linguis ic di e ences, cu ency exchange,
and cumbe some impo o expo p ocedu es ha inhibi ade be ween he hos and
home coun ies.
Combining Equa ions (1)–(3) and log- ans o ming he a iables yields a o m o he
g a i y model o ade, p esen ed as Equa ion (4), ha desc ibes bila e al TiVA.
ln Yk
ij =α0+α1lnImmigk
i +α2lnPCIk
i +α3lnPCIk
j
+α4hlnImmigk
ij ×lnPCIk
i i+α5hlnImmigk
ij ×lnPCIk
j i
+α6lnτij +nk
ij +uk
ij
(4)
In Equa ion (4), he slope coe icien s
α1
,
α4
, and
α5
e lec he e ec s o he s ock o
immig an s om home coun y
i
ha eside in hos coun y
j
.
3
Addi ionally,
α2
and
α3
ep esen he impac s o home and hos coun ies’ p oduc i e capaci ies, espec i ely, wi h
he ec o
nk
ij
ep esen ing a se ies o home, hos , and ime-speci ic ixed e ec s and
uk
ij
being an assumed iden ically and independen ly dis ibu ed andom e o e m.
We es ima e Equa ion (4) using h ee al e na i e app oaches: (a) he High-Dimensional
Fixed-E ec s (HDFE) es ima ion app oach inco po a ing he mul ila e al esis ance e ms
and he dyadic ixed e ec o accoun o a ious sou ces o unobse ed he e ogenei y ha
could bias he esul s; (b) he PPML (Poisson Pseudo-Maximum Likelihood) and HDFE
(High-Dimensional Fixed-E ec s) g a i y model app oach, which allows o handling he
issue o ze o ade lows, which a e common in he da a; and (c) he mixed-e ec s ( andom
in e cep and andom coe icien ) model.
The i s wo es ima ion app oaches possess wo dis inc cha ac e is ics. Fi s , al hough
hey pe mi accoun ing o unobse ed he e ogenei y ha may in luence he dependen
a iable, hey p esume a consis en e ec o immig an s ac oss all coun y pai s. While
he p ima y mechanisms h ough which immig an s a ec ade migh be consis en , he
assump ion may no always hold. Fo example, de ia ions in he e ec s o immig an s may
a ise due o a ia ions in hei size and skill composi ion, he o e all di e si y o immig an s
om each o he home coun ies ha eside in he hos coun ies, o di e ences in he
s anda ds and egula ions ha go e n ade in in e media e p oduc s (i.e., alue added).
Second, bo h app oaches p esume ha he e ms
ui
ij
and
ui′
ij
, a e mu ually exclusi e.
Howe e , he ade in e ac ions be ween coun y pai s, especially among geog aphically
p oxima e coun ies o wo home coun ies nes ed in he same egion, may esul in a
close esemblance o a gi en pai han o he pai s, po en ially esul ing in co ela ed
e o e ms.4
To ackle hese issues, ollowing Bal agi e al. (2003), we in oduce a home–hos coun y
pai -speci ic andom componen ,
ζi
, which allows he e o e m
uk
ij
, o be decomposed
in o wo dis inc pa s.
uk
ij ≡ζ1i+ϵk
ij (5)
Subs i u ing Equa ion (5) in o Equa ion (4) yields he mul ile el mixed-e ec s model
( andom in e cep and andom coe icien ) p esen ed as Equa ion (6).
ln Yk
ij =α0ij +α1ijlnImmigk
i +α2lnPCIk
i +α3lnPCIk
j
+α4hln Immigk
ij ×ln PCIk
i i+α5hln Immigk
ij ×ln PCIk
j i
+α6lnτij +ϵk
ij
(6)
The e ms
α0ij =ζ00k+u0ij
and
α1ij =ζ10k
+
u1ij
ep esen he andom in e cep s and
andom slopes (i.e., he impac s o immig an s) on TiVA o a speci ic home–hos coun y
Economies 2024,12, 222 7 o 21
pai .
ζ00k
and
ζ10k
indica e he mean in e cep and slope o a gi en egion k, while
u0ij
and
u1ij
iden i y he andom e ec s ha co espond o he home–hos coun y pai s. A posi i e
de ia ion (
u1ij >0
sugges s ha he in luence o immig an s on TiVA o a speci ic coun y
pai exceeds he a e age e ec . Con e sely, a nega i e de ia ion (
u1ij <0
sugges s ha
he impac o immig an s on TiVA o he gi en coun y pai is below he a e age. The
e ms
α2
and
α3
highligh he impac o he p oduc i e capaci ies o he home and hos
coun ies. As be o e,
α4
and
α5
signi y he deg ees o which he immig an s ock in e plays
wi h he p oduc i e capaci y me ics o he home and hos coun ies, while
α6
ep esen s
he in luence o ade cos s on TiVA. The andom e o e m o coun y pai iand ja ime
is deno ed by ϵk
ij .
3.2. The Va iables, Da a Sou ces, and Expec ed Signs
3.2.1. Dependen Va iables
Ou dependen a iables a e bila e al TiVA measu es o igina ing om 64 home (in-
cluding OECD membe ) coun ies and embedded in he expo s o 38 OECD membe hos
coun ies o which da a on he s ocks o immig an s in he espec i e OECD coun ies
du ing he s udy pe iod (2000–2018) and p oduc i e capaci y indices a e a ailable. The
measu es include he o al alue added om all indus ies in each home coun y ha is em-
bedded in he expo s o he hos coun ies, disagg ega ed by sec o s (i.e., manu ac u ing,
ag icul u e, and se ices), o in e na ional ma ke s. The measu es, sou ced om he O igin
o Value Added in G oss Expo s (OECD 2021) and exp essed in millions o U.S. dolla s
a cu en p ices, p o ide insigh s in o he complex p oduc ion and supply ne wo ks ha
connec immig an s’ home and hos coun ies.
We also u ilize g oss bila e al expo s (impo s) be ween he home and hos coun-
ies o compa a i e pu poses and o pu he es ima ed e ec s o immig an s on TiVA
in o pe spec i e.
3.2.2. Explana o y Va iables
Gi en hei po en ial o ampli y ade be ween hei home and hos coun ies, ou
p ima y in e es is he coe icien o he immig an s ock a iable. As indica ed, immig an s
may con ibu e o TiVA by acili a ing he sou cing o p oduc s and se ices om hei
home (hos ) coun ies o ill ma ke gaps in hei hos (home) coun ies. Dual cul u al
unde s anding also allows immig an s o e ec i ely media e ade nego ia ions, educ-
ing misunde s andings and os e ing mu ual us . Addi ionally, diaspo a ne wo ks can
po en ially cul i a e o mal business ela ionships, pa ne ships, and o he collabo a ions
be ween i ms in he immig an s’ home and hos coun ies, pa icula ly in alue-added
ade. Simila ly, he inhe en us , cul u al o e laps, and sha ed expe iences ha im-
mig an s in oduce o he ade dynamic can educe ansac ion cos s and en ich he
olume and quali y o alue-added ade lows.
5
Las ly, immig an s’ ex ensi e awa eness
o p oduc ion s anda ds, quali y benchma ks, and business e hos ac oss bo de s solidi ies
hei posi ion as c ucial connec o s, ensu ing ha p oduc s adhe e o global no ms and
acili a ing seamless ade in di e en ia ed p oduc s (Rauch and T indade 2002).
We examine he e ec s while con olling o he hos and home coun ies’ p oduc i e
capaci ies o gene a e alue and he bila e al ade cos s, de e mining he easibili y o
ade be ween he po en ial pa ne s. Encompassing echnological p owess, in as uc u e,
skilled labo o ce, and e icien ins i u ional amewo ks, he p oduc i e capaci y index
(PCI) measu es he abili y o a coun y o p oduce and ade goods o p o ide se ices
e icien ly. The measu e is quan i ied as a geome ic mean o eigh key dimensions: human
capi al, which emphasizes he quali y o labo , educa ion, skills, and o e all heal h condi-
ions; na u al capi al, e lec ing a coun y’s enewable and non- enewable esou ces like
mine als and o es s; ene gy access, indica ing he eliabili y o ene gy sou ces; s uc u al
change, e lec ing economic ans o ma ion owa ds high-p oduc i i y sec o s; ins i u ions,
ou lining he go e nance and egula o y amewo ks; he igo o he p i a e sec o , o-
cusing on aspec s like inno a ion and access o inance; anspo in as uc u e, which
Economies 2024,12, 222 8 o 21
includes oads, ailways, and po s ha a e i al o ade; and in o ma ion and commu-
nica ions echnology in eg a ion and accessibili y, depic ing a na ion’s emb ace o digi al
ools and echnologies (UNCTAD 2021).6
A high p oduc i e capaci y p omo es echnological spillo e , eliable supply chains,
and access o quali y inpu s, all o which con ibu e alue o he goods and se ices
p oduced by ade pa ne s. I also c ea es economies o scale, allowing coun ies o
p oduce a lowe cos s. This can lead o compe i i e p icing in in e na ional ma ke s,
making p oduc s mo e appealing o consume s in o he coun ies and encou aging ade.
T ade cos s encompass a my iad o ac o s impeding he exchange o goods and se -
ices be ween coun ies. Di ec inancial obs acles include explici a i s and non- a i
ba ie s such as quo as, emba goes, and di e ing egula ions, which in la e he p oduc-
ion cos s o manu ac u e s needing o mee a ying in e na ional s anda ds (Ande son
and an Wincoop 2004). Indi ec cos s encompassing anspo a ion expenses a e ied o
geog aphical and in as uc u al ac o s and p ocedu al ine iciencies a bo de s ha cause
cos ly delays and spoilage o pe ishable goods, a ec ing he imely deli e y o componen s
(Hummels 2007;Po ugal-Pe ez and Wilson 2012). In addi ion, in angible ac o s (e.g., lack
o ma ke in o ma ion, cul u al and linguis ic ba ie s, and inancial challenges, pa icula ly
in de eloping economies) can de e i ms om engaging in in e na ional ade (Rauch 1999;
Ahn e al. 2011) o make i mo e expensi e o coun ies o impo componen s o u he
enhancemen o expo goods a e imbuing hem wi h added alue.
To adequa ely cap u e he e ec , we u ilize he ad alo em a i -equi alen mea-
su es o bila e al ade cos s (l cos ) sou ced om UNESCAP h ough he Wo ld Bank
(2021). Exp essed as a pe cen age, he es ima es e lec bo h he angible (e.g., a i s and
anspo a ion cos s) and in angible ba ie s (e.g., cul u al o egula o y disc epancies) o
ade, essen ially ep esen ing he supplemen a y cos s ha would equalize he appeal o
domes ic and in e na ional ade.7
We expec pa ne s ha ace highe bila e al ade cos s o ha e lowe olumes o
alue-added ade, sugges ing a nega i e coe icien o he a iable in ou empi ical model.
The magni ude o he coe icien o he ade cos a iable sheds ligh on he sensi i i y o
alue-added ade o changes in he ade cos s. A la ge nega i e coe icien would sugges
ha e en a small inc ease in he ade cos s could lead o a subs an ial dec ease in he
alue-added ade o he home (hos ) coun ies. Con e sely, a smalle coe icien would
imply ha alue-added ade is less esponsi e o changes in ade cos s.
3.3. Desc ip i e S a is ics
Table 1p esen s he desc ip i e s a is ics. S a ing wi h he dependen a iable se ies,
we no e ha , on a e age, ac oss coun y pai s, he annual g oss expo s and impo s a e
equal o USD 69.6 million and USD 1.874 billion, espec i ely. The a e age o al alue-
added ade om a ypical home coun y included in a ypical hos coun y’s expo is
USD 876.59 million. Manu ac u ing and se ices con ibu e signi ican ly o he o al TiVA,
wi h a e age annual alues o USD 649.39 million and USD 200.35 million. The a e age
alue-added ade in ag icul u al p oduc s (USD 10.56 million) is much lowe .
In ou sample, app oxima ely 36,085 immig an s om a ypical home coun y eside
in a ypical hos coun y. Wi h a s anda d de ia ion o mo e han a qua e million, he e
is conside able a ia ion ac oss coun y pai s. Mo ing o he o he explana o y a iables,
ou da a’s ypical home and hos coun ies exhibi compa able p oduc i e capaci y index
alues (54.11 and 60.01, espec i ely), wi h s anda d de ia ions o 9.55 and 6.34, sugges ing
di e se p oduc i e capaci ies. The ad alo em a i -equi alen bila e al ade cos s ange
om 0.156 pe cen o 954.92 pe cen , wi h a mean o 150.87 pe cen , indica ing addi ional
cos s, ela i e o domes ic ade, o app oxima ely 1.5 imes he alue o he goods.
Economies 2024,12, 222 15 o 21
(in he manu ac u ing sec o ), demons a ing how highe ade cos s educe alue-added
ade ac oss all sec o s.15
The esul s om he Poisson Pseudo-Maximum Likelihood and High-Dimensional
Fixed-E ec s (PPML HDFE) es ima ions p esen ed in Panel B simila ly highligh he s a is i-
cally signi ican impac o immig an s ocks and p oduc i e capaci y indices o he po en ial
ading pa ne s on alue-added ade o igina ing om home coun ies and embedded in
he expo s o hos coun ies. Fo example, wi h an es ima ed coe icien anging om 0.196
(manu ac u ing) o 0.206 ( o al) and 0.298 (ag icul u e), we ind ha a 1 pe cen inc ease
in immig an s ocks leads o an app oxima ely 0.206 pe cen a e age inc ease in he o al
alue-added o igina ing om home coun ies ha a e included in he expo s o he hos
coun ies o he wo ld. This posi i e impac is e en mo e p onounced in he ag icul u e
sec o , wi h a coe icien o 0.298 pe cen .
The consis ency in he posi i e and s a is ically disce nible coe icien s o ou p ima y
a iable o in e es , he immig an s ock, and he co e con ol a iables ( he p oduc i e
capaci y indices), as well as he nega i e impac s o a ise in bila e al ade cos s, ac oss
he h ee di e en es ima ion app oaches we employed, unde sco e he obus ness o ou
indings. Ou es ima ion esul s consis en ly show ha inc eased immig an s ocks signi i-
can ly boos he alue added om home coun ies ha is embedded in he hos coun ies’
expo s o he wo ld a he agg ega e and sec o al le els (ag icul u e, manu ac u ing, and
se ices). The high pseudo-R-squa ed alues and signi ican F-s a is ics ac oss bo h models
u he alida e ha ou conclusions abou he posi i e ela ionship be ween immig an
s ocks and alue-added ade a e obus o di e en es ima ion echniques.
5. Conclusions
Ou esea ch demons a es he signi ican impac o immig an s on alue-added ade
(TiVA) be ween hei home and hos coun ies. Analyzing da a om 2000 o 2018 ac oss
38 OECD hos coun ies and 64 home coun ies, we ind ha a 10 pe cen inc ease in
immig an s ock leads o a 2.08 pe cen inc ease in TiVA.
16
This obse a ion highligh s he
ole o immig an s in alue-added ade h ough skills ans e , knowledge di usion, and
ne wo k c ea ion.
By ocusing on alue-added ade, ou esea ch ex ends he li e a u e on he immig a ion–
ade nexus, enhancing ou unde s anding o immig an s’ con ibu ions o global alue chains.
Immig an s acili a e ade in inal goods and play a i al ole in he ade o in e media e
goods and se ices wi hin mode n global p oduc ion ne wo ks. This insigh suppo s a mo e
comp ehensi e heo y o how human mobili y impac s in e na ional economic in eg a ion.
Using he andom in e cep and andom slope mixed-e ec s model o examine he
ela ionship allows o cap u ing he a ia ion in immig an s’ impac on TiVA ac oss
di e en coun y pai s, p o iding a mo e nuanced pic u e han he adi ional ixed-e ec s
panel da a models. Ou b oad sec o -speci ic analysis depic s ha immig an s’ impac s
a y ac oss he ag icul u al, manu ac u ing, and se ice sec o s, o e ing aluable insigh s
o policymake s and esea che s. Unde s anding hese sec o al di e ences helps iden i y
he speci ic channels h ough which immig an s in luence in e na ional ade.
Beyond depic ing he c ucial ele ance o le e aging immig an s’ con ibu ions o
alue-added ade o enhancing coun ies’ compe i i eness and p ospe i y in an in e -
connec ed wo ld and highligh ing he economic bene i s o di e si y and in e na ional
connec ions, as well as inclusi e immig a ion policies and in e na ional coope a ion, ou
indings ha e impo an implica ions o immig a ion policies, ade nego ia ions, and
immig an in eg a ion p og ams. Policymake s should conside he ade bene i s o im-
mig a ion, ecognizing he posi i e e ec s o immig an s on alue-added ade. T ade
nego ia o s can le e age he ole o immig an ne wo ks in acili a ing ade o in o m
s a egies o ade p omo ion and ma ke access, especially in coun ies wi h signi ican
diaspo a popula ions.
Ta ge ed s a egies can be de eloped o maximize he bene i s o immig an ne -
wo ks, pa icula ly in sec o s whe e he impac o immig an s is mos p onounced. Poli-

Economies 2024,12, 222 16 o 21
cies can acili a e knowledge ans e and ne wo k building in hese high-impac sec o s.
Go e nmen s migh also in es in p og ams suppo ing immig an s’ economic in eg a-
ion, such as language aining and p o essional ne wo king e en s. Suppo ing immi-
g an s and na i e-bo n ci izens’ educa ion and skills de elopmen can enhance a coun y’s
pa icipa ion in global alue chains. These policies can also help small- and medium-
sized en e p ises (SMEs) le e age immig an s’ knowledge and ne wo k connec ions o
in e na ional expansion.
While ou s udy p o ides aluable insigh s in o he impac o immig an s on alue-
added ade, i is essen ial o acknowledge ce ain limi a ions. Al hough ou me hodology
is obus a he agg ega e le el, i may no ully cap u e he nuanced bila e al ela ionships
be ween speci ic coun y pai s o p oduc s. As no ed in oo no es 10 h ough 14, he
impac o immig an s may a y signi ican ly based on ac o s such as he speci ic skills o
immig an g oups, cul u al a ini ies, and p oduc specializa ions. Fo example, he e ec
o I alian a isans on he U.S. luxu y goods sec o o F ench immig an s on Japan’s wine
ma ke would no be applicable o all coun y pai s’ immig an – ade ela ionships.
Despi e hese limi a ions, ou indings o e a aluable ounda ion o unde s and-
ing he b oade impac o immig an s on alue-added ade and highligh he need o
complemen a y, de ailed case s udies. Fu u e esea ch could explo e de ailed sub-sec o
analyses, mechanisms h ough which immig an s acili a e TiVA, he impac o immig an s’
composi ion and educa ional a ainmen on TiVA, and he e ec s o changing immig a ion
policies o e ime.
Au ho Con ibu ions: Concep ualiza ion, B.T. and R.W.; me hodology, B.T.; so wa e, B.T.; ali-
da ion, R.W.; o mal analysis, B.T.; in es iga ion, R.W.; o mal analysis, B.T.; esou ces, R.W.; da a
cu a ion, B.T. and R.W.; w i ing—o iginal d a p epa a ion, B.T.; w i ing— e iew and edi ing,
R.W.; isualiza ion, B.T. and R.W. 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.
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 o iginal con ibu ions p esen ed in he s udy a e included in he
a icle. Fu he inqui ies can be di ec ed o he co esponding au ho .
Con lic s o In e es : The au ho s decla e no con lic o in e es .
Appendix A
Table A1. De e minan s o TiVA; esul s om mixed-e ec s model es ima ion wi h in e ac ion e ec s.
T ade in Value Added (TiVA) G oss Impo s and Expo s
(a) (b) (c) (d) (e) ( )
Va iables l i a_ o l i a_ag l i a_mn l i a_se log(gimp) log(gexp)
Ln (Immig) −0.965 *** −0.953 *** −0.649 *** −1.372 *** −0.0209 *** −0.135 ***
(0.0864) (0.100) (0.0903) (0.0870) (0.0081) (0.018)
Ln (PCI1) 3.412 *** 4.203 *** 3.244 *** 3.471 *** 3.599 *** 0.339
(0.102) (0.118) (0.107) (0.103) (0.115) (0.288)
Ln (Immig)#ln (PCI1) 0.0348 *** 0.0445 *** 0.0477 *** 0.0581 *** −0.0357 ** 0.359 ***
(0.0132) (0.0153) (0.0138) (0.0133) (0.0150) (0.0373)
Ln (PCI2) 4.358 *** 4.991 *** 4.831 *** 3.186 *** 5.378 *** 2.061 ***
(0.155) (0.180) (0.162) (0.157) (0.177) (0.479)
Ln (Immig)#ln (PCI2) 0.273 *** 0.272 *** 0.198 *** 0.346 *** 0.0954 *** −0.217 ***
(0.0242) (0.0279) (0.0253) (0.0243) (0.0275) (0.0693)
Ln (TRcos ) −0.399 *** −0.453 *** −0.455 *** −0.305 *** −0.450 *** −1.219 ***
(0.0114) (0.0133) (0.0120) (0.0115) (0.0131) (0.0465)
Cons an −26.18 *** −36.21 *** −27.41 *** −24.02 *** −29.97 *** −2.196
(0.628) (0.700) (0.652) (0.632) (0.692) (2.091)
Economies 2024,12, 222 17 o 21
Table A1. Con .
T ade in Value Added (TiVA) G oss Impo s and Expo s
(a) (b) (c) (d) (e) ( )
Va iables l i a_ o l i a_ag l i a_mn l i a_se log(gimp) log(gexp)
Random-e ec s componen s:
S . De . (Region) −0.0500 −0.146 −0.0412 −0.0504 −0.121 −0.696 ***
(0.220) (0.224) (0.223) (0.218) (0.228) (0.223)
S . De . (Immig) −0.668 *** −0.444 *** −0.651 *** −0.555 *** −0.687 *** −2.086 ***
(0.0250) (0.0243) (0.0254) (0.0232) (0.0253) (0.145)
S . De . (Panel) 1.379 *** 1.585 *** 1.414 *** 1.428 *** 1.373 *** 0.143 *
(0.0250) (0.0245) (0.0252) (0.0241) (0.0246) (0.0762)
S . De . (Residual) −1.156 *** −1.008 *** −1.112 *** −1.155 *** −1.011 *** 0.717 ***
(0.00433) (0.00437) (0.00432) (0.00433) (0.00430) (0.00407)
Log-likelihood −17,650 −22,517 −19,183 −17,708 −22,143 −71,547
Chi-squa e (o e all) 36,049 36,436 31,839 33,841 27,956 5851
AIC 35,324.93 45,057.18 38,389.87 35,439.78 44,310.15 143,118.8
BIC 35,426.05 45,158.3 38491.0 35,540.9 44,411.27 143,219.6
ICC ( egion- home) 0.994 *** 0.9946 *** 0.9937 *** 0.9945 *** 0.9919 *** 0.8733 ***
(0.003) (0.0010) (0.0010) (0.0011) (0.0013) (0.0013)
Obse a ions 33,754 33,754 33,754 33,754 33,754 33,754
S anda d e o s in pa en heses; *** p< 0.01, ** p< 0.05, and * p< 0.1
Table A2. The E ec o Immig an s on Value-Added T ade, Resul s om HDFE and PPML Es ima ion
App oaches.
Panel A: Mul ile el Linea Model Es ima ion Resul s
Dep Va iable: Value Added G ade (Logs) G oss Expo s and Impo s
(a) (b) (c) (d) (e) ( )
VARIABLES Ti a_To al Ti a_Ag i Ti a_Mn Ti a_Se G _Imp G _Exp
Ln (Immig) 0.103 *** 0.122 *** 0.0954 *** 0.117 *** 0.155 *** 0.141 ***
(0.0024) (0.0025) (0.0024) (0.0024) (0.0029) (0.0093)
Ln (PCI1) 1.784 *** 1.859 *** 1.759 *** 1.890 *** 2.065 *** 0.959 ***
(0.0737) (0.0782) (0.0740) (0.0751) (0.0881) (0.291)
Ln (PCI2) 1.470 *** 1.565 *** 1.601 *** 0.559 *** 2.787 *** 1.084 *
(0.145) (0.154) (0.146) (0.148) (0.168) (0.564)
Ln (TRcos ) −1.529 *** −1.521 *** −1.579 *** −1.424 *** −1.801 *** −1.850 ***
(0.0106) (0.0112) (0.0106) (0.0108) (0.0128) (0.0405)
Cons an −1.727 ** −6.944 *** −2.332 *** −0.465 −6.037 *** 4.143
(0.671) (0.713) (0.674) (0.684) (0.783) (2.611)
Obse a ions 31,769 31,769 31,769 31,769 31,769 31,769
R−Squa ed (Wi hin) 0.566 0.551 0.571 0.540 0.564 0.122
Log Likelihood −26,718 −28,623 −26,865 −27,331 −35,856 −66,807
F−S a is ic 10,334 9701 10,549 9288 10,870 1063
RMSE 0.562 0.597 0.565 0.573 0.702 2.119
Panel B: Mul ile el PPML
Es ima ion Resul s
Dep Va iable: Value Added T ade (Le els) G oss Expo s and Impo s
VARIABLES TOT AGR MNF SER IMP EXP
Ln (Immig) 0.203 *** 0.299 *** 0.193 *** 0.222 *** 0.257 *** 0.292 ***
(0.0127) (0.0153) (0.0132) (0.0118) (0.0128) (0.0162)
Ln (PCI1) 2.651 *** 1.898 *** 3.054 *** 1.856 *** 2.677 *** 3.716 ***
(0.245) (0.272) (0.269) (0.231) (0.227) (0.575)
Ln (PCI2) 2.802 *** 2.041 *** 3.032 *** 2.606 *** 3.597 *** 2.009 *
(0.513) (0.435) (0.551) (0.552) (0.428) (1.161)
Ln (TRcos ) −0.750 *** −0.719 *** −0.797 *** −0.603 *** −0.864 *** −0.821 ***
(0.0640) (0.0768) (0.0632) (0.0671) (0.0658) (0.0688)
Cons an −13.13 *** −12.49 *** −15.61 *** −11.34 *** −15.06 *** −14.12 ***
(2.639) (2.563) (2.877) (2.584) (2.234) (5.377)
Obse a ions 31,769 31,769 31,769 31,769 31,769 31,769
Psuedo R−Squa e 0.918 0.861 0.921 0.913 0.940 0.783
Log Likelihood −3.719 ×106−85,740 −2.813 ×106−898,260 −1.440 ×107−2.770 ×107
Chi−Squa e 3075 7068 2678 3361 7055 1845
RMSE 0.566 0.561 0.567 0.561 0.505 0.976
S anda d e o s in pa en heses; *** p< 0.01, ** p< 0.05, and * p< 0.1
Economies 2024,12, 222 18 o 21
Table A3. Lis o OECD Membe Hos Coun ies Included in he S udy.
OECD Membe Hos Coun ies
Aus alia Finland Ko ea Slo akia
Aus ia F ance La ia Slo enia
Belgium Ge many Li huania Spain
Canada G eece Luxembou g Sweden
Chile Hunga y Mexico Swi ze land
Colombia Iceland Ne he lands Tü kiye
Cos a Rica I eland New Zealand Uni ed Kingdom
Czech Republic Is ael No way Uni ed S a es
Denma k I aly Poland
Es onia Japan Po ugal
No es
1
Rauch (2001) no es ha businesses mee local demand by le e aging immig an expe ise o cus omize hei p oduc s and se ices,
he eby adding alue and gaining a compe i i e ad an age in o eign ma ke s.
2
A sepa a e su ey by Ha zigeo giou and Lode alk (2021) also epo s a consis en posi i e in luence o immig an s on home–hos
coun y ade.
3
In ancilla y es ima ions, he esul s o which can be ob ained om he au ho s, we eplace he ade cos measu e wi h s anda d
g a i y model a iables, including geodesic dis ance (a common p oxy o anspo a ion cos s), economic emo eness ( o
ep esen mul ila e al esis ance o ade), and dummy a iables ha iden i y whe he coun ies a e landlocked, ha e a p io
colonial ela ionship, sha e a common bo de o language, o a e pa ies o one o mo e ade ag eemen (s). The al e na i e
speci ica ion is as ollows:
lnYij =β0+β1lnGDPCi +β2lnGDPCj +β3lnGDISTij +β4REMTi +β5REMTj
+β6LLOCKi+β7LLOCKj+β8COMLANGij +β9FTAij +β10lnImmigij +ϵij
4
One o he key bene i s o mul ile el models o e he linea high-dimensional ixed-e ec s (HDFE) app oach is hei abili y
o inco po a e bo h ixed and andom e ec s. This lexibili y allows o modeling andom a ia ions ac oss di e en le els o
he hie a chy, imp o ing he abili y o gene alize indings beyond he sampled da a (Bell and Jones 2015). By inco po a ing
andom e ec s, mul ile el models also o e be e es ima es o g oup-le el e ec s, such as coun y-speci ic e ec s, while
accoun ing o unobse ed he e ogenei y wi hin g oups (e.g., home coun ies in he same egion). This can yield mo e eliable
and comp ehensi e esul s (B owne e al. 2018). Mul ile el models also p o ide enhanced in e p e abili y, pa icula ly in
hie a chical se ings. They allow o he sepa a e es ima ion o wi hin-g oup and be ween-g oup e ec s, o e ing clea e insigh s
in o ela ionships a di e en le els o analysis. This can be especially aluable o unde s anding he dynamics wi hin and
be ween di e en g oups in a da ase , such as egions o ins i u ions (Raudenbush and B yk 2002).
5
Fo example, a ech manu ac u e in he hos (home) coun y migh ely on speci ic semiconduc o componen s om he
immig an ’s home (hos ) coun y, enabling he e icien sou cing o componen s, in eg a ion in o he manu ac u ing p ocess, and
he global expo o he inal p oduc .
6
The Wo ld Bank (2019) posi s ha na u al capi al, and he a ailabili y o a skilled wo k o ce a e pi o al o a na ion’s compe i i e
edge. Limão and Venables (2001) highligh he impo ance o e icien anspo ne wo ks and he ans o ma i e na u e o ICT
in eg a ion and accessibili y in mode n economies. McMillan e al. (2017) unde sco e he impo ance o s uc u al economic
shi s, while Robinson and Acemoglu (2012) s ess he signi icance o ins i u ional amewo ks in shaping economic in e ac ion
and he cen al ole o he p i a e sec o in g ow h dynamics, espec i ely. Thus, a coun y wi h a obus p oduc i e capaci y can
specialize in p oducing speci ic componen s o s ages o p oduc ion mo e e icien ly and economically a he han manu ac u ing
he en i e p oduc .
7
I is impo an o no e ha he ad alo em a i -equi alen ade cos es ima es include he ade cos s o all goods (some o
which a e no aded in e na ionally); he es ima es also a y g ea ly depending on unde lying assump ions used o he elas ici y
o subs i u ion; hence, such es ima es should p e e ably be used o compa a i e exe cise, o analyze changes in ade cos s o e
ime, o o echnical analysis, such as in an econome ic model o ade (UNESCAP 2021).
8
Fo example, a coun y pai ha is one s anda d de ia ion abo e he mean migh ha e mo e a o able ini ial condi ions o
inhe en cha ac e is ics ha inc ease hei alue-added ade.
9
Fo b e i y, es ima ion esul s wi h he in e ac ion e ms om which he ma ginal e ec s p esen ed in Table 3a e de i ed a e
p esen ed in Appendix ATable A1.
10
One example is skilled I alian a isans mig a ing o he U.S. and con ibu ing o he luxu y goods sec o , inc easing he alue
added in Ame ican expo s o designe p oduc s back o I aly o o o he ma ke s.
Economies 2024,12, 222 19 o 21
11
F ench immig an s in Japan, o example, may in luence he Japanese demand o F ench luxu y goods while also helping F ench
winemake s ailo hei p oduc s o he Japanese pala e, he eby enhancing TiVA be ween he coun ies.
12
Fo ins ance, he ech indus y in Silicon Valley has signi ican ly bene i ed om immig an s’ con ibu ions o so wa e de elop-
men and IT ha ha e bols e ed he alue added o U.S. expo s in hese sec o s (Saxenian 2006).
13
An example would be Vie namese immig an s in Aus alia who inc ease TiVA by s a ing a sea ood p ocessing i m ha expo s
high-quali y sea ood p oduc s o Vie nam.
14
Mexican U.S. immig an s may use hei ne wo ks o help U.S. i ms na iga e he Mexican ma ke o e ined pe oleum p oduc s,
adding alue o U.S. expo s.
15 To add ess he conce ns abou po en ial e e se causali y, we also es ima e ou models using a one-pe iod lag o he immig an
s ock a iable. The esul s, p esen ed in Appendix ATable A2, emain consis en and s a is ically signi ican , wi h minimal
coe icien changes compa ed o ou o iginal es ima ions.
16 Appendix ATable A3 p o ides he lis o OECD membe hos coun ies included in he p esen s udy.
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